Model rankings

Models ranked by quality, speed, and cost.

Compare the live MindsHub catalog by capability, response time, and measured cost per task. For newer releases beyond this catalog, read the model comparison.

Free tier

Use the included models at no charge with your MindsHub account.

$0 No credit card required

Included models

MindsHub Air model

A general-purpose model for everyday work with agents.

Use in MindsHub Agents or through MindsHub Inference.

API alias mindshub_air Use Air with the API →

Jev

TypeSafe’s decision model for classification, routing and scoring.

Get choices, scores and probabilities through the Decisions API.

API alias jev Jev API guide →
Use cases

What are you building?

Choose a model for the kind of work you run.

  • Agentic coding

    Many steps, many files, and the model has to keep its own plan straight for an hour. A one-shot index only half predicts that, so run your own repo through the top two.

    On a budget
    DeepSeek V4.1 Flash $0.27/task at top effort
  • The genuinely hard problems

    Research, analysis and anything where being wrong is expensive.

    On a budget
    GPT-6.1 Sol $0.72/task at top effort
  • Anything a person waits on

    For chat and other interactive work, test a lower reasoning setting and measure the wait on your own requests.

  • Documents, images, audio, video

    One request carrying a whole corpus of mixed media, reasoned over as a unit.

    On a budget
    Gemini 3.7 Flash $0.93/task at top effort
  • High volume, tight budget

    Classification, extraction, tagging — millions of calls where the bill is the constraint.

  • Weights you can run yourself

    Data that cannot leave your environment, or volume that beats renting.

    Pick
    GLM 5.3 or Kimi K3
    On a budget
    GLM 5.3 Flash $0.25/task at top effort
Leaderboard

Compare the full catalog.

Sort and filter the table, then expand a row for context, modalities, reasoning settings, and billing notes.

The models MindsHub serves, ranked by quality index, with a coding read, output speed, latency, measured cost per task at top reasoning effort, price per million tokens, context window and weight availability.
Anthropic opus-5-5 58 Frontier 66.9% 93 tok/sec 692.6s first answer $5.98 $4 / $20 our rate 1M Closed

Difficult reasoning, code changes and document work

Pick it when
Your evaluation needs a stronger candidate for difficult reasoning, code changes or document work.
Skip it when
Routine work already passes with a cheaper model.
Inputs
TextImages
API alias
opus-5-5 opus The first names exactly this model and never moves. The second is the rotating alias for its line: it points here today and follows the line when we move it. Both reach the same model — see Rotating aliases.
Reasoning effort
lowmediumhighxhighmax We send high unless you ask for another. Benchmark figures use the highest published source setting; this route supports up to max. Our default can differ from the benchmark in quality, cost and wait.
Worth knowing
Artificial Analysis measures max effort with the default fallback: 58 at $5.98 per benchmark task. High effort scores 54 at $1.82. Test the extra reasoning against your own acceptance criteria.
Anthropic sonnet-5-5 56 Frontier 61.0% 138 tok/sec 438.4s first answer $5.46 $2 / $10 our rate 1M Closed

Reasoning and coding with effort tuned to the task

Pick it when
You want to compare the newer Sonnet with Opus on code and document work at the same effort.
Skip it when
You are choosing by token price alone: it has half Opus 5.5's token rates, but at max effort it finishes a benchmark task for only about 9% less.
Inputs
TextImages
API alias
sonnet-5-5 sonnet The first names exactly this model and never moves. The second is the rotating alias for its line: it points here today and follows the line when we move it. Both reach the same model — see Rotating aliases.
Reasoning effort
lowmediumhighxhighmax We send high unless you ask for another. Benchmark figures use the highest published source setting; this route supports up to max. Our default can differ from the benchmark in quality, cost and wait.
Worth knowing
Artificial Analysis measures max with the default fallback at 56 and $5.46 per task. Xhigh scores 52 at $2.01; high scores 47 at $0.88. These are separate configurations, not a maximum bill.
OpenAI gpt-6-astra 53 Frontier 56.5% 48 tok/sec 410.6s first answer $3.26 $10 / $50 our rate 1.05M Closed

Hard end-to-end work across code, browsers, and professional files

Pick it when
The job is a long, tool-driven run — a browser to operate, professional files to work through, a complicated task to finish with little guidance — and you want a premium specialist for it rather than a general flagship.
Skip it when
Drafting, summaries and routine analysis: GPT-6.1 Sol scores a point lower for $0.72 a task against $3.26, and the GPT 5.6 family covers the same work at a fraction of the rate card.
Inputs
TextImages
API alias
gpt-6-astra gpt The first names exactly this model and never moves. The second is the rotating alias for its line: it points here today and follows the line when we move it. Both reach the same model — see Rotating aliases.
Reasoning effort
lowmediumhighxhighmax We send medium unless you ask for another. Benchmark figures use the highest published source setting; this route supports up to max. Our default can differ from the benchmark in quality, cost and wait.
Worth knowing
At max, Artificial Analysis measures 53 and $3.26 per task. Xhigh scores 52 at $2.31. Test whether the extra reasoning improves your accepted results; neither figure is a spending limit.
Anthropic fable-5-1 53 Frontier 63.1% 69 tok/sec 286.0s first answer $7.63 $10 / $50 our rate 1M Closed

Difficult reasoning and coding, with a safeguard fallback

Pick it when
The problem is at the edge of what any model clears, the run is long, and being wrong costs more than the premium rate does.
Skip it when
Routine work, or anything a cheaper frontier row already clears — Claude Opus 5.5 scores five points higher at $5.98 a task against $7.63, Opus 5 sits two points back at $5.86, and GPT-6 Astra ties it at 53 for $3.26, under half the cost.
Inputs
TextImages
API alias
fable-5-1 fable The first names exactly this model and never moves. The second is the rotating alias for its line: it points here today and follows the line when we move it. Both reach the same model — see Rotating aliases.
Reasoning effort
lowmediumhighxhighmax We send high unless you ask for another. Benchmark figures use the highest published source setting; this route supports up to max. Our default can differ from the benchmark in quality, cost and wait.
Worth knowing
"With fallback" is Artificial Analysis's label for the API's default configuration: the small share of prompts Anthropic's safeguard classifiers flag — cybersecurity and biology, fewer than 5% of sessions by Anthropic's count — is answered by a fallback Claude model, and the score above includes those answers. The dial matters as much as the model here: at xhigh Artificial Analysis measures the same 53 for $5.98 a task, at high 51 for $3.91 — Opus 5's score for a third less — and at medium 49 for $2.98, a point below Fable 5 at about a third of its cost.
OpenAI gpt-sol-6-1 52 Frontier 54.2% 58 tok/sec 314.5s first answer $0.72 $2 / $10 our rate 1.05M Closed

Coding and multi-step agent work at GPT-6 Sol's list rates

Pick it when
You are upgrading from GPT-6 Sol and can test the same workload at the effort you would use.
Skip it when
You need a higher score on hard agentic work: GPT-6 Astra scores a point higher at $3.26 a task against $0.72, and Claude Opus 5.5 six points higher at $5.98.
Inputs
TextImages
API alias
gpt-sol-6-1 gpt-sol The first names exactly this model and never moves. The second is the rotating alias for its line: it points here today and follows the line when we move it. Both reach the same model — see Rotating aliases.
Reasoning effort
lowmediumhighxhighmax We send medium unless you ask for another. Benchmark figures use the highest published source setting; this route supports up to max. Our default can differ from the benchmark in quality, cost and wait.
Worth knowing
Artificial Analysis lists this version at max effort, scoring 52 at $0.72 per task. Xhigh scores 51 at $0.39 and high 50 at $0.32. OpenAI released it in its API on September 29, 2026 as gpt-6.1-sol.
Anthropic opus-5 51 Frontier 56.4% 52 tok/sec 54.3s first answer $5.86 $5 / $25 our rate 1M Closed

Reasoning, coding and review for existing Opus 5 workflows

Pick it when
You have hard, multi-step work validated on Opus 5 and re-testing it on Opus 5.5 is not yet worth the interruption.
Skip it when
You are starting fresh — Claude Opus 5.5 scores seven points higher at lower token rates, and at high effort it still scores 54 for $1.82 a task against this row's $5.86.
Inputs
TextImages
API alias
opus-5 Names exactly this model version and never moves.
Reasoning effort
lowmediumhighxhighmax We send high unless you ask for another. Benchmark figures use the highest published source setting; this route supports up to max. Our default can differ from the benchmark in quality, cost and wait.
Worth knowing
This row quotes max at 51 and $5.86 per benchmark task. Xhigh measures 50 at $4.88, and high measures 48 at $3.61. Test the lower settings on your work; these averages do not establish a maximum bill.
Anthropic fable-5 50 Frontier 61.0% 63 tok/sec 107.0s first answer $8.75 $10 / $50 our rate 1M Closed

The previous Fable, for traffic already validated against it

Pick it when
You have production traffic validated against this version and re-testing it on 5.1 is not yet worth the interruption.
Skip it when
You are starting fresh — Fable 5.1 scores three points higher on the same list price, and at high it still clears this row's 50 by a point for $3.91 a task against $8.75. Claude Opus 5.5 scores eight points higher at $5.98 a task.
Inputs
TextImages
API alias
fable-5 Names exactly this model version and never moves.
Reasoning effort
lowmediumhighxhighmax We send high unless you ask for another. Benchmark figures use the highest published source setting; this route supports up to max. Our default can differ from the benchmark in quality, cost and wait.
OpenAI gpt-sol-6 48 Frontier 57.6% 85 tok/sec 132.5s first answer $1.04 $2 / $10 our rate 1.05M Closed

The previous Sol, for agent and coding work already validated on it

Pick it when
You have work validated on GPT-6 Sol and re-testing it on GPT-6.1 Sol is not yet worth the interruption.
Skip it when
You are starting fresh — GPT-6.1 Sol scores four points higher at the same $2 / $10 list rates, with cheaper cached input, for $0.72 a task against $1.04.
Inputs
TextImages
API alias
gpt-sol-6 Names exactly this model version and never moves.
Reasoning effort
nonelowmediumhighxhighmax We send medium unless you ask for another. Benchmark figures use the highest published source setting; this route supports up to max. Our default can differ from the benchmark in quality, cost and wait.
Worth knowing
Artificial Analysis reports 48 at $1.04 per benchmark task at max effort, versus 47 at $1.99 for GPT-5.6 Sol and 52 at $0.72 for GPT-6.1 Sol.
Meta muse-spark-1-3 48 Frontier 58.8% 97 tok/sec 70.5s first answer $1.60 $1.25 / $4.25 our rate 1M Closed

Long-context agentic coding that reads text, images and video

Pick it when
Long agent and coding runs over mixed inputs, where a capable closed model at a low rate beats owning the weights and Meta is an acceptable processor of your data.
Skip it when
You need weights to host — the Muse family is closed — or your data cannot go to Meta, and the Contributor discount does not change that: it is paid for with your prompts.
Inputs
TextImagesVideo
API alias
muse-spark-1-3 muse-spark The first names exactly this model and never moves. The second is the rotating alias for its line: it points here today and follows the line when we move it. Both reach the same model — see Rotating aliases.
Reasoning effort
Single setting — no dial. This route exposes no effort dial. The benchmark uses the source configuration and endpoint; your wait and cost can differ.
Worth knowing
Two rate cards. Artificial Analysis costs it at Meta's Standard rate, which is the one this row prints; the Contributor tier is far cheaper in exchange for training on your prompts and replies, and has no published cost per task. Fine for hobby projects, an easy no for anything confidential.
OpenAI gpt-5-6-sol 47 Frontier 57.1% 74 tok/sec 98.0s first answer $1.99 $5 / $30 our rate 1.05M Closed

General reasoning and coding work with OpenAI's tooling around it

Pick it when
You have work validated on GPT 5.6 Sol and re-testing it on GPT-6.1 Sol is not yet worth the interruption.
Skip it when
You are starting fresh — GPT-6.1 Sol scores five points higher at half the token rates, for $0.72 a task against $1.99, and GPT 5.6 Terra scores five points lower for about 30% less per finished task.
Inputs
TextImages
API alias
gpt-5-6-sol Names exactly this model version and never moves.
Reasoning effort
nonelowmediumhighxhighmax We send medium unless you ask for another. Benchmark figures use the highest published source setting; this route supports up to max. Our default can differ from the benchmark in quality, cost and wait.
SpaceXAI grok-4-7 46 Frontier 57.4% 65 tok/sec 70.5s first answer $3.74 $2 / $6 our rate 500K Closed

Long coding and knowledge-work runs with web and X tools

Pick it when
You want to test the newer Grok on multi-step coding or research workflows that need web and X search.
Skip it when
Low task cost or a context window beyond 500k tokens is the priority.
Inputs
TextImages
API alias
grok-4-7 grok The first names exactly this model and never moves. The second is the rotating alias for its line: it points here today and follows the line when we move it. Both reach the same model — see Rotating aliases.
Reasoning effort
lowmediumhighxhigh We send high unless you ask for another. Benchmark figures use the highest published source setting; this route supports up to xhigh. Our default can differ from the benchmark in quality, cost and wait.
Worth knowing
At xhigh, Artificial Analysis measures 46 at $3.74 per task. High also rounds to 46 at $2.73. The standard token rates match Grok 4.6, but this benchmark run costs more. This row excludes the separately priced fast variant.
Zhipu via Fireworks AI glm-5-3 45 Frontier 59.0% 62 tok/sec 26.8s first answer $2.01 $1.40 / $4.40 our rate 1M Open GLM-5.3 License

Frontier-class coding and security review at a low rate

Pick it when
You want strong coding and security review at a fraction of frontier prices, rented or on your own hardware.
Skip it when
You need image input, or plain MIT terms — this one is Zhipu's own GLM-5.3 License, which allows commercial use with conditions.
Inputs
Text
API alias
glm-5-3 glm The first names exactly this model and never moves. The second is the rotating alias for its line: it points here today and follows the line when we move it. Both reach the same model — see Rotating aliases.
Reasoning effort
lowhighmax We send max unless you ask for another. Benchmark figures use the highest published source setting; this route supports up to max. A lower setting may reduce cost and wait; test whether it still clears your tasks.
Licence
GLM-5.3 License
Served by
Fireworks AI Zhipu makes it. We buy the inference from Fireworks AI, which is the name the rate card shows.
Worth knowing
Zhipu released the weights at the end of August under its own GLM-5.3 License, which allows commercial use with conditions — read the terms before you build on it. A point ahead of Kimi K3 on the index at the same cost per task to within a cent, and it streams faster; Kimi takes images, this does not.
SpaceXAI grok-4-6 44 Near-frontier 53.0% 62 tok/sec 45.1s first answer $1.75 $2 / $6 our rate 500K Closed

Reasoning with access to the live web

Pick it when
You need information from this morning in the same call as the reasoning.
Skip it when
Your agents live in a terminal, or your prompts are enormous — the window is half what most of this board offers.
Inputs
TextImages
API alias
grok-4-6 Names exactly this model version and never moves.
Reasoning effort
lowmediumhighxhigh We send high unless you ask for another. Benchmark figures use the highest published source setting; this route supports up to xhigh. Our default can differ from the benchmark in quality, cost and wait.
Worth knowing
This row quotes xhigh at 44 and $1.75 per benchmark task. High also rounds to 44 at $1.48. Compare the effort settings on your own work before paying for more reasoning.
Moonshot AI via Fireworks AI kimi-k3 44 Near-frontier 59.5% 41 tok/sec 52.0s first answer $2.00 $3 / $15 our rate 1M Open Kimi K3 License

Long autonomous coding runs you can self-host

Pick it when
You want one of the strongest open-weights models with image input as well as text — GLM-5.3 sits a point ahead on the index but reads text only.
Skip it when
The token rate is the point — GLM-5.3 charges well under half per token for a point more on the index, though the two finish a task for about the same.
Inputs
TextImages
API alias
kimi-k3 kimi The first names exactly this model and never moves. The second is the rotating alias for its line: it points here today and follows the line when we move it. Both reach the same model — see Rotating aliases.
Reasoning effort
Single setting — no dial. This route exposes no effort dial. The benchmark uses the source configuration and endpoint; your wait and cost can differ.
Licence
Kimi K3 License
Served by
Fireworks AI Moonshot AI makes it. We buy the inference from Fireworks AI, which is the name the rate card shows.
Worth knowing
The licence is Moonshot's own, not MIT or Apache. Commercial use is allowed with conditions that start at scale, including attribution for very large products and a separate agreement for large model-as-a-service operators, so read it before you build on it.
Zhipu via Fireworks AI glm-flash-5-3 42 Near-frontier 51.6% 51 tok/sec 41.0s first answer $0.25 $0.15 / $0.50 our rate 1M Open MIT

A high score per dollar, on MIT-licensed weights

Pick it when
You want a high score per dollar on MIT weights, with the image input the GLM flagship lacks.
Skip it when
Your prompts are short and interactive — it answers at length, so a finished task costs more than its rate card suggests.
Inputs
TextImages
API alias
glm-flash-5-3 glm-5-3-flash The first names exactly this model and never moves. The second is the rotating alias for its line: it points here today and follows the line when we move it. Both reach the same model — see Rotating aliases.
Reasoning effort
lowhighmax We send max unless you ask for another. Benchmark figures use the highest published source setting; this route supports up to max. A lower setting may reduce cost and wait; test whether it still clears your tasks.
Licence
MIT
Served by
Fireworks AI Zhipu makes it. We buy the inference from Fireworks AI, which is the name the rate card shows.
Worth knowing
Artificial Analysis measures it as very verbose, so a finished task uses more tokens, and costs more, than its rate card suggests. First natively multimodal model in the GLM-5 line — 320B total parameters, 18B active.
OpenAI gpt-terra-5-6 42 Near-frontier 55.0% 98 tok/sec 111.2s first answer $1.40 $2 / $12 our rate 1.05M Closed

Balanced mid-tier for everyday work

Pick it when
You have work validated on GPT 5.6 Terra, or you want a shorter wait for the first answer than GPT-6 Sol or GPT-6.1 Sol give at max effort.
Skip it when
Score or cost decides it — GPT-6.1 Sol scores ten points higher for $0.72 a task against $1.40, at a lower output rate.
Inputs
TextImages
API alias
gpt-terra-5-6 gpt-terra The first names exactly this model and never moves. The second is the rotating alias for its line: it points here today and follows the line when we move it. Both reach the same model — see Rotating aliases.
Reasoning effort
nonelowmediumhighxhighmax We send medium unless you ask for another. Benchmark figures use the highest published source setting; this route supports up to max. Our default can differ from the benchmark in quality, cost and wait.
Google gemini-flash-3-8 41 Strong 56.6% 122 tok/sec 27.2s first answer $1.24 $0.75 / $3.75 our rate 1M Closed

Multimodal agents and long coding work

Pick it when
Mixed-media inputs — text, images, audio, video — feeding an agent or a long coding session, where its two-point lead over 3.7 Flash is worth the longer wait.
Skip it when
The problem is genuinely hard: its reasoning sits below the leaders, and Google itself says it can spend more tokens and tool calls than 3.7 Flash on difficult work. If a person is waiting, 3.7 Flash starts answering sooner and streams faster for less per task. Budget with the post-introductory price in mind.
Inputs
TextImagesAudioVideo
API alias
gemini-flash-3-8 gemini-flash The first names exactly this model and never moves. The second is the rotating alias for its line: it points here today and follows the line when we move it. Both reach the same model — see Rotating aliases.
Reasoning effort
lowmediumhigh We send medium unless you ask for another. Benchmark figures use the highest published source setting; this route supports up to high. Our default can differ from the benchmark in quality, cost and wait.
Meta muse-spark-1-2 40 Strong 57.4% 402 tok/sec 15.5s first answer $0.97 $1.25 / $4.25 our rate 1M Closed

Cheap closed model that powers the free Meta AI

Pick it when
You want a fast, capable, every-input model and Meta is an acceptable processor of your data.
Skip it when
You need weights — the Muse family is closed — or your data cannot go to Meta.
Inputs
TextImagesAudioVideo
API alias
muse-spark-1-2 Names exactly this model version and never moves.
Reasoning effort
Single setting — no dial. This route exposes no effort dial. The benchmark uses the source configuration and endpoint; your wait and cost can differ.
Worth knowing
Meta publishes a "contributor" tier at roughly a fifteenth of the standard rate in exchange for training on your prompts and replies. Fine for hobby projects, an easy no for anything confidential.
Alibaba via Fireworks AI qwen-3-8-a95b 40 Strong 54.1% 39 tok/sec 54.2s first answer $2.16 $2 / $6 our rate 262K Open Qwen3.8-Max License

The open-weights Qwen checkpoint, for teams that host their own models

Pick it when
You need the weights, and text-only input plus a licence with conditions are acceptable.
Skip it when
You plan to resell access at scale, or your inputs are not text.
Inputs
Text
API alias
qwen-3-8-a95b qwen The first names exactly this model and never moves. The second is the rotating alias for its line: it points here today and follows the line when we move it. Both reach the same model — see Rotating aliases.
Reasoning effort
lowmediumxhigh We send xhigh unless you ask for another. Benchmark figures use the highest published source setting; this route supports up to xhigh. A lower setting may reduce cost and wait; test whether it still clears your tasks.
Licence
Qwen3.8-Max License
Served by
Fireworks AI Alibaba makes it. We buy the inference from Fireworks AI, which is the name the rate card shows.
Worth knowing
Artificial Analysis costs it at Alibaba's own $2 / $6 — the same rate card as the proprietary Max — but the weights are downloadable, so your actual bill is whatever your host or your hardware charges. Its Qwen3.8-Max License allows commercial use with conditions, including separate authorization for large model-as-a-service and AI work-assistant businesses, so read it before you build on it.
DeepSeek via Fireworks AI deepseek-v4-1-flash 39 Strong 51.9% 212 tok/sec 10.4s first answer $0.27 $0.30 / $1.20 our rate 1M Open MIT

Low-cost text and image work on MIT-licensed weights

Pick it when
High-volume text and image work that still wants step-by-step reasoning, on weights you can take with you.
Skip it when
You need audio or video input, or the last few points of quality.
Inputs
TextImages
API alias
deepseek-v4-1-flash deepseek-v4-flash The first names exactly this model and never moves. The second is the rotating alias for its line: it points here today and follows the line when we move it. Both reach the same model — see Rotating aliases.
Reasoning effort
nonelowhighmax We send high unless you ask for another. Benchmark figures use the highest published source setting; this route supports up to max. Our default can differ from the benchmark in quality, cost and wait.
Licence
MIT
Served by
Fireworks AI DeepSeek makes it. We buy the inference from Fireworks AI, which is the name the rate card shows.
SpaceXAI grok-4-5 39 Strong 55.0% 49 tok/sec 16.9s first answer $0.88 $2 / $6 our rate 500K Closed

Earlier Grok for existing integrations and cost comparisons

Pick it when
You want most of 4.6 for much less per task, or you have production traffic validated against this version.
Skip it when
You need the higher general score of a newer Grok and have verified that it improves your tasks.
Inputs
TextImages
API alias
grok-4-5 Names exactly this model version and never moves.
Reasoning effort
lowmediumhigh We send high unless you ask for another. Benchmark figures use the highest published source setting; this route supports up to high. A lower setting may reduce cost and wait; test whether it still clears your tasks.
Google gemini-flash-3-7 39 Strong 57.2% 290 tok/sec 11.9s first answer $0.93 $0.75 / $3.75 our rate 1M Closed

Fast multimodal work at a promotional price

Pick it when
Inputs are large or mixed-media — PDFs, images, audio, video — and you want them read quickly.
Skip it when
You need frontier-level reasoning, or weights you can host yourself.
Inputs
TextImagesAudioVideo
API alias
gemini-flash-3-7 Names exactly this model version and never moves.
Reasoning effort
lowmediumhigh We send medium unless you ask for another. Benchmark figures use the highest published source setting; this route supports up to high. Our default can differ from the benchmark in quality, cost and wait.
MindsHub mindshub_air Free tier 38 Solid 54.6% 135 tok/sec 105.3s first answer $0.07 $0.10 / $0.50 our rate 1.05M Closed

Free general-purpose model access, within fair use

Pick it when
You want a free starting point for everyday work in MindsHub Agents or through the API. Fair use and daily rate limits apply.
Skip it when
You are benchmarking, pinning a version, or otherwise need the numbers in this row to hold still. Name a model directly instead.
Inputs
TextImages
API alias
mindshub_air A rotating alias: we move it as better options ship, so the model behind it can change without a code change on your side.
Reasoning effort
Single setting — no dial. This route exposes no effort dial. The benchmark uses the source configuration and endpoint; your wait and cost can differ.
Worth knowing
The benchmark figures mirror the model this alias currently uses. Cost per task is measured at that provider’s rates, not a charge for Air within the free tier. The underlying model can change; pin a version when comparing results.
OpenAI gpt-luna-6 38 Solid 54.6% 135 tok/sec 105.3s first answer $0.07 $0.10 / $0.50 our rate 1.05M Closed

Focused text and image tasks at low token rates

Pick it when
You process many focused tasks and can test the results against clear acceptance criteria.
Skip it when
Your evaluation needs the stronger reasoning of Sol or Astra.
Inputs
TextImages
API alias
gpt-luna-6 gpt-luna The first names exactly this model and never moves. The second is the rotating alias for its line: it points here today and follows the line when we move it. Both reach the same model — see Rotating aliases.
Reasoning effort
nonelowmediumhighxhighmax We send medium unless you ask for another. Benchmark figures use the highest published source setting; this route supports up to max. Our default can differ from the benchmark in quality, cost and wait.
Worth knowing
Artificial Analysis reports 38 at $0.07 per benchmark task at max effort, versus 37 at $0.18 for GPT-5.6 Luna.
Anthropic sonnet-5 38 Solid 54.3% 75 tok/sec 202.7s first answer $5.09 $2 / $10 our rate 1M Closed

The previous Sonnet, for routine work already validated on it

Pick it when
You have routine drafting, summaries or small edits validated on Sonnet 5 and re-testing them on Sonnet 5.5 is not yet worth the interruption.
Skip it when
You are starting fresh — Claude Sonnet 5.5 scores eighteen points higher on the same token rates, and at high effort it still scores 47 for $0.88 a task against this row's $5.09.
Inputs
TextImages
API alias
sonnet-5 Names exactly this model version and never moves.
Reasoning effort
lowmediumhighmax We send high unless you ask for another. Benchmark figures use the highest published source setting; this route supports up to max. Our default can differ from the benchmark in quality, cost and wait.
Worth knowing
Twice as cheap as GPT 5.6 Sol per output token and about two and a half times the cost per finished task — a plain case of a rate card not predicting the bill. Streaming speed varies with reasoning effort: this row reports the top measured setting, while MindsHub defaults to high.
OpenAI gpt-codex-5-3 38 Solid — 84 tok/sec 69.3s first answer — $1.75 / $14 our rate 400K Closed

Coding specialist for repo-scale changes

Pick it when
The job is software, across many files, and you want a model tuned for that rather than for general reasoning.
Skip it when
The work is not code.
Inputs
TextImages
API alias
gpt-codex-5-3 gpt-codex The first names exactly this model and never moves. The second is the rotating alias for its line: it points here today and follows the line when we move it. Both reach the same model — see Rotating aliases.
Reasoning effort
lowmediumhighxhigh We send medium unless you ask for another. Benchmark figures use the highest published source setting; this route supports up to xhigh. Our default can differ from the benchmark in quality, cost and wait.
Worth knowing
Artificial Analysis scores this version only provisionally — on an older component set that omits both of the benchmarks they run on every fully scored row (Terminal-Bench v4.0 and GDPval-AA v2) — and publishes no cost per task for it, as they do for none of their provisional scores. Their figure is not on the same scale as the rest of this column, so both published columns here are ours.
OpenAI gpt-luna-5-6 37 Solid 53.6% 119 tok/sec 106.3s first answer $0.18 $0.20 / $1.20 our rate 1.05M Closed

The previous Luna, for high-volume work already validated on it

Pick it when
You run routine, high-volume work already validated on this version, and re-testing it on GPT-6 Luna is not yet worth the interruption.
Skip it when
You are starting fresh — GPT-6 Luna scores a point higher for $0.07 a task against $0.18, at lower token rates.
Inputs
TextImages
API alias
gpt-luna-5-6 Names exactly this model version and never moves.
Reasoning effort
nonelowmediumhighxhighmax We send medium unless you ask for another. Benchmark figures use the highest published source setting; this route supports up to max. Our default can differ from the benchmark in quality, cost and wait.
MindsHub via Cerebras mindshub_blaze 34 Solid 46.6% ≈1850 tok/sec — $1.01 $0.99 / $1.49 our rate 131K API only

A MindsHub model alias optimized for speed, served by Cerebras

Pick it when
You want fast generation for interactive work in MindsHub Agents or through the API.
Skip it when
You need to pin a model version or require verified first-answer latency for your workload.
Inputs
TextImages
API alias
mindshub_blaze A rotating alias: we move it as better options ship, so the model behind it can change without a code change on your side.
Reasoning effort
nonehigh We send high unless you ask for another. Benchmark figures use the highest published source setting; this route supports up to high. A lower setting may reduce cost and wait; test whether it still clears your tasks.
Served by
Cerebras We buy the inference from Cerebras, which is the name the rate card shows.
Speed source
Cerebras estimate. Provider-published approximate throughput, not a measured MindsHub median.
Worth knowing
We keep Blaze pointed at a model optimized for speed, so the model behind the alias can change. Quality, SciCode and task cost are reference benchmarks, not an independent Blaze evaluation or a forecast of your MindsHub bill. Their source settings may differ from this route. Speed is a Cerebras estimate; first-answer latency has not been verified. The context window shown is the serving route's limit (131,072 tokens on the paid Cerebras tier).
Meta muse-spark-1-1 34 Solid 58.8% — — $1.38 $1.25 / $4.25 our rate 1M Closed

Every input type, at an open-model rate

Pick it when
You need mixed-media input in an existing Muse Spark 1.1 workflow.
Skip it when
You can use a newer Muse: 1.2 scores six points higher here at a lower measured task cost.
Inputs
TextImagesAudioVideo
API alias
muse-spark-1-1 Names exactly this model version and never moves.
Reasoning effort
Single setting — no dial. This route exposes no effort dial. The benchmark uses the source configuration and endpoint; your wait and cost can differ.
Google gemini-flash-3-6 34 Solid 53.4% 184 tok/sec 14.3s first answer $1.60 $0.75 / $3.75 our rate 1M Closed

Fast, high-volume everyday tasks

Pick it when
You already run on Gemini 3.6 Flash and want to keep its alias while you evaluate a newer Flash.
Skip it when
3.7 Flash scores five index points better, is stronger at code, and finishes a benchmark task for $0.93 against $1.60 on the same token rates.
Inputs
TextImagesAudioVideo
API alias
gemini-flash-3-6 Names exactly this model version and never moves.
Reasoning effort
minimallowmediumhigh We send medium unless you ask for another. Benchmark figures use the highest published source setting; this route supports up to high. Our default can differ from the benchmark in quality, cost and wait.
Google gemini-flash-3-5 33 Light 53.9% 195 tok/sec 17.4s first answer $3.69 $1.50 / $9 our rate 1M Closed

The legacy Google Flash, for workloads already built on it

Pick it when
You already run on Gemini 3.5 Flash and want the same model behind the same alias while you evaluate a newer Flash.
Skip it when
You are starting fresh: Google itself files this as its legacy Flash, and the newer Flash generations here score higher at a lower rate card.
Inputs
TextImagesAudioVideo
API alias
gemini-flash-3-5 Names exactly this model version and never moves.
Reasoning effort
minimallowmediumhigh We send medium unless you ask for another. Benchmark figures use the highest published source setting; this route supports up to high. Our default can differ from the benchmark in quality, cost and wait.
Worth knowing
Figures are at high, the top of its dial. Artificial Analysis scores its medium and minimal runs only provisionally on the current index and publishes no cost per task for them, so high is the one comparable reading and the one this row quotes.
Google gemini-3-1-pro 30 Light 58.7% 113 tok/sec 25.9s first answer $1.30 $2 / $12 our rate 1M Closed

Huge documents, images, audio and video

Pick it when
A single request has to carry a whole corpus of mixed media, and it has to be reasoned over rather than skimmed.
Skip it when
You are paying by the token — the Flash line reads the same inputs at a third of the rate card, and 3.7 Flash outscores this by nine points.
Inputs
TextImagesAudioVideo
API alias
gemini-3-1-pro gemini The first names exactly this model and never moves. The second is the rotating alias for its line: it points here today and follows the line when we move it. Both reach the same model — see Rotating aliases.
Reasoning effort
lowmediumhigh We send high unless you ask for another. Benchmark figures use the highest published source setting; this route supports up to high. A lower setting may reduce cost and wait; test whether it still clears your tasks.
Google gemini-flash-3 26 Light — 192 tok/sec 6.8s first answer — $0.50 / $3 our rate 1M Closed

Preview-era Flash, kept so early integrations keep running

Pick it when
A workload already built on the Gemini 3 preview that you are not ready to move, and want to keep calling by its own alias.
Skip it when
Anything new: it is a preview from December 2025, and each Flash release since scores higher here.
Inputs
TextImagesAudioVideo
API alias
gemini-flash-3 Names exactly this model version and never moves.
Reasoning effort
minimallowmediumhigh We send high unless you ask for another. Benchmark figures use the highest published source setting; this route supports up to high. A lower setting may reduce cost and wait; test whether it still clears your tasks.
Worth knowing
Artificial Analysis lists it in reasoning and non-reasoning configurations and publishes no cost per task for either — on their table, the mark of a score not yet on the current component set — so quality remains marked as provisional and cost per task stays blank. Through MindsHub it exposes a minimal-to-high dial.
OpenAI gpt-mini-5-4 24 Light 52.1% 271 tok/sec 101.8s first answer $0.45 $0.75 / $4.50 our rate 400K Closed

Small and cheap for routine automation

Pick it when
Classification, extraction, tagging and other high-frequency jobs with a narrow definition of correct.
Skip it when
Luna passes the same tasks: its index is higher here, with a lower measured task cost. Compare both on your workload.
Inputs
TextImages
API alias
gpt-mini-5-4 gpt-mini The first names exactly this model and never moves. The second is the rotating alias for its line: it points here today and follows the line when we move it. Both reach the same model — see Rotating aliases.
Reasoning effort
nonelowmediumhighxhigh We send none unless you ask for another — the lowest setting this route exposes. Benchmark figures use the highest published source setting; this route supports up to xhigh. Our default can differ from the benchmark in quality, cost and wait.
OpenAI gpt-nano-5-4 21 Basic 47.2% 164 tok/sec 74.8s first answer $0.18 $0.20 / $1.25 our rate 400K Closed

Built for throughput on bulk, simple work

Pick it when
Millions of tiny calls where throughput matters and the task fits in one sentence.
Skip it when
Any judgement is required.
Inputs
TextImages
API alias
gpt-nano-5-4 gpt-nano The first names exactly this model and never moves. The second is the rotating alias for its line: it points here today and follows the line when we move it. Both reach the same model — see Rotating aliases.
Reasoning effort
nonelowmediumhighxhigh We send none unless you ask for another — the lowest setting this route exposes. Benchmark figures use the highest published source setting; this route supports up to xhigh. Our default can differ from the benchmark in quality, cost and wait.
Anthropic haiku-4-5 17 Basic 42.2% 97 tok/sec 15.2s first answer $0.28 $1 / $5 our rate 200K Closed

The smallest Claude, for high-volume simple work

Pick it when
You want Claude behaviour and Claude tooling on work that does not need Claude-sized thinking.
Skip it when
The job needs reasoning headroom — this is the previous generation, and it shows on hard tasks.
Inputs
TextImages
API alias
haiku-4-5 haiku The first names exactly this model and never moves. The second is the rotating alias for its line: it points here today and follows the line when we move it. Both reach the same model — see Rotating aliases.
Reasoning effort
Single setting — no dial. This route exposes no effort dial. The benchmark uses the source configuration and endpoint; your wait and cost can differ.
Google gemini-flash-lite-3-1 16 Basic 43.4% 265 tok/sec 5.8s first answer $0.06 $0.25 / $1.50 our rate 1M Closed

Lite-tier extraction and classification at scale

Pick it when
High-volume, simple work — extraction, classification, routing, transcription — where per-call cost and latency matter more than depth.
Skip it when
Multi-step reasoning or coding — the Flash and Pro lines exist for that.
Inputs
TextImagesAudioVideo
API alias
gemini-flash-lite-3-1 gemini-flash-lite The first names exactly this model and never moves. The second is the rotating alias for its line: it points here today and follows the line when we move it. Both reach the same model — see Rotating aliases.
Reasoning effort
minimallowmediumhigh We send minimal unless you ask for another — the lowest setting this route exposes. Benchmark figures use the highest published source setting; this route supports up to high. Our default can differ from the benchmark in quality, cost and wait.
OpenAI via Fireworks AI Fallback model gpt-oss-fireworks 12 Basic 34.0% 185 tok/sec 12.8s first answer $0.11 $0.15 / $0.60 our rate 131K Open Apache 2.0

Open weights for focused text tasks

Pick it when
You need downloadable weights or a low-cost text model and can validate the result on your own tasks.
Skip it when
You need image input or frontier-level general reasoning.
Inputs
Text
API alias
gpt-oss-fireworks Names exactly this model version and never moves.
Reasoning effort
Single setting — no dial. This route exposes no effort dial. The benchmark uses the source configuration and endpoint; your wait and cost can differ.
Licence
Apache 2.0
Served by
Fireworks AI OpenAI makes it. We buy the inference from Fireworks AI, which is the name the rate card shows.
Worth knowing
Benchmark figures describe Artificial Analysis’s gpt-oss-120b high-effort configuration and source endpoints, not a measurement of MindsHub’s Fireworks route. The catalog exposes no effort dial for this route.
Quality & Cost/task
Artificial Analysis's published figures, on Intelligence Index v4.3.2 — they measure independently of us — at each model's highest published reasoning effort, or its sole reasoning row. These are reference settings, not a maximum bill or a guarantee of results. Expand a row for the level we send.
Coding, Speed & Latency
Artificial Analysis: SciCode %, median output tokens/sec, and time to first answer including reasoning. These measure source endpoints. Expand a row for provider estimates; missing measurements show —.
Price
Per 1M tokens, in / out. Everything else about the bill — prompt-cache rates, long-prompt tiers and search — is on the full rate card.
Missing figures
≈ marks a reference value or estimate; expand the row for its source. — means no comparable measurement is available here for that column or configuration.
MindsHub Air
Air has no reasoning dial. Air's board row mirrors the model it points at and may briefly lag an alias change.
Checked
All benchmark columns and source rates against Artificial Analysis on . Last automated API refresh: . Our rates are live from the catalog.
Rotating aliases

One alias per line, pointed at the model we serve for it.

A rotating alias such as gpt always resolves to the most recent version of that line we serve, so it can move without a code change on your side. Versioned model lines also have a fixed alias that names one exact version. The branded MindsHub Air and MindsHub Blaze aliases have no fixed counterpart.

Rotating alias Currently serves Fixed alias Older versions still served
mindshub_air Whichever model balances cost, speed and intelligence best — see its board row. — —
mindshub_blaze A model optimized for speed — see its board row. — —
sonnet Claude Sonnet 5.5 sonnet-5-5 Claude Sonnet 5
opus Claude Opus 5.5 opus-5-5 Claude Opus 5
fable Claude Fable 5.1 fable-5-1 Claude Fable 5
haiku Claude Haiku 4.5 haiku-4-5 —
gpt GPT-6 Astra gpt-6-astra GPT 5.6 Sol
gpt-sol GPT-6.1 Sol gpt-sol-6-1 GPT-6 Sol
gpt-terra GPT 5.6 Terra gpt-terra-5-6 —
gpt-luna GPT-6 Luna gpt-luna-6 GPT 5.6 Luna
gpt-codex GPT 5.3 Codex gpt-codex-5-3 —
gpt-mini GPT 5.4 Mini gpt-mini-5-4 —
gpt-nano GPT 5.4 Nano gpt-nano-5-4 —
gemini Gemini 3.1 Pro Preview gemini-3-1-pro —
gemini-flash Gemini 3.8 Flash gemini-flash-3-8 Gemini 3.7 Flash , Gemini 3.6 Flash , Gemini 3.5 Flash , Gemini 3 Flash Preview
gemini-flash-lite Gemini 3.1 Flash-Lite gemini-flash-lite-3-1 —
kimi Kimi K3 kimi-k3 —
deepseek-v4-flash DeepSeek V4.1 Flash deepseek-v4-1-flash —
qwen Qwen3.8-2.4T-A95B qwen-3-8-a95b —
glm GLM 5.3 glm-5-3 —
glm-5-3-flash GLM 5.3 Flash glm-flash-5-3 —
muse-spark Muse Spark 1.3 muse-spark-1-3 Muse Spark 1.2 , Muse Spark 1.1
grok Grok 4.7 grok-4-7 Grok 4.6 , Grok 4.5
01 · Quality

Small score differences are ties.

Treat scores within 3 points of each other as ties. For models in that range, speed and cost can help you choose.

A benchmark averages many tasks and can hide weaknesses that matter to you. Use the scores to shortlist two or three models, then test them on your own work. The method below shows how.

Each score is for a model at a specific reasoning setting, usually the top one. Compare it with a lower setting on your own tasks: extra reasoning can change quality, cost and wait. These figures do not predict the bill or success rate of an individual request.

Quality index from Artificial Analysis for the full board.
  1. Claude Opus 5.5 58
  2. Claude Sonnet 5.5 56
  3. GPT-6 Astra 53
  4. Claude Fable 5.1 53
  5. GPT-6.1 Sol 52
  6. Claude Opus 5 51
  7. Claude Fable 5 50
  8. GPT-6 Sol 48
  9. Muse Spark 1.3 48
  10. GPT 5.6 Sol 47
  11. Grok 4.7 46
  12. GLM 5.3 45
  13. Grok 4.6 44
  14. Kimi K3 44
  15. GLM 5.3 Flash 42
  16. GPT 5.6 Terra 42
  17. Gemini 3.8 Flash 41
  18. Muse Spark 1.2 40
  19. Qwen3.8-2.4T-A95B 40
  20. DeepSeek V4.1 Flash 39
  21. Grok 4.5 39
  22. Gemini 3.7 Flash 39
  23. MindsHub Air ≈38
  24. GPT-6 Luna 38
  25. Claude Sonnet 5 38
  26. GPT 5.3 Codex ≈38
  27. GPT 5.6 Luna 37
  28. MindsHub Blaze ≈34
  29. Muse Spark 1.1 34
  30. Gemini 3.6 Flash 34
  31. Gemini 3.5 Flash 33
  32. Gemini 3.1 Pro Preview 30
  33. Gemini 3 Flash Preview ≈26
  34. GPT 5.4 Mini 24
  35. GPT 5.4 Nano 21
  36. Claude Haiku 4.5 17
  37. Gemini 3.1 Flash-Lite 16
  38. GPT-OSS 120B (Fireworks) 12

Bars run from zero and are relative to the leader — a truncated axis would manufacture a gap that isn't there. Scores within 3 points of each other are a tie.

02 · Performance

Measure the wait and the streaming speed.

Latency is the wait for the first answer token, including thinking time. Throughput is how quickly the rest arrives. The chart shows both because a model can be strong on one and weak on the other.

From the request to a finished answer. Pale is the wait before the first answer token; solid estimates the time to stream the answer. Both inputs are Artificial Analysis medians at the source configuration. Adding them estimates completion time; it is not a timed run of one shared request or a measurement of MindsHub's endpoints. Answer length changes both the stakes and the order. A 200-token reply is estimated at between 6.6s and 694.8s; at 4,000 tokens the estimate runs 21s to 736s, with 27 of 36 rows changing places.
  1. Gemini 3.1 Flash-Lite 9.6s
  2. Gemini 3 Flash Preview 12.0s
  3. DeepSeek V4.1 Flash 15.1s
  4. Gemini 3.7 Flash 15.3s
  5. Muse Spark 1.2 18.0s
  6. GPT-OSS 120B (Fireworks) 18.2s
  7. Gemini 3.6 Flash 19.7s
  8. Gemini 3.5 Flash 22.5s
  9. Claude Haiku 4.5 25.5s
  10. Gemini 3.1 Pro Preview 34.7s
  11. Gemini 3.8 Flash 35.4s
  12. Grok 4.5 37.3s
  13. GLM 5.3 42.9s
  14. GLM 5.3 Flash 60.6s
  15. Grok 4.6 61.3s
  16. Claude Opus 5 73.6s
  17. Kimi K3 76.4s
  18. Qwen3.8-2.4T-A95B 79.9s
  19. Muse Spark 1.3 80.8s
  20. GPT 5.4 Nano 80.8s
  21. GPT 5.3 Codex 81.3s
  22. Grok 4.7 85.9s
  23. GPT 5.4 Mini 105.5s
  24. GPT 5.6 Sol 111.5s
  25. MindsHub Air 112.7s
  26. GPT-6 Luna 112.7s
  27. GPT 5.6 Luna 114.7s
  28. GPT 5.6 Terra 121.4s
  29. Claude Fable 5 122.9s
  30. GPT-6 Sol 144.2s
  31. Claude Sonnet 5 216.0s
  32. Claude Fable 5.1 300.5s
  33. GPT-6.1 Sol 331.7s
  34. GPT-6 Astra 431.4s
  35. Claude Sonnet 5.5 445.7s
  36. Claude Opus 5.5 703.4s

Wait for the first answer token Streaming the answer

A 73-fold spread in completion time

The estimate for Gemini 3.1 Flash-Lite is about 10 seconds and Claude Opus 5.5 is about 703. Both use the same answer length, but different model configurations. Top-effort reasoning can account for much of that wait.

Short answers make latency more important

On a 200-token reply the wait is 81% to 100% of the wall clock, so latency is worth weighting. A longer answer gives streaming speed more weight, but a large reasoning budget can still dominate the wait. The control above the chart switches between the two views.

Measure with your own traffic

Region, prompt length, cache hit rate and reasoning effort all move these figures. Use them to rank candidates, then measure the two you shortlist against your own traffic.

03 · Cost

Price per token is not cost per task.

Token prices do not show how many tokens a model will use to finish the job. Reasoning models can vary widely on that second number.

You pay for reasoning tokens as well as the visible answer. A model with a lower token rate can still cost more per completed task.

It is somebody else's task, at each model's top effort, priced at the provider's own rate — so treat it as a way to rank candidates, not a forecast of your bill.

How much of the discount survives the invoice. Each model against GPT 5.6 Sol: what its published output rate promises, then what its measured cost per task delivers — both at top effort. These 5 keep the least.
  • Grok 4.7 3.3× cheaper on paper 1.9× dearer per task
  • Claude Sonnet 5.5 2.0× cheaper on paper 2.7× dearer per task
  • Claude Sonnet 5 2.0× cheaper on paper 2.6× dearer per task
  • GLM 5.3 Flash 40.0× cheaper on paper 8.0× cheaper per task
  • GLM 5.3 4.5× cheaper on paper 1.0× dearer per task

Both figures come from the same rate card — each provider's own published price, which is what these tasks were costed at, and not always the rate in the Price column above. GPT 5.6 Sol's output rate is a promotional rate OpenAI lists through at least November 21, 2026. And the lesson is not that cheap models are a lie: Gemini 3.1 Flash-Lite beats its own rate card — 13.3× cheaper on paper, 33.2× cheaper per task. It is that you cannot rank them by reading price pages.

04 · Method

Choose a model in an afternoon.

Use the board for a shortlist, then test it against real examples.

  1. Shortlist two or three from the board

    Use the task router above, or filter the board to your constraint — open weights, a modality, a latency ceiling. Stop at three.

  2. Collect ten real tasks

    With the messy context attached. Not clean samples: the actual ones you ran last week, including the awkward ones.

  3. Run them at the effort you would really use

    Not maximum. The reasoning dial moves cost further than switching models does, and every published cost-per-task figure is measured at the top setting.

  4. Read the token counts off the response

    Every provider returns a usage object. Multiply input, cached input and output separately — those three rates can differ by an order of magnitude.

  5. Divide by the results you would actually ship

    If eight of ten came back usable, your real cost is the total divided by eight. That division is the one no leaderboard can do for you.

One API key reaches every model here, so a bake-off is a string change rather than three integrations. There's a runnable version, a cost measurement guide, a guide to running evals, and a free working session if you'd rather do it with an engineer.

FAQ

Questions about the rankings.

Which model should I use?
Use the task recommendations on the board. Current picks include GPT-6.1 Sol or Claude Opus 5.5 for agentic coding, Claude Opus 5.5 for hard reasoning, DeepSeek V4.1 Flash or Gemini 3.7 Flash for interactive work, and GLM-5.3 or Kimi K3 when you need open weights. Start with MindsHub Air if you do not yet have a strong preference.
Which models does this page cover?
Every model currently in the MindsHub catalog, and only those models, one row per model. Each row includes the alias that calls it: the fixed alias for that exact version, or the branded alias for MindsHub Air and MindsHub Blaze.
What is a rotating alias?
A rotating alias such as gpt or sonnet always resolves to the most recent version of that line MindsHub serves, so it can change without a code change on your side. Versioned model lines also have a fixed alias that names one exact version. Branded aliases such as MindsHub Air and MindsHub Blaze have no fixed counterpart. The rotating aliases table on the board maps each rotating alias to the model it serves today and to that fixed alias.
Why rank on cost per task instead of price per token?
Models use different numbers of tokens and reasoning steps to finish the same task. Cost per task captures that difference. Use it to compare candidates, not as a forecast of your own bill.
Where do these benchmark numbers come from?
Quality and task cost come from Artificial Analysis at each model's highest reasoning setting. A “≈” marks a reference value or estimate. Coding is the published SciCode percentage. Latency is the median wait for the first answer token, including reasoning; speed is median output throughput except for provider estimates explained in expanded rows, as on MindsHub Blaze. These source-endpoint measurements do not measure MindsHub latency, and prices come from the live MindsHub catalog.
At what reasoning effort were these numbers measured?
Artificial Analysis figures use each model's highest setting. MindsHub often sends a lower default, shown when you expand a row, so actual cost may be lower. MindsHub does not publish its own per-setting scores.
Does this page replace the pricing page?
No. The board shows input and output token prices for comparison. Use the pricing page for cache rates, long-prompt tiers, web search, failover order, and billing details.