Mistral AI·#368 of 504 in the all-versions archive
Mistral Large 2407 is a language model from Mistral AI. It ranks #368 of 504 in ModelCap's all-versions archive, with an Index score of 27.9, modeled from its measured predecessor. Its score range of 14.2–41.6 spans positions #252–#435. It is listed at $2.00 per million input tokens and $6.00 per million output tokens from one provider. It reads up to 131K tokens of context, with no downloadable weights linked in the current source data.
Modeled · succession · publisher-corpus-prior over 210 held-out anchors (20%); opens from measured predecessor mistralai/mistral-large (80%); shrunk 2.7 up toward the measured corpus
How this position was produced · fused launch placement
No general-family board lists this model yet. Its point estimate is the precision-weighted mean of every channel that spoke for it; each channel’s share is the weight it carried. Independent measurements replace this placement as boards list the model.
Fused estimate
27.9 ± 10.7
Independent share
0%
Shrink toward corpus
+2.7
Optimism haircut
None applied
Method
precision-weighted-v1
Channels fused into this model’s launch placement
Channel
Estimate
Share
Publisher corpus prior · not independent
publisher-corpus-prior over 210 held-out anchors
38.5 ± 23.8
20%
Family succession · not independent
opens from measured predecessor mistralai/mistral-large
25.2 ± 12.0
80%
Bayesian Evidence Score · measured evidence input only
BES normalizes admitted public benchmark evidence for measured Index rows. Its legacy score and observables prior do not define the public language rank.
Observed capability
—
Evidence status
No admitted measured evidence
General preference
—
Coding
—
Agents & tools
—
Reasoning
—
Evidence breadth
0%
Evidence coverage
0%
Market and catalogue signals · secondary, never the language Index rank
These adoption and deployment observations remain context only. They do not change this model's ModelCap Index score or rank.
The bounded 0–100 capability score blends each source’s competitive placement with its published achievement, then combines capability families. Evidence breadth adds a modest uncertainty adjustment; price and popularity are not part of benchmark-led rank.
Not yet published: a pinned repository revision, the architecture and model type, a parameter count, safetensors weight metadata, the base model it derives from, a declared licence, a link to the licence terms, admitted benchmark results, results across several capability areas, results from more than one source, a confident match to its benchmark entries, pinned evaluation dataset versions.
A metadata completeness and deployability index—not a safety certification, quality grade, or production-readiness claim.
Market Gravity uses OpenRouter’s full-catalogue popularity order. Sparse Vercel top-ten observations appear only when published and do not affect the score.
Arena preference
No matched Arena rating
This model is visible because it is available in the live catalogue, but it has no trustworthy community result yet. ModelCap does not infer a quality score from price, features, or market activity.
Market Gravity breakdown
Usage55%
2.9
OpenRouter weekly popularity across the full model catalogue.
Liquidity25%
95.8
Independent providers versus the model's open or closed cohort, weighted by uptime.
Open reach15%
50.0
Hugging Face 30-day downloads for open models; neutral for closed models.
Freshness5%
6.5
Time since first public availability, on a six-month half-life.
Specification
Model ID
mistralai/mistral-large-2407
Context window
131K tokens
Declared output cap
105K tokens
OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. OpenRouter metadata
Inputs
Text, File
Outputs
Text
Tokenizer
Mistral
Cached input tokens
$0.20 / 1M
First seen on OpenRouter
19 Nov 2024
Knowledge cutoff
2024-03-31
Capabilities
Not supported: Reasoning
Supported: Tool use
Supported: Structured output
Supported: Response format
Not supported: Moderated
Mistral Large 2407: common questions
How does Mistral Large 2407 rank among AI models?
Mistral Large 2407 is a superseded version and is not on the current board as of 6 November 2026. Its archive position, where one exists, is shown on the page; the newer version carries the current rank.
How much does Mistral Large 2407 cost per 1M tokens?
Mistral Large 2407 is listed at $2.00 per 1M input tokens and $6.00 per 1M output tokens as of 6 November 2026. Prices come from the OpenRouter catalogue and re-observe on every refresh. For 1,000 requests using 2,000 input and 500 output tokens each, the listed rates imply $7.00 total (2M input + 0.5M output). This excludes caching, batch discounts, prompt-length tiers, tool charges and retries; verify the chosen endpoint's rate and limits before budgeting.
What is the context window of Mistral Large 2407?
Mistral Large 2407 has a published context window of 131K tokens (131,072). The snapshot lists a 104,857 token catalogue-declared route output cap. OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. The providers table lists each endpoint's context limit.
Is Mistral Large 2407 open-weight?
No linked weights. No downloadable model weights are linked in the current source data. This does not identify every API or chat product that offers the model.
Which API providers serve Mistral Large 2407?
One provider serves Mistral Large 2407 through OpenRouter as of 6 November 2026: Mistral. Each provider's price, context limit, quantization and measured uptime are in the providers table above.
When was Mistral Large 2407 released?
Mistral Large 2407 first appeared in the catalogue on 19 Nov 2024, with a published knowledge cutoff of 2024-03-31. It has since been superseded by Mistral Large 4. Rank and price movements since then are recorded on the site's changes feed.