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ModelCap

Mistral Large 4

Arena #115NewNo linked weights

Mistral AI·#62 of 344 on the current board·cheaper than #60 Kimi K2 Thinking

Mistral Large 4 is a language model from Mistral AI. It ranks #62 of 344 on ModelCap's current board, with an Index score of 63.1, measured on 3 public benchmarks. Its score range of 57.3–68.9 spans positions #42–#89. It is listed at $0.68 per million input tokens and $2.09 per million output tokens from one provider. It reads up to 1M tokens of context, with no downloadable weights linked in the current source data.

Figures as of 11 Oct 2026, 15:20 UTC · download the public dataset · methodology

ModelCap Index · Current board
63.1#62
Measured on 3 public benchmarks · range 57.3–68.9
Evidence as of 8 Oct 2026, 00:00 UTC
Market Gravity
34.2Increased by 0.4
Secondary market signal
Input
$0.68
per 1M tokens
Output
$2.09
per 1M tokens
Context
1M
tokens
Providers
1
3 endpoints

Providers

Uptime measured over the last 30 minutes
ProviderInputOutputContextQuantUptime
MistralzdrCheapest$0.68$2.091M—100.0%
Mistral$0.68$2.091M—100.0%
Mistraleu$0.748$2.30524K——

Reasoning efforts

Best supported result can inform ModelCap

Published Max, X-High, High and other configurations for this model. These are sourced scores, not head-to-head essays.

EffortAgent scoreSource rankSampleSource
Default
mistral-large-4
-6.56%
CI -9.5–-3.6%
#43272K obs
5K sessions
LMArena Agent
Match 100%

Other versions (3)

ModelCap Index · Current board

Methodology
63.1
Measured on 3 public benchmarks
Current board
#62 of 344
Score range
57.3–68.9
Rank range
#42–#89
Evidence as of
8 Oct 2026, 00:00 UTC
Benchmarks used
Arena Coding, Arena Overall, LMArena Agent
Technical details
Public rank basis
Measured (measured)
Evidence label
Measured · 3 public benchmark observations across 3 boards
Index support
52.9% · moderate
Identity binding
Exact catalogue product · mistralai/mistralai/mistral-large-4-0 · aggregates disclosed benchmark configurations · endpoint configuration not claimed
Index observations used
3
Qualified Index evidence point
63.1
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
63.1
Evidence status
confirmed · 84% mass
General preference
63.8
Coding
68.0
Agents & tools
27.2
Reasoning
—
Evidence breadth
97%
Evidence coverage
53%
Market and catalogue signals · secondary, never the language Index rank
Usage (OpenRouter popularity)
23.5
Liquidity (providers × uptime)
35.5
Open reach (HF downloads)
—
Surface (context / tools / modalities)
100.0
Freshness
98.1
  • · OpenRouter popularity #85
  • · 1 live provider
  • · Catalogue: context 1048576, reasoning, tools, modalities Text/Image
  • · First seen 2026-10-06

These adoption and deployment observations remain context only. They do not change this model's ModelCap Index score or rank.

BES evidence selected · measured input only

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.

Deployment readiness

Metadata index
44.5
limited · 56% metadata coverage
Not capability
Artifact reproducibility
0.0
Access & legal clarity
30.3
Deployability
80.0
Evaluation provenance
72.3

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, pinned evaluation dataset versions.

A metadata completeness and deployability index—not a safety certification, quality grade, or production-readiness claim.

Market activity

Venue coverage
Market Gravity
34.2
OpenRouter weekly popularity
#85 of 332

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

Status
Ranked
Source
LMArena
Official rank
#115 of 414
Rating
1429.3
95% confidence interval
1420–1439
Votes
4K
Source published at
8 Oct 2026, 00:00 UTC
Category
overall
Identity match confidence
100%

Market Gravity breakdown

Usage55%
23.5

OpenRouter weekly popularity across the full model catalogue.

Liquidity25%
35.5

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%
98.1

Time since first public availability, on a six-month half-life.

Specification

Model ID
mistralai/mistral-large-4-0
Context window
1M tokens
Declared output cap
262K 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, Image
Outputs
Text
Tokenizer
Mistral
Cached input tokens
$0.07 / 1M
First seen on OpenRouter
6 Oct 2026

Capabilities

  • Supported: Reasoning
  • Supported: Tool use
  • Supported: Structured output
  • Supported: Response format
  • Not supported: Moderated

Compare Mistral Large 4 with

Pick any model

Benchmark leaderboards featuring Mistral Large 4

All leaderboards
Public benchmark boards on which Mistral Large 4 has a published result
LeaderboardScoreSource rankConfigurationPublished
Arena text leaderboardArena (LMArena)14291420–1439#115 of 414Not reported8 Oct 2026
Arena coding leaderboardArena (LMArena)14921473–1512#87 of 409Default8 Oct 2026
LMArena Agent leaderboardLMArena-6.6%-9.5%–-3.6%#43 of 52Default8 Oct 2026

Alternatives to Mistral Large 4, by the numbers

Ranked neighbours

Models within 3 places of #62 on the ModelCap Index.

Cheaper at a similar or higher Index

Index score within 3 points of, or above, this model's, with a lower listed blended price (3:1 input:output).

Other ranked Mistral AI models

The same publisher's other current models with a public Index position.

Mistral Large 4: common questions

How does Mistral Large 4 rank among AI models?

Mistral Large 4 holds ModelCap Index position #62 of 344 ranked language models as of 11 October 2026, with an Index score of 63.1 (interval 57.3–68.9); evidence: measured. The Index combines public benchmark boards with published uncertainty; the methodology page explains the weighting.

How much does Mistral Large 4 cost per 1M tokens?

Mistral Large 4 is listed at $0.68 per 1M input tokens and $2.09 per 1M output tokens as of 11 October 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 $2.40 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 4?

Mistral Large 4 has a published context window of 1M tokens (1,048,576). The snapshot lists a 262,144 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 4 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 4?

One provider serves Mistral Large 4 through OpenRouter as of 11 October 2026: Mistral. Each provider's price, context limit, quantization and measured uptime are in the providers table above.

Which benchmarks has Mistral Large 4 been evaluated on?

Mistral Large 4 has published results on 3 public boards tracked by ModelCap as of 11 October 2026: Arena text 1429 (#115 of 414), Arena coding 1492 (#87 of 409) and LMArena Agent -6.6% (#43 of 52). Each board page ranks every tracked model on that benchmark. The ModelCap Index scores the results its methodology admits, with published uncertainty, and shows reference boards without scoring them.

How does Mistral Large 4 compare with Mistral Medium 3.5?

Mistral Large 4 ranks #62 (Index 63.1) and Mistral Medium 3.5 ranks #73 (Index 60.8) on the ModelCap Index as of 11 October 2026. The head-to-head page lines up their benchmarks, listed prices, context windows and provider counts side by side.

When was Mistral Large 4 released?

Mistral Large 4 first appeared in the catalogue on 6 Oct 2026. It is the current version in its family. Rank and price movements since then are recorded on the site's changes feed.