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Mistral Large 4

Multimodal
Mistral AI

Mistral Large 4 (public preview, also called ML4 or "le Chonk") is Mistral AI's flagship general-purpose multimodal mixture-of-experts model. Mistral's docs describe it as 1.05T total parameters with 52B active parameters and a 1.6B vision encoder, while the Hugging Face upcoming-release page describes a 1T model with 49B active parameters per token. It supports a 1M-token context window with text and image input and text output, plus structured outputs, function calling, document QnA, batching, agents and conversations, and built-in tools. Launch API pricing is 50% off for two weeks: $0.68/$0.07/$2.09 per million input/cached/output tokens versus $1.36/$0.14/$4.18 list. Weights are planned for the end of October 2026, so the model is stored as proprietary until a public weights license is published. Catalog scores are self-reported from the Mistral launch announcement.

Key Specifications

Parameters
1.1T
Context
1.0M
Release Date
October 6, 2026
Average Score
60.4%

Timeline

Key dates in the model's history
Announcement
October 6, 2026
Last Update
October 8, 2026
Today
October 12, 2026

Technical Specifications

Parameters
1.1T
Training Tokens
-
Knowledge Cutoff
-
Family
-
Capabilities
MultimodalZeroEval

Pricing & Availability

Input (per 1M tokens)
$0.68
Output (per 1M tokens)
$2.09
Max Input Tokens
1.0M
Max Output Tokens
-
Supported Features
Function CallingStructured OutputCode ExecutionWeb SearchBatch InferenceFine-tuning

Benchmark Results

Model performance metrics across various tests and benchmarks

Other Tests

Specialized benchmarks
AA-Briefcase
Elo 1,393 from announcement prose only (no separate briefcase chart); max_score 3000. • Self-reported
46.4%
AutomationBench
Announcement prose + chart 59.9% on AutomationBench (657 business workflows). • Self-reported
59.9%
B3 AI Security Benchmark
Attack resistance; announcement cites Lakera's public benchmark for indirect prompt-injection robustness. • Self-reported
93.3%
ChartQAPro
Chart ChartQA Pro 63.1%. • Self-reported
63.1%
Coding Agent Index
Combined Coding Agent Index; announcement prose 49.8%. • Self-reported
49.8%
CyBench
Announcement prose 93% (chart 93). • Self-reported
93.0%
CyberGym
Announcement prose 82% vulnerability reproduce+patch; chart CyberGym-E2E (AA) 82. • Self-reported
82.0%
DeepSWE 1.1
Announcement prose 61.7% (chart ~62). Artificial Analysis private pre-harness launch footnote on chart. • Self-reported
61.7%
Dense200
Dense200 bbox; announcement prose 42% (chart 42.0 vs GPT-6 Astra 41.5). • Self-reported
42.0%
Finance Agent v2
Chart Vals.ai Finance Agent v2: 54.7%. • Self-reported
54.7%
Finch (FinWorkBench)
Chart Finch (FinWorkBench) 67.4%. • Self-reported
67.4%
GDP.pdf
Chart "GDP.pdf - AA" 18.6%. Artificial Analysis labeling; not OpenAI's different gdp.pdf figures. • Self-reported
18.6%
Harvey's Legal Agent Benchmark
Chart "Vals.ai Harvey LAB" 15.8% (Astra 5.4). Stored as 0.158 all-pass rate to match sibling cards (max_score 1.0). • Self-reported
15.8%
KORABench
Overall score; announcement notes that 2.0 is the maximum and denotes "Exemplary". • Self-reported
84.5%
SciCode
SciCode-Verified pass@1 n=6; chart 91.8%. No scicode-verified catalog id; stored under scicode. • Self-reported
91.8%
Surge AI Coding Quality
Blind human evaluation on coding quality; professional annotators rated outputs on a 1-5 scale with model identities hidden. • Self-reported
74.8%
SWE Atlas - Codebase QnA
SWE-Atlas-QnA; announcement prose 59.4% (chart ~59). • Self-reported
59.4%
Terminal-Bench 4.0
Announcement prose 28.3% (chart ~28). Chart footer: AA Coding Agent Index harness. • Self-reported
28.3%

License & Metadata

License
proprietary
Announcement Date
October 6, 2026
Last Updated
October 8, 2026

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