Mistral · Released Oct 6, 2026

Mistral Large 4

Mistral Large 4 is a frontier multimodal (text and image input) model from Mistral AI built for reasoning, coding, and agentic workloads. It offers a 1M-token context window with up...

ReasoningVision
  • Top 23%OTIS Mock AIME
  • Top 34%SciCode
  • Top 50%CritPt
Released
Oct 6 2026
Context window
1M 262K out
Input / 1M tokens
$0.68
Output / 1M tokens
$2.09

Where to run it

Providers

Cheapest: Mistral at $0.68 / $2.09 per 1M input / output tokens — 9% less than the priciest option.

ProviderInputOutputCache readContextMax outputUptimevs. best
Mistralzdr $0.68 $2.09 $0.071M262K100%24h Cheapest
Mistral $0.68 $2.09 $0.071M262K100%24h Cheapest
Mistraleu $0.75 $2.30 $0.077524K262K96.4%24h +10%

Value

Price vs. performance

16 models score higher for the same price or lesson GPQA Diamond, e.g. Kimi K3.
25.3%49.0%72.7%96.4% $0.01$0.10$1.00$10.00$100.00 DeepSeek V4.1 Flash 1017 (DeepSeek) — 89.8% · $0.30/1M in Gemini 4 Argon (Google) — 96.4% · $2.00/1M in Claude Haiku 5.5 (Anthropic) — 89.6% · $0.10/1M in GPT-6.1 Sol (OpenAI) — 95.4% · $2.00/1M in Claude Sonnet 5.5 (Anthropic) — 95.6% · $2.00/1M in GPT-6 Luna (OpenAI) — 90.5% · $0.10/1M in GPT-6 Sol (OpenAI) — 94.3% · $2.00/1M in Claude Opus 5.5 (Anthropic) — 90.6% · $4.00/1M in Grok 4.7 (xAI) — 92.7% · $2.00/1M in DeepSeek V4.1 Flash (DeepSeek) — 89.8% · $0.056/1M in GPT-6 Astra (OpenAI) — 95.8% · $10.00/1M in Qwen3.8 Max (0902) (Qwen) — 92.7% · $2.00/1M in Gemini 3.8 Flash (Google) — 95.4% · $0.82/1M in GLM 5.3 Flash (Z.ai) — 90.1% · $0.047/1M in GLM 5.3 (Z.ai) — 90.9% · $0.079/1M in Gemini 3.7 Flash (Google) — 94.8% · $0.75/1M in DeepSeek V4 Pro 0813 (DeepSeek) — 91.7% · $0.66/1M in Grok 4.6 (xAI) — 94.0% · $2.00/1M in DeepSeek V4 Flash 0731 (DeepSeek) — 91.0% · $0.44/1M in Qwen3.7 Flash (Qwen) — 82.3% · $0.03/1M in Claude Opus 5 (Anthropic) — 93.9% · $5.00/1M in Gemini 3.6 Flash (Google) — 94.1% · $0.75/1M in Gemini 3.5 Flash Lite (Google) — 83.3% · $0.30/1M in Kimi K3 (Moonshot AI) — 93.1% · $0.24/1M in GPT-5.6 Luna (OpenAI) — 91.6% · $0.20/1M in GPT-5.6 Terra (OpenAI) — 93.3% · $2.00/1M in GPT-5.6 Sol (OpenAI) — 93.5% · $4.00/1M in Grok 4.5 (xAI) — 93.4% · $2.00/1M in Claude Sonnet 5 (Anthropic) — 90.5% · $2.00/1M in GLM 5.2 (Z.ai) — 91.9% · $0.62/1M in Kimi K2.7 Code (Moonshot AI) — 87.9% · $0.67/1M in Claude Fable 5 (Anthropic) — 85.9% · $10.00/1M in Qwen3.7 Plus (Qwen) — 87.9% · $0.32/1M in MiniMax M3 (MiniMax) — 90.9% · $0.30/1M in Claude Opus 4.8 (Anthropic) — 91.0% · $5.00/1M in Qwen3.7 Max (Qwen) — 90.9% · $1.48/1M in Gemini 3.5 Flash (Google) — 92.8% · $1.50/1M in Gemini 3.1 Flash Lite (Google) — 81.8% · $0.25/1M in Grok 4.3 (xAI) — 88.8% · $1.25/1M in Qwen3.5 Plus 2026-04-20 (Qwen) — 84.9% · $0.30/1M in Qwen3.6 Flash (Qwen) — 83.3% · $0.19/1M in Qwen3.6 35B A3B (Qwen) — 84.9% · $0.10/1M in Qwen3.6 27B (Qwen) — 85.9% · $0.25/1M in GPT-5.5 (OpenAI) — 90.7% · $5.00/1M in DeepSeek V4 Pro 0423 (DeepSeek) — 91.7% · $0.95/1M in DeepSeek V4 Flash 0423 (DeepSeek) — 91.0% · $0.091/1M in Kimi K2.6 (Moonshot AI) — 90.8% · $0.65/1M in Claude Opus 4.7 (Anthropic) — 90.1% · $5.00/1M in GLM 5.1 (Z.ai) — 89.9% · $0.97/1M in Gemma 4 26B A4B (Google) — 73.2% · $0.09/1M in Gemma 4 31B (Google) — 75.8% · $0.20/1M in Qwen3.6 Plus (Qwen) — 88.4% · $0.33/1M in GPT-5.4 Nano (OpenAI) — 78.5% · $0.20/1M in GPT-5.4 Mini (OpenAI) — 86.9% · $0.75/1M in Qwen3.5-9B (Qwen) — 79.0% · $0.10/1M in GPT-5.4 Pro (OpenAI) — 94.6% · $30.00/1M in GPT-5.4 (OpenAI) — 93.3% · $2.50/1M in Gemini 3.1 Flash Lite Preview (Google) — 81.8% · $0.25/1M in Qwen3.5-35B-A3B (Qwen) — 83.5% · $0.15/1M in Gemini 3.1 Pro Preview (Google) — 94.4% · $2.00/1M in Claude Sonnet 4.6 (Anthropic) — 87.4% · $3.00/1M in Qwen3.5 397B A17B (Qwen) — 86.4% · $0.39/1M in GLM 5 (Z.ai) — 87.8% · $0.60/1M in Claude Opus 4.6 (Anthropic) — 90.5% · $5.00/1M in GLM 4.7 Flash (Z.ai) — 60.5% · $0.061/1M in GLM 4.7 (Z.ai) — 83.3% · $0.54/1M in Gemini 3 Flash Preview (Google) — 89.4% · $0.50/1M in GPT-5.2 (OpenAI) — 91.4% · $1.75/1M in Claude Opus 4.5 (Anthropic) — 86.1% · $5.00/1M in GPT-5.1 (OpenAI) — 87.6% · $1.25/1M in Claude Haiku 4.5 (Anthropic) — 71.2% · $1.00/1M in Claude Sonnet 4.5 (Anthropic) — 82.3% · $3.00/1M in GPT-5 (OpenAI) — 86.2% · $1.25/1M in GPT-5 Mini (OpenAI) — 75.0% · $0.25/1M in GPT-5 Nano (OpenAI) — 69.4% · $0.05/1M in gpt-oss-120b (OpenAI) — 75.8% · $0.15/1M in gpt-oss-20b (OpenAI) — 60.8% · $0.018/1M in Claude Opus 4.1 (Anthropic) — 77.3% · $15.00/1M in Qwen3 30B A3B Instruct 2507 (Qwen) — 55.6% · $0.09/1M in Qwen3 235B A22B Thinking 2507 (Qwen) — 80.0% · $0.45/1M in Qwen3 235B A22B Instruct 2507 (Qwen) — 70.7% · $0.09/1M in Gemini 2.5 Pro (Google) — 85.3% · $1.25/1M in Gemini 2.5 Pro Preview 06-05 (Google) — 85.3% · $1.25/1M in R1 0528 (DeepSeek) — 76.3% · $0.50/1M in Qwen3 30B A3B (Qwen) — 61.7% · $0.12/1M in Qwen3 14B (Qwen) — 63.8% · $0.12/1M in Qwen3 32B (Qwen) — 65.7% · $0.08/1M in Mistral Small 4 (Mistral) — 47.5% · $0.15/1M in Ministral 3 8B 2512 (Mistral) — 27.2% · $0.15/1M in Ministral 3 3B 2512 (Mistral) — 25.3% · $0.10/1M in Mistral Large 3 2512 (Mistral) — 51.3% · $0.50/1M in Mistral Large 4 (Mistral) — 88.1% · $0.68/1M in Mistral Large 4

Mistral Large 4 Other Mistral Other labs Value frontier · GPQA Diamond vs. input price per 1M tokens (log scale) · Drag to pan, pinch or Ctrl + scroll to zoom, double-click to zoom in.

Benchmarks

13 benchmark scores

BenchmarkScoreRankLeader
FrontierCodeSoftware engineering · Mergeable fixes for hard open-source issues 39.4% #27of 41 Claude Opus 5.554.6%
SciCodeSoftware engineering · Research-coding problems from the natural sciences 54.2% #31of 93 Claude Opus 5.566.9%
WeirdML v3Software engineering · Unfamiliar ML and data tasks with vague goals 4.5% #22of 22 GPT-6 Astra42.2%
SimpleQA VerifiedWriting & content · Factual accuracy on 1,000 short questions 20.0% #61of 66 Gemini 4 Argon76.0%
Furniture AssemblyDesign & visual · Spot mistakes in photos of IKEA builds 20.8% #32of 34 Claude Opus 5.583.3%
GPQA DiamondReasoning & knowledge · PhD-level biology, chemistry and physics questions 88.1% #47of 92 Gemini 4 Argon96.4%
CritPtReasoning & knowledge · Open-ended, research-level physics problems 10.6% #48of 96 GPT-5.6 Sol32.3%
Chess PuzzlesReasoning & knowledge · Find the single best move in 100 new puzzles 33.0% #45of 70 GPT-6 Astra76.0%
LMCAReasoning & knowledge · Judge the quality of conceptual arguments like experts 35.8% #64of 96 Claude Sonnet 5.568.3%
FrontierMathMaths · Expert-written problems, undergrad to early research (tiers 1–3) 58.6% #41of 72 GPT-6.1 Sol93.7%
FrontierMath Tier 4Maths · Exceptionally hard research-level problems 26.8% #32of 62 GPT-6.1 Sol100.0%
ProofBenchMaths · Graduate maths proofs verified in Lean 4 10.0% #64of 70 Claude Sonnet 5.5100.0%
OTIS Mock AIMEMaths · Competition-style problems harder than MATH Level 5 98.3% #20of 90 Gemini 4 Argon100.0%

Specs

Details

Model ID
mistralai/mistral-large-4-0
Developer
Mistral
Release date
Oct 6, 2026 ·
Context window
1,048,576 tokens
Max output
262,144 tokens
API price
$0.68 / $2.09 per 1M input / output tokens
Providers
1
Input types
text, image
Reasoning
Yes
Tool calling
Yes
Open weights
No
Free tier
No

Release date, prices and providers from OpenRouter's catalog; buying directly from a provider can cost a little differently. Uptime is the share of OpenRouter requests each provider served over the last day. Benchmark scores are the best result per benchmark from Epoch AI, licensed CC BY 4.0. Rank counts every model tracked here with a score.