Noometry

Model comparison

GPT-5-Codex vs Mistral Large 3

Mistral Large 3 is the stronger model overall, scoring 39.1 to 37.9 on the Noometry Index.

Last verified . 1 shared benchmarks.

GPT-5-Codex OpenAI

37.9

Rank #192 Reported

Mistral Large 3 Mistral AI

39.1

Rank #176 Confirmed

Summary

  • They share 1 benchmark with published results for both. GPT-5-Codex scores higher in 2 categories and Mistral Large 3 in 0 categories; 2 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where GPT-5-Codex leads 30.9 to 15.2.
  • The biggest single-benchmark swing is Kagi LLM Benchmark: 70.3% for GPT-5-Codex and 50.9% for Mistral Large 3.
  • Mistral Large 3 is cheaper at $0.25 / $0.75 per million input/output tokens, against $1.25 / $10 for GPT-5-Codex.
  • GPT-5-Codex accepts more context: 400K tokens versus 262K.
  • Mistral Large 3 has downloadable open weights; the other is API-only.

Side by side

GPT-5-CodexMistral Large 3
ProviderOpenAIMistral AI
Noometry Index37.939.1
Released2025-09-152025-12-02
WeightsProprietaryOpen
Context window400K262K
Max output128K8K
Input $ / M tokens$1.25$0.25
Output $ / M tokens$10$0.75
Results tracked324

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Category by category

Coding GPT-5-Codex leads

GPT-5-Codex: 42.4 (#103), Mistral Large 3: 34.4 (#237)

BenchmarkGPT-5-CodexMistral Large 3
LMArena WebDev—1230
WeirdML54.5%—
LMArena Coding—1448

Agentic & Tool Use Not comparable

GPT-5-Codex: 31.0 (#72), Mistral Large 3: —

BenchmarkGPT-5-CodexMistral Large 3
Terminal-Bench44.3%—

Reasoning GPT-5-Codex leads

GPT-5-Codex: 30.9 (#83), Mistral Large 3: 15.2 (#319)

BenchmarkGPT-5-CodexMistral Large 3
Kagi LLM Benchmark70.3%50.9%
NYT Connections (extended)—7.5%
Thematic Generalization—23%
LMArena Hard Prompts—1429

Math Not comparable

GPT-5-Codex: —, Mistral Large 3: 38.7 (#129)

BenchmarkGPT-5-CodexMistral Large 3
LMArena Math—1414

Knowledge Not comparable

GPT-5-Codex: —, Mistral Large 3: 36.0 (#177)

BenchmarkGPT-5-CodexMistral Large 3
Vectara Hallucination Rate—14.5%
LMArena Expert—1421

Multimodal Not comparable

GPT-5-Codex: —, Mistral Large 3: 38.2 (#66)

BenchmarkGPT-5-CodexMistral Large 3
LMArena Vision—1221

Multilingual Not comparable

GPT-5-Codex: —, Mistral Large 3: 52.5 (#84)

BenchmarkGPT-5-CodexMistral Large 3
LMArena Non-English—1413
LMArena Chinese—1447
LMArena French—1455
LMArena German—1437
LMArena Japanese—1394
LMArena Korean—1384
LMArena Russian—1411
LMArena Spanish—1440

Instruction Following Not comparable

GPT-5-Codex: —, Mistral Large 3: 74.0 (#108)

BenchmarkGPT-5-CodexMistral Large 3
LMArena Instruction Following—1403

Long Context Not comparable

GPT-5-Codex: —, Mistral Large 3: 43.1 (#105)

BenchmarkGPT-5-CodexMistral Large 3
LMArena Longer Query—1413

Writing & Preference Not comparable

GPT-5-Codex: —, Mistral Large 3: 60.0 (#101)

BenchmarkGPT-5-CodexMistral Large 3
LMArena Text—1428
LMArena Creative Writing—1386
EQ-Bench Creative Writing—1412
LMArena Multi-Turn—1429

Frequently asked questions

Is GPT-5-Codex better than Mistral Large 3?

Mistral Large 3 is the stronger model overall, scoring 39.1 to 37.9 on the Noometry Index.

Which is cheaper, GPT-5-Codex or Mistral Large 3?

Mistral Large 3 is cheaper. It lists at $0.25 per million input tokens and $0.75 per million output tokens; GPT-5-Codex lists at $1.25 and $10.

Is GPT-5-Codex or Mistral Large 3 better for coding?

GPT-5-Codex scores higher on coding benchmarks: 42.4 versus 34.4 in the Noometry coding category.

Which has the bigger context window?

GPT-5-Codex does, with 400K tokens against 262K.

How many benchmarks do GPT-5-Codex and Mistral Large 3 share?

1 benchmark has published results for both models. GPT-5-Codex has 3 scored results on Noometry and Mistral Large 3 has 24.

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