Noometry

Model comparison

GPT-5-Codex vs Mistral Medium 3.5

Mistral Medium 3.5 is the stronger model overall, scoring 40.2 to 37.9 on the Noometry Index.

Last verified . 1 shared benchmarks.

GPT-5-Codex OpenAI

37.9

Rank #192 Reported

Mistral Medium 3.5 Mistral AI

40.2

Rank #152 Confirmed

Summary

  • They share 1 benchmark with published results for both. GPT-5-Codex scores higher in 2 categories and Mistral Medium 3.5 in 0 categories; 2 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where GPT-5-Codex leads 30.9 to 17.3.
  • The biggest single-benchmark swing is Kagi LLM Benchmark: 70.3% for GPT-5-Codex and 41.4% for Mistral Medium 3.5.
  • Mistral Medium 3.5 is cheaper at $1.50 / $7.50 per million input/output tokens, against $1.25 / $10 for GPT-5-Codex.
  • GPT-5-Codex accepts more context: 400K tokens versus 262K.
  • Mistral Medium 3.5 has downloadable open weights; the other is API-only.

Side by side

GPT-5-CodexMistral Medium 3.5
ProviderOpenAIMistral AI
Noometry Index37.940.2
Released2025-09-15—
WeightsProprietaryOpen
Context window400K262K
Max output128K210K
Input $ / M tokens$1.25$1.50
Output $ / M tokens$10$7.50
Results tracked322

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Category by category

Coding GPT-5-Codex leads

GPT-5-Codex: 42.4 (#103), Mistral Medium 3.5: 36.0 (#213)

BenchmarkGPT-5-CodexMistral Medium 3.5
LMArena WebDev—1264
WeirdML54.5%—
LMArena Coding—1461

Agentic & Tool Use Not comparable

GPT-5-Codex: 31.0 (#72), Mistral Medium 3.5: —

BenchmarkGPT-5-CodexMistral Medium 3.5
Terminal-Bench44.3%—

Reasoning GPT-5-Codex leads

GPT-5-Codex: 30.9 (#83), Mistral Medium 3.5: 17.3 (#295)

BenchmarkGPT-5-CodexMistral Medium 3.5
Kagi LLM Benchmark70.3%41.4%
NYT Connections (extended)—12.9%
LMArena Hard Prompts—1436
Epoch Capabilities Index—141.35

Math Not comparable

GPT-5-Codex: —, Mistral Medium 3.5: 39.1 (#113)

BenchmarkGPT-5-CodexMistral Medium 3.5
LMArena Math—1431

Knowledge Not comparable

GPT-5-Codex: —, Mistral Medium 3.5: 40.0 (#126)

BenchmarkGPT-5-CodexMistral Medium 3.5
LMArena Expert—1432

Multimodal Not comparable

GPT-5-Codex: —, Mistral Medium 3.5: 38.3 (#65)

BenchmarkGPT-5-CodexMistral Medium 3.5
LMArena Vision—1223

Multilingual Not comparable

GPT-5-Codex: —, Mistral Medium 3.5: 51.9 (#100)

BenchmarkGPT-5-CodexMistral Medium 3.5
LMArena Non-English—1404
LMArena Chinese—1442
LMArena French—1448
LMArena German—1451
LMArena Korean—1385
LMArena Russian—1395
LMArena Spanish—1409

Instruction Following Not comparable

GPT-5-Codex: —, Mistral Medium 3.5: 74.6 (#90)

BenchmarkGPT-5-CodexMistral Medium 3.5
LMArena Instruction Following—1415

Long Context Not comparable

GPT-5-Codex: —, Mistral Medium 3.5: 43.2 (#103)

BenchmarkGPT-5-CodexMistral Medium 3.5
LMArena Longer Query—1415

Writing & Preference Not comparable

GPT-5-Codex: —, Mistral Medium 3.5: 58.5 (#117)

BenchmarkGPT-5-CodexMistral Medium 3.5
LMArena Text—1421
LMArena Creative Writing—1374
EQ-Bench 4—993
LMArena Multi-Turn—1423

Frequently asked questions

Is GPT-5-Codex better than Mistral Medium 3.5?

Mistral Medium 3.5 is the stronger model overall, scoring 40.2 to 37.9 on the Noometry Index.

Which is cheaper, GPT-5-Codex or Mistral Medium 3.5?

Mistral Medium 3.5 is cheaper. It lists at $1.50 per million input tokens and $7.50 per million output tokens; GPT-5-Codex lists at $1.25 and $10.

Is GPT-5-Codex or Mistral Medium 3.5 better for coding?

GPT-5-Codex scores higher on coding benchmarks: 42.4 versus 36.0 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 Medium 3.5 share?

1 benchmark has published results for both models. GPT-5-Codex has 3 scored results on Noometry and Mistral Medium 3.5 has 22.

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