Model comparison

GPT-5-Codex vs Mistral Small 3.1

GPT-5-Codex is the stronger model overall, scoring 37.9 to 31.7 on the Noometry Index. Mistral Small 3.1 costs 8.6× less per token, which makes it the better buy when GPT-5-Codex's lead doesn't matter for your workload.

Last verified October 11, 2026. 0 shared benchmarks.

GPT-5-Codex OpenAI

37.9

Rank #192 Reported

Mistral Small 3.1

Mistral AI

31.7

Rank #269 Confirmed

Summary

The widest gap is in reasoning, where GPT-5-Codex leads 30.9 to 19.7.
Mistral Small 3.1 is cheaper at $0.35 / $0.56 per million input/output tokens, against $1.25 / $10 for GPT-5-Codex.
GPT-5-Codex accepts more context: 400K tokens versus 128K.
Mistral Small 3.1 has downloadable open weights; the other is API-only.

Side by side

GPT-5-Codex and Mistral Small 3.1 specifications
	GPT-5-Codex	Mistral Small 3.1
Provider	OpenAI	Mistral AI
Noometry Index	37.9	31.7
Released	2025-09-15	2025-03-17
Weights	Proprietary	Open
Context window	400K	128K
Max output	128K	102K
Input $ / M tokens	$1.25	$0.35
Output $ / M tokens	$10	$0.56
Results tracked	3	28

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Category by category

Coding GPT-5-Codex leads

GPT-5-Codex: 42.4 (#103), Mistral Small 3.1: 38.3 (#179)

Coding benchmarks
Benchmark	GPT-5-Codex	Mistral Small 3.1
WeirdML	54.5%	—
LMArena Coding	—	1309

Agentic & Tool Use Not comparable

GPT-5-Codex: 31.0 (#72), Mistral Small 3.1: —

Agentic & Tool Use benchmarks
Benchmark	GPT-5-Codex	Mistral Small 3.1
Terminal-Bench	44.3%	—

Reasoning GPT-5-Codex leads

GPT-5-Codex: 30.9 (#83), Mistral Small 3.1: 19.7 (#254)

Reasoning benchmarks
Benchmark	GPT-5-Codex	Mistral Small 3.1
Kagi LLM Benchmark	70.3%	—
Chess Puzzles	—	1%
LMArena Hard Prompts	—	1278
Epoch Capabilities Index	—	127.48

Math Not comparable

GPT-5-Codex: —, Mistral Small 3.1: 14.7 (#301)

Math benchmarks
Benchmark	GPT-5-Codex	Mistral Small 3.1
OTIS Mock AIME 2024-2025	—	3.9%
Omni-MATH	—	24.8%
LMArena Math	—	1262

Knowledge Not comparable

GPT-5-Codex: —, Mistral Small 3.1: 22.6 (#271)

Knowledge benchmarks
Benchmark	GPT-5-Codex	Mistral Small 3.1
GPQA Diamond	—	41.9%
MMLU-Pro	—	61%
GPQA (HELM)	—	39.2%
LMArena Expert	—	1257

Multimodal Not comparable

GPT-5-Codex: —, Mistral Small 3.1: 33.2 (#99)

Multimodal benchmarks
Benchmark	GPT-5-Codex	Mistral Small 3.1
LMArena Vision	—	1136

Multilingual Not comparable

GPT-5-Codex: —, Mistral Small 3.1: 41.2 (#209)

Multilingual benchmarks
Benchmark	GPT-5-Codex	Mistral Small 3.1
LMArena Non-English	—	1255
LMArena Chinese	—	1253
LMArena French	—	1273
LMArena German	—	1266
LMArena Japanese	—	1208
LMArena Korean	—	1206
LMArena Russian	—	1263
LMArena Spanish	—	1283

Instruction Following Not comparable

GPT-5-Codex: —, Mistral Small 3.1: 63.6 (#230)

Instruction Following benchmarks
Benchmark	GPT-5-Codex	Mistral Small 3.1
IFEval	—	75%
LMArena Instruction Following	—	1264

Long Context Not comparable

GPT-5-Codex: —, Mistral Small 3.1: 39.5 (#178)

Long Context benchmarks
Benchmark	GPT-5-Codex	Mistral Small 3.1
LMArena Longer Query	—	1299

Writing & Preference Not comparable

GPT-5-Codex: —, Mistral Small 3.1: 37.0 (#259)

Writing & Preference benchmarks
Benchmark	GPT-5-Codex	Mistral Small 3.1
LMArena Text	—	1277
LMArena Creative Writing	—	1253
EQ-Bench Creative Writing	—	761
WildBench	—	78.8%
LMArena Multi-Turn	—	1270

Frequently asked questions

Is GPT-5-Codex better than Mistral Small 3.1?

Which is cheaper, GPT-5-Codex or Mistral Small 3.1?

Mistral Small 3.1 is cheaper. It lists at $0.35 per million input tokens and $0.56 per million output tokens; GPT-5-Codex lists at $1.25 and $10.

Is GPT-5-Codex or Mistral Small 3.1 better for coding?

GPT-5-Codex scores higher on coding benchmarks: 42.4 versus 38.3 in the Noometry coding category.

Which has the bigger context window?

GPT-5-Codex does, with 400K tokens against 128K.

How many benchmarks do GPT-5-Codex and Mistral Small 3.1 share?

0 benchmarks have published results for both models. GPT-5-Codex has 3 scored results on Noometry and Mistral Small 3.1 has 28.