Model comparison

Codestral vs MiniMax-M2.7

MiniMax-M2.7 is the stronger model overall, scoring 37.7 to 30.6 on the Noometry Index.

Last verified October 11, 2026. 1 shared benchmarks.

Codestral

Mistral AI

30.6

Rank #290 Reported

MiniMax-M2.7

MiniMax

37.7

Rank #196 Confirmed

Summary

They share 1 benchmark with published results for both. Codestral scores higher in 1 category and MiniMax-M2.7 in 1 category; one gap is clear of the uncertainty.
The widest gap is in coding, where MiniMax-M2.7 leads 41.8 to 27.3.
Codestral is cheaper at $0.30 / $0.90 per million input/output tokens, against $0.30 / $1.20 for MiniMax-M2.7.
Codestral accepts more context: 256K tokens versus 205K.
MiniMax-M2.7 has downloadable open weights; the other is API-only.

Side by side

Codestral and MiniMax-M2.7 specifications
	Codestral	MiniMax-M2.7
Provider	Mistral AI	MiniMax
Noometry Index	30.6	37.7
Released	2024-05-29	2026-03-18
Weights	Proprietary	Open
Context window	256K	205K
Max output	8K	131K
Input $ / M tokens	$0.30	$0.30
Output $ / M tokens	$0.90	$1.20
Results tracked	7	30

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Category by category

Coding MiniMax-M2.7 leads

Codestral: 27.3 (#321), MiniMax-M2.7: 41.8 (#120)

Coding benchmarks
Benchmark	Codestral	MiniMax-M2.7
ALE-Bench	137.78	599.25
Aider Polyglot	11.1%	—
LMArena WebDev	—	1398
SciCode	—	47%
WeirdML	—	37%
BigCodeBench Instruct	41.8%	—
LMArena Coding	—	1454
BigCodeBench Complete	52.5%	—
HumanEval+	73.8%	—
MBPP+	61.9%	—

Agentic & Tool Use Not comparable

Codestral: —, MiniMax-M2.7: 25.1 (#111)

Agentic & Tool Use benchmarks
Benchmark	Codestral	MiniMax-M2.7
Terminal-Bench	—	45.1%
ExploitBench	—	13.3%
GBAEval	—	0%

Reasoning Too close to call

Codestral: 19.8 (#251), MiniMax-M2.7: 19.7 (#253)

Reasoning benchmarks
Benchmark	Codestral	MiniMax-M2.7
Kagi LLM Benchmark	32.5%	—
NYT Connections (extended)	—	24.7%
CritPt	—	0.6%
Thematic Generalization	—	39.3%
LMArena Hard Prompts	—	1422
Epoch Capabilities Index	—	145.85

Math Not comparable

Codestral: —, MiniMax-M2.7: 25.9 (#263)

Math benchmarks
Benchmark	Codestral	MiniMax-M2.7
ProofBench	—	3%
LMArena Math	—	1420

Knowledge Not comparable

Codestral: —, MiniMax-M2.7: 37.7 (#152)

Knowledge benchmarks
Benchmark	Codestral	MiniMax-M2.7
Vectara Hallucination Rate	—	12.9%
LMArena Expert	—	1444

Multilingual Not comparable

Codestral: —, MiniMax-M2.7: 50.3 (#123)

Multilingual benchmarks
Benchmark	Codestral	MiniMax-M2.7
LMArena Non-English	—	1382
LMArena Chinese	—	1441
LMArena French	—	1421
LMArena German	—	1398
LMArena Japanese	—	1262
LMArena Korean	—	1313
LMArena Russian	—	1383
LMArena Spanish	—	1403

Instruction Following Not comparable

Codestral: —, MiniMax-M2.7: 74.1 (#103)

Instruction Following benchmarks
Benchmark	Codestral	MiniMax-M2.7
LMArena Instruction Following	—	1405

Long Context Not comparable

Codestral: —, MiniMax-M2.7: 43.3 (#99)

Long Context benchmarks
Benchmark	Codestral	MiniMax-M2.7
LMArena Longer Query	—	1419

Writing & Preference Not comparable

Codestral: —, MiniMax-M2.7: 58.9 (#112)

Writing & Preference benchmarks
Benchmark	Codestral	MiniMax-M2.7
LMArena Text	—	1405
LMArena Creative Writing	—	1354
LMArena Multi-Turn	—	1412

Frequently asked questions

Is Codestral better than MiniMax-M2.7?

MiniMax-M2.7 is the stronger model overall, scoring 37.7 to 30.6 on the Noometry Index.

Which is cheaper, Codestral or MiniMax-M2.7?

Codestral is cheaper. It lists at $0.30 per million input tokens and $0.90 per million output tokens; MiniMax-M2.7 lists at $0.30 and $1.20.

Is Codestral or MiniMax-M2.7 better for coding?

MiniMax-M2.7 scores higher on coding benchmarks: 41.8 versus 27.3 in the Noometry coding category.

Which has the bigger context window?

Codestral does, with 256K tokens against 205K.

How many benchmarks do Codestral and MiniMax-M2.7 share?

1 benchmark has published results for both models. Codestral has 7 scored results on Noometry and MiniMax-M2.7 has 30.