Model comparison

Codestral vs Qwen3.5 122B-A10B

Qwen3.5 122B-A10B is the stronger model overall, scoring 42.1 to 30.6 on the Noometry Index. Codestral costs 2.4× less per token, which makes it the better buy when Qwen3.5 122B-A10B's lead doesn't matter for your workload.

Last verified October 10, 2026. 0 shared benchmarks.

Codestral

Mistral AI

30.6

Rank #290 Reported

Qwen3.5 122B-A10B

Alibaba (Qwen)

42.1

Rank #119 Confirmed

Summary

The widest gap is in coding, where Qwen3.5 122B-A10B leads 39.1 to 27.3.
Codestral is cheaper at $0.30 / $0.90 per million input/output tokens, against $0.40 / $3.20 for Qwen3.5 122B-A10B.
Qwen3.5 122B-A10B accepts more context: 262K tokens versus 256K.
Qwen3.5 122B-A10B has downloadable open weights; the other is API-only.

Side by side

Codestral and Qwen3.5 122B-A10B specifications
	Codestral	Qwen3.5 122B-A10B
Provider	Mistral AI	Alibaba (Qwen)
Noometry Index	30.6	42.1
Released	2024-05-29	2026-02-23
Weights	Proprietary	Open
Context window	256K	262K
Max output	8K	66K
Input $ / M tokens	$0.30	$0.40
Output $ / M tokens	$0.90	$3.20
Results tracked	7	27

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Category by category

Coding Qwen3.5 122B-A10B leads

Codestral: 27.3 (#321), Qwen3.5 122B-A10B: 39.1 (#162)

Coding benchmarks
Benchmark	Codestral	Qwen3.5 122B-A10B
Aider Polyglot	11.1%	—
LMArena WebDev	—	1360
SciCode	—	35.6%
BigCodeBench Instruct	41.8%	—
LMArena Coding	—	1436
BigCodeBench Complete	52.5%	—
ALE-Bench	137.78	—
HumanEval+	73.8%	—
MBPP+	61.9%	—

Reasoning Qwen3.5 122B-A10B leads

Codestral: 19.8 (#251), Qwen3.5 122B-A10B: 27.2 (#123)

Reasoning benchmarks
Benchmark	Codestral	Qwen3.5 122B-A10B
Kagi LLM Benchmark	32.5%	—
NYT Connections (extended)	—	51.7%
CritPt	—	0.9%
Thematic Generalization	—	51.2%
LMArena Hard Prompts	—	1421
Mystery Game Puzzles	—	17%
DTBench	—	84.3%
LMCA	—	32.2%

Math Not comparable

Codestral: —, Qwen3.5 122B-A10B: 39.1 (#112)

Math benchmarks
Benchmark	Codestral	Qwen3.5 122B-A10B
LMArena Math	—	1432

Knowledge Not comparable

Codestral: —, Qwen3.5 122B-A10B: 38.8 (#142)

Knowledge benchmarks
Benchmark	Codestral	Qwen3.5 122B-A10B
Vectara Hallucination Rate	—	11.2%
LMArena Expert	—	1432

Multimodal Not comparable

Codestral: —, Qwen3.5 122B-A10B: 39.6 (#57)

Multimodal benchmarks
Benchmark	Codestral	Qwen3.5 122B-A10B
LMArena Vision	—	1245

Multilingual Not comparable

Codestral: —, Qwen3.5 122B-A10B: 51.6 (#107)

Multilingual benchmarks
Benchmark	Codestral	Qwen3.5 122B-A10B
LMArena Non-English	—	1400
LMArena Chinese	—	1462
LMArena French	—	1442
LMArena German	—	1426
LMArena Japanese	—	1367
LMArena Korean	—	1352
LMArena Russian	—	1400
LMArena Spanish	—	1424

Instruction Following Not comparable

Codestral: —, Qwen3.5 122B-A10B: 73.8 (#115)

Instruction Following benchmarks
Benchmark	Codestral	Qwen3.5 122B-A10B
LMArena Instruction Following	—	1399

Long Context Not comparable

Codestral: —, Qwen3.5 122B-A10B: 43.0 (#109)

Long Context benchmarks
Benchmark	Codestral	Qwen3.5 122B-A10B
LMArena Longer Query	—	1410

Writing & Preference Not comparable

Codestral: —, Qwen3.5 122B-A10B: 60.0 (#105)

Writing & Preference benchmarks
Benchmark	Codestral	Qwen3.5 122B-A10B
LMArena Text	—	1417
LMArena Creative Writing	—	1368
LMArena Multi-Turn	—	1416

Frequently asked questions

Is Codestral better than Qwen3.5 122B-A10B?

Which is cheaper, Codestral or Qwen3.5 122B-A10B?

Codestral is cheaper. It lists at $0.30 per million input tokens and $0.90 per million output tokens; Qwen3.5 122B-A10B lists at $0.40 and $3.20.

Is Codestral or Qwen3.5 122B-A10B better for coding?

Qwen3.5 122B-A10B scores higher on coding benchmarks: 39.1 versus 27.3 in the Noometry coding category.

Which has the bigger context window?

Qwen3.5 122B-A10B does, with 262K tokens against 256K.

How many benchmarks do Codestral and Qwen3.5 122B-A10B share?

0 benchmarks have published results for both models. Codestral has 7 scored results on Noometry and Qwen3.5 122B-A10B has 27.