Model comparison

Mistral Large 3 vs Qwen3.6 27B

Qwen3.6 27B is the stronger model overall, scoring 41.9 to 38.6 on the Noometry Index. Mistral Large 3 costs 3.6× less per token, which makes it the better buy when Qwen3.6 27B's lead doesn't matter for your workload.

Last verified October 10, 2026. 0 shared benchmarks.

Mistral Large 3

Mistral AI

38.6

Rank #172 Confirmed

Qwen3.6 27B

Alibaba (Qwen)

41.9

Rank #112 Confirmed

Summary

The widest gap is in knowledge, where Qwen3.6 27B leads 52.4 to 35.5.
Mistral Large 3 is cheaper at $0.25 / $0.75 per million input/output tokens, against $0.60 / $3.60 for Qwen3.6 27B.

Side by side

Mistral Large 3 and Qwen3.6 27B specifications
	Mistral Large 3	Qwen3.6 27B
Provider	Mistral AI	Alibaba (Qwen)
Noometry Index	38.6	41.9
Released	2025-12-02	2026-04-22
Weights	Open	Open
Context window	262K	262K
Max output	8K	66K
Input $ / M tokens	$0.25	$0.60
Output $ / M tokens	$0.75	$3.60
Results tracked	24	11

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Category by category

Coding Qwen3.6 27B leads

Mistral Large 3: 34.1 (#230), Qwen3.6 27B: 38.5 (#162)

Coding benchmarks
Benchmark	Mistral Large 3	Qwen3.6 27B
LMArena WebDev	1230	—
SciCode	—	37.3%
LMArena Coding	1447	—

Reasoning Qwen3.6 27B leads

Mistral Large 3: 14.6 (#314), Qwen3.6 27B: 24.4 (#148)

Reasoning benchmarks
Benchmark	Mistral Large 3	Qwen3.6 27B
Kagi LLM Benchmark	50.9%	—
NYT Connections (extended)	7.5%	—
CritPt	—	0.9%
Chess Puzzles	—	22%
Thematic Generalization	23%	—
LMArena Hard Prompts	1429	—
Mystery Game Puzzles	—	7%
DTBench	—	78.1%
LMCA	—	34.5%
Epoch Capabilities Index	—	146.47

Math Qwen3.6 27B leads

Mistral Large 3: 36.0 (#131), Qwen3.6 27B: 47.5 (#56)

Math benchmarks
Benchmark	Mistral Large 3	Qwen3.6 27B
FrontierMath (Tiers 1-3)	—	35.1%
OTIS Mock AIME 2024-2025	—	91.1%
LMArena Math	1415	—

Knowledge Qwen3.6 27B leads

Mistral Large 3: 35.5 (#173), Qwen3.6 27B: 52.4 (#58)

Knowledge benchmarks
Benchmark	Mistral Large 3	Qwen3.6 27B
GPQA Diamond	—	85.9%
Vectara Hallucination Rate	14.5%	—
LMArena Expert	1421	—

Multimodal Not comparable

Mistral Large 3: 37.6 (#65), Qwen3.6 27B: —

Multimodal benchmarks
Benchmark	Mistral Large 3	Qwen3.6 27B
LMArena Vision	1222	—

Multilingual Not comparable

Mistral Large 3: 52.6 (#79), Qwen3.6 27B: —

Multilingual benchmarks
Benchmark	Mistral Large 3	Qwen3.6 27B
LMArena Non-English	1412	—
LMArena Chinese	1448	—
LMArena French	1456	—
LMArena German	1438	—
LMArena Japanese	1399	—
LMArena Korean	1384	—
LMArena Russian	1412	—
LMArena Spanish	1437	—

Instruction Following Not comparable

Mistral Large 3: 74.1 (#104), Qwen3.6 27B: —

Instruction Following benchmarks
Benchmark	Mistral Large 3	Qwen3.6 27B
LMArena Instruction Following	1402	—

Long Context Not comparable

Mistral Large 3: 43.1 (#102), Qwen3.6 27B: —

Long Context benchmarks
Benchmark	Mistral Large 3	Qwen3.6 27B
LMArena Longer Query	1413	—

Writing & Preference Mistral Large 3 leads

Mistral Large 3: 60.2 (#100), Qwen3.6 27B: 50.3 (#180)

Writing & Preference benchmarks
Benchmark	Mistral Large 3	Qwen3.6 27B
LMArena Text	1427	—
LMArena Creative Writing	1385	—
EQ-Bench Creative Writing	1412	—
EQ-Bench 4	—	1026
LMArena Multi-Turn	1429	—

Frequently asked questions

Is Mistral Large 3 better than Qwen3.6 27B?

Which is cheaper, Mistral Large 3 or Qwen3.6 27B?

Mistral Large 3 is cheaper. It lists at $0.25 per million input tokens and $0.75 per million output tokens; Qwen3.6 27B lists at $0.60 and $3.60.

Is Mistral Large 3 or Qwen3.6 27B better for coding?

Qwen3.6 27B scores higher on coding benchmarks: 38.5 versus 34.1 in the Noometry coding category.

Which has the bigger context window?

Both accept 262K tokens.

How many benchmarks do Mistral Large 3 and Qwen3.6 27B share?

0 benchmarks have published results for both models. Mistral Large 3 has 24 scored results on Noometry and Qwen3.6 27B has 11.