Model comparison

Mistral Medium 3.5 vs Qwen3.6 27B

Qwen3.6 27B is the stronger model overall, scoring 42.2 to 40.2 on the Noometry Index.

Last verified October 10, 2026. 2 shared benchmarks.

Mistral Medium 3.5

Mistral AI

40.2

Rank #152 Confirmed

Qwen3.6 27B

Alibaba (Qwen)

42.2

Rank #117 Confirmed

Summary

They share 2 benchmarks with published results for both. Mistral Medium 3.5 scores higher in 1 category and Qwen3.6 27B in 4 categories; 5 gaps are clear of the uncertainty.
The widest gap is in knowledge, where Qwen3.6 27B leads 52.4 to 40.0.
Qwen3.6 27B is cheaper at $0.60 / $3.60 per million input/output tokens, against $1.50 / $7.50 for Mistral Medium 3.5.

Side by side

Mistral Medium 3.5 and Qwen3.6 27B specifications
	Mistral Medium 3.5	Qwen3.6 27B
Provider	Mistral AI	Alibaba (Qwen)
Noometry Index	40.2	42.2
Released	—	2026-04-22
Weights	Open	Open
Context window	262K	262K
Max output	210K	66K
Input $ / M tokens	$1.50	$0.60
Output $ / M tokens	$7.50	$3.60
Results tracked	22	11

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Category by category

Coding Qwen3.6 27B leads

Mistral Medium 3.5: 36.0 (#213), Qwen3.6 27B: 39.1 (#163)

Coding benchmarks
Benchmark	Mistral Medium 3.5	Qwen3.6 27B
LMArena WebDev	1264	—
SciCode	—	37.3%
LMArena Coding	1461	—

Reasoning Qwen3.6 27B leads

Mistral Medium 3.5: 17.3 (#295), Qwen3.6 27B: 25.0 (#153)

Reasoning benchmarks
Benchmark	Mistral Medium 3.5	Qwen3.6 27B
Epoch Capabilities Index	141.35	146.5
Kagi LLM Benchmark	41.4%	—
NYT Connections (extended)	12.9%	—
CritPt	—	0.9%
Chess Puzzles	—	22%
LMArena Hard Prompts	1436	—
Mystery Game Puzzles	—	7%
DTBench	—	78.1%
LMCA	—	34.5%

Math Qwen3.6 27B leads

Mistral Medium 3.5: 39.1 (#113), Qwen3.6 27B: 48.5 (#62)

Math benchmarks
Benchmark	Mistral Medium 3.5	Qwen3.6 27B
FrontierMath (Tiers 1-3)	—	35.1%
OTIS Mock AIME 2024-2025	—	91.1%
LMArena Math	1431	—

Knowledge Qwen3.6 27B leads

Mistral Medium 3.5: 40.0 (#126), Qwen3.6 27B: 52.4 (#63)

Knowledge benchmarks
Benchmark	Mistral Medium 3.5	Qwen3.6 27B
GPQA Diamond	—	85.9%
LMArena Expert	1432	—

Multimodal Not comparable

Mistral Medium 3.5: 38.3 (#65), Qwen3.6 27B: —

Multimodal benchmarks
Benchmark	Mistral Medium 3.5	Qwen3.6 27B
LMArena Vision	1223	—

Multilingual Not comparable

Mistral Medium 3.5: 51.9 (#100), Qwen3.6 27B: —

Multilingual benchmarks
Benchmark	Mistral Medium 3.5	Qwen3.6 27B
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

Mistral Medium 3.5: 74.6 (#90), Qwen3.6 27B: —

Instruction Following benchmarks
Benchmark	Mistral Medium 3.5	Qwen3.6 27B
LMArena Instruction Following	1415	—

Long Context Not comparable

Mistral Medium 3.5: 43.2 (#103), Qwen3.6 27B: —

Long Context benchmarks
Benchmark	Mistral Medium 3.5	Qwen3.6 27B
LMArena Longer Query	1415	—

Writing & Preference Mistral Medium 3.5 leads

Mistral Medium 3.5: 58.5 (#117), Qwen3.6 27B: 50.3 (#181)

Writing & Preference benchmarks
Benchmark	Mistral Medium 3.5	Qwen3.6 27B
EQ-Bench 4	993	1026
LMArena Text	1421	—
LMArena Creative Writing	1374	—
LMArena Multi-Turn	1423	—

Frequently asked questions

Is Mistral Medium 3.5 better than Qwen3.6 27B?

Qwen3.6 27B is the stronger model overall, scoring 42.2 to 40.2 on the Noometry Index.

Which is cheaper, Mistral Medium 3.5 or Qwen3.6 27B?

Qwen3.6 27B is cheaper. It lists at $0.60 per million input tokens and $3.60 per million output tokens; Mistral Medium 3.5 lists at $1.50 and $7.50.

Is Mistral Medium 3.5 or Qwen3.6 27B better for coding?

Qwen3.6 27B scores higher on coding benchmarks: 39.1 versus 36.0 in the Noometry coding category.

Which has the bigger context window?

Both accept 262K tokens.

How many benchmarks do Mistral Medium 3.5 and Qwen3.6 27B share?

2 benchmarks have published results for both models. Mistral Medium 3.5 has 22 scored results on Noometry and Qwen3.6 27B has 11.