Noometry

Model comparison

Mistral Medium 3.5 vs Qwen3.5 27B

Qwen3.5 27B is the stronger model overall, scoring 41.4 to 39.6 on the Noometry Index.

Last verified . 19 shared benchmarks.

Mistral Medium 3.5 Mistral AI

39.6

Rank #151 Confirmed

Qwen3.5 27B Alibaba (Qwen)

41.4

Rank #127 Confirmed

Summary

  • They share 19 benchmarks with published results for both. Mistral Medium 3.5 scores higher in 4 categories and Qwen3.5 27B in 5 categories; 6 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where Qwen3.5 27B leads 26.6 to 16.6.
  • The biggest single-benchmark swing is NYT Connections (extended): 12.9% for Mistral Medium 3.5 and 47.9% for Qwen3.5 27B.
  • Qwen3.5 27B is cheaper at $0.30 / $2.40 per million input/output tokens, against $1.50 / $7.50 for Mistral Medium 3.5.

Side by side

Mistral Medium 3.5Qwen3.5 27B
ProviderMistral AIAlibaba (Qwen)
Noometry Index39.641.4
Released—2026-02-23
WeightsOpenOpen
Context window262K262K
Max output210K66K
Input $ / M tokens$1.50$0.30
Output $ / M tokens$7.50$2.40
Results tracked2228

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Category by category

Coding Qwen3.5 27B leads

Mistral Medium 3.5: 35.7 (#208), Qwen3.5 27B: 38.6 (#159)

BenchmarkMistral Medium 3.5Qwen3.5 27B
LMArena WebDev12631357
LMArena Coding14611427
WeirdML—39.5%
ALE-Bench—349.45

Agentic & Tool Use Not comparable

Mistral Medium 3.5: —, Qwen3.5 27B: —

BenchmarkMistral Medium 3.5Qwen3.5 27B
Vending-Bench 2—201.98

Reasoning Qwen3.5 27B leads

Mistral Medium 3.5: 16.6 (#290), Qwen3.5 27B: 26.6 (#116)

BenchmarkMistral Medium 3.5Qwen3.5 27B
NYT Connections (extended)12.9%47.9%
LMArena Hard Prompts14361414
Kagi LLM Benchmark41.4%—
Thematic Generalization—45.5%
DTBench—82.4%
LMCA—34%
Epoch Capabilities Index141.42—

Math Too close to call

Mistral Medium 3.5: 36.4 (#113), Qwen3.5 27B: 36.8 (#103)

BenchmarkMistral Medium 3.5Qwen3.5 27B
LMArena Math14321428
MathArena Final-Answer Competitions—56.7%

Knowledge Mistral Medium 3.5 leads

Mistral Medium 3.5: 39.3 (#123), Qwen3.5 27B: 37.4 (#149)

BenchmarkMistral Medium 3.5Qwen3.5 27B
LMArena Expert14311428
Vectara Hallucination Rate—12.1%

Multimodal Qwen3.5 27B leads

Mistral Medium 3.5: 37.6 (#64), Qwen3.5 27B: 38.7 (#56)

BenchmarkMistral Medium 3.5Qwen3.5 27B
LMArena Vision12221240

Multilingual Mistral Medium 3.5 leads

Mistral Medium 3.5: 52.1 (#93), Qwen3.5 27B: 51.0 (#112)

BenchmarkMistral Medium 3.5Qwen3.5 27B
LMArena Non-English14051390
LMArena Chinese14431478
LMArena French14481409
LMArena German14531393
LMArena Korean13871359
LMArena Russian13961389
LMArena Spanish14061408
LMArena Japanese—1345

Instruction Following Mistral Medium 3.5 leads

Mistral Medium 3.5: 74.7 (#87), Qwen3.5 27B: 73.7 (#114)

BenchmarkMistral Medium 3.5Qwen3.5 27B
LMArena Instruction Following14141393

Long Context Too close to call

Mistral Medium 3.5: 43.2 (#101), Qwen3.5 27B: 43.1 (#103)

BenchmarkMistral Medium 3.5Qwen3.5 27B
LMArena Longer Query14141413

Writing & Preference Too close to call

Mistral Medium 3.5: 58.6 (#113), Qwen3.5 27B: 59.5 (#106)

BenchmarkMistral Medium 3.5Qwen3.5 27B
LMArena Text14211409
LMArena Creative Writing13721362
LMArena Multi-Turn14231410
EQ-Bench 4993—

Frequently asked questions

Is Mistral Medium 3.5 better than Qwen3.5 27B?

Qwen3.5 27B is the stronger model overall, scoring 41.4 to 39.6 on the Noometry Index.

Which is cheaper, Mistral Medium 3.5 or Qwen3.5 27B?

Qwen3.5 27B is cheaper. It lists at $0.30 per million input tokens and $2.40 per million output tokens; Mistral Medium 3.5 lists at $1.50 and $7.50.

Is Mistral Medium 3.5 or Qwen3.5 27B better for coding?

Qwen3.5 27B scores higher on coding benchmarks: 38.6 versus 35.7 in the Noometry coding category.

Which has the bigger context window?

Both accept 262K tokens.

How many benchmarks do Mistral Medium 3.5 and Qwen3.5 27B share?

19 benchmarks have published results for both models. Mistral Medium 3.5 has 22 scored results on Noometry and Qwen3.5 27B has 28.

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