Noometry

Model comparison

Mistral Large 4 vs Qwen3.8 27B

Qwen3.8 27B is the stronger model overall, scoring 46.0 to 43.1 on the Noometry Index.

Last verified . 14 shared benchmarks.

Mistral Large 4 Mistral AI

43.1

Rank #99 Confirmed

Qwen3.8 27B Alibaba (Qwen)

46.0

Rank #68 Confirmed

Summary

  • They share 14 benchmarks with published results for both. Mistral Large 4 scores higher in 1 category and Qwen3.8 27B in 7 categories; 6 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where Qwen3.8 27B leads 41.0 to 22.5.
  • The biggest single-benchmark swing is NYT Connections (extended): 27.4% for Mistral Large 4 and 54.5% for Qwen3.8 27B.
  • Mistral Large 4 is cheaper at $0.68 / $2.09 per million input/output tokens, against $0.99 / $1.49 for Qwen3.8 27B.
  • Mistral Large 4 accepts more context: 1.05M tokens versus 262K.
  • Qwen3.8 27B has downloadable open weights; the other is API-only.

Side by side

Mistral Large 4Qwen3.8 27B
ProviderMistral AIAlibaba (Qwen)
Noometry Index43.146.0
Released2026-10-062026-08-14
WeightsProprietaryOpen
Context window1.05M262K
Max output262K33K
Input $ / M tokens$0.68$0.99
Output $ / M tokens$2.09$1.49
Results tracked1531

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Category by category

Coding Qwen3.8 27B leads

Mistral Large 4: 48.6 (#57), Qwen3.8 27B: 50.5 (#44)

BenchmarkMistral Large 4Qwen3.8 27B
LMArena WebDev15411593
LMArena Coding14751482
SciCode—46.6%

Agentic & Tool Use Not comparable

Mistral Large 4: —, Qwen3.8 27B: 32.9 (#57)

BenchmarkMistral Large 4Qwen3.8 27B
APEX-Agents—47.5%

Reasoning Qwen3.8 27B leads

Mistral Large 4: 22.5 (#192), Qwen3.8 27B: 41.0 (#54)

BenchmarkMistral Large 4Qwen3.8 27B
NYT Connections (extended)27.4%54.5%
LMArena Hard Prompts14441460
ARC-AGI-2—42.4%
ARC-AGI-1—87.5%
CritPt—5.4%
DTBench—88%
LMCA—41.4%
Surface Evolver Bench—45%
Epoch Capabilities Index—149.38

Math Mistral Large 4 leads

Mistral Large 4: 40.4 (#91), Qwen3.8 27B: 37.1 (#161)

BenchmarkMistral Large 4Qwen3.8 27B
LMArena Math14881456
ProofBench—16%

Knowledge Qwen3.8 27B leads

Mistral Large 4: 36.6 (#166), Qwen3.8 27B: 41.6 (#109)

BenchmarkMistral Large 4Qwen3.8 27B
LMArena Expert14471482
SimpleQA Verified20%—

Multimodal Not comparable

Mistral Large 4: —, Qwen3.8 27B: 41.3 (#37)

BenchmarkMistral Large 4Qwen3.8 27B
LMArena Vision—1271

Multilingual Qwen3.8 27B leads

Mistral Large 4: 52.6 (#82), Qwen3.8 27B: 53.7 (#60)

BenchmarkMistral Large 4Qwen3.8 27B
LMArena Non-English14151430
LMArena Chinese14911504
LMArena Russian14141415
LMArena French—1465
LMArena German—1438
LMArena Japanese—1384
LMArena Korean—1393
LMArena Spanish—1448

Instruction Following Too close to call

Mistral Large 4: 75.0 (#76), Qwen3.8 27B: 75.8 (#53)

BenchmarkMistral Large 4Qwen3.8 27B
LMArena Instruction Following14241439

Long Context Too close to call

Mistral Large 4: 43.6 (#89), Qwen3.8 27B: 44.3 (#70)

BenchmarkMistral Large 4Qwen3.8 27B
LMArena Longer Query14291450

Writing & Preference Qwen3.8 27B leads

Mistral Large 4: 60.4 (#97), Qwen3.8 27B: 65.8 (#43)

BenchmarkMistral Large 4Qwen3.8 27B
LMArena Text14271441
LMArena Creative Writing13611384
LMArena Multi-Turn14241441
EQ-Bench Creative Writing—1671

Frequently asked questions

Is Mistral Large 4 better than Qwen3.8 27B?

Qwen3.8 27B is the stronger model overall, scoring 46.0 to 43.1 on the Noometry Index.

Which is cheaper, Mistral Large 4 or Qwen3.8 27B?

Mistral Large 4 is cheaper. It lists at $0.68 per million input tokens and $2.09 per million output tokens; Qwen3.8 27B lists at $0.99 and $1.49.

Is Mistral Large 4 or Qwen3.8 27B better for coding?

Qwen3.8 27B scores higher on coding benchmarks: 50.5 versus 48.6 in the Noometry coding category.

Which has the bigger context window?

Mistral Large 4 does, with 1.05M tokens against 262K.

How many benchmarks do Mistral Large 4 and Qwen3.8 27B share?

14 benchmarks have published results for both models. Mistral Large 4 has 15 scored results on Noometry and Qwen3.8 27B has 31.

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