Model comparison

Kimi K2.7 Code vs Qwen Max

Kimi K2.7 Code is the stronger model overall, scoring 43.3 to 34.7 on the Noometry Index.

Last verified . 2 shared benchmarks.

Kimi K2.7 Code Moonshot AI

43.3

Rank #94 Confirmed

Qwen Max Alibaba (Qwen)

34.7

Rank #230 Confirmed

Summary

  • They share 2 benchmarks with published results for both. Kimi K2.7 Code scores higher in 4 categories and Qwen Max in 0 categories; 4 gaps are clear of the uncertainty.
  • The widest gap is in math, where Kimi K2.7 Code leads 52.9 to 22.3.
  • The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 95.6% for Kimi K2.7 Code and 16.1% for Qwen Max.
  • Kimi K2.7 Code is cheaper at $0.95 / $4 per million input/output tokens, against $1.60 / $6.40 for Qwen Max.
  • Kimi K2.7 Code accepts more context: 262K tokens versus 33K.
  • Kimi K2.7 Code has downloadable open weights; the other is API-only.

Side by side

Kimi K2.7 Code and Qwen Max specifications
Kimi K2.7 CodeQwen Max
ProviderMoonshot AIAlibaba (Qwen)
Noometry Index43.334.7
Released2026-06-122024-04-03
WeightsOpenProprietary
Context window262K33K
Max output262K8K
Input $ / M tokens$0.95$1.60
Output $ / M tokens$4$6.40
Results tracked1923

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Category by category

Coding Kimi K2.7 Code leads

Kimi K2.7 Code: 42.9 (#95), Qwen Max: 30.7 (#292)

Coding benchmarks
BenchmarkKimi K2.7 CodeQwen Max
DeepSWE30.5%—
FrontierCode30.1%—
Aider Polyglot—21.8%
LMArena WebDev1473—
SciCode47.5%—
WeirdML54.1%—
LMArena Coding—1288
ALE-Bench886.23—

Agentic & Tool Use Not comparable

Kimi K2.7 Code: 24.0 (#122), Qwen Max: —

Agentic & Tool Use benchmarks
BenchmarkKimi K2.7 CodeQwen Max
APEX-Agents37.6%—
GBAEval0.9%—
Vending-Bench 25,083—

Reasoning Kimi K2.7 Code leads

Kimi K2.7 Code: 39.0 (#61), Qwen Max: 25.1 (#151)

Reasoning benchmarks
BenchmarkKimi K2.7 CodeQwen Max
SimpleBench57.9%—
CritPt10%—
Chess Puzzles21%—
LMArena Hard Prompts—1269
Surface Evolver Bench48.8%—
Epoch Capabilities Index149.97—

Math Kimi K2.7 Code leads

Kimi K2.7 Code: 52.9 (#48), Qwen Max: 22.3 (#276)

Math benchmarks
BenchmarkKimi K2.7 CodeQwen Max
OTIS Mock AIME 2024-202595.6%16.1%
FrontierMath (Tiers 1-3)54%—
FrontierMath Tier 412.2%—
LMArena Math—1275
MATH Level 5—67.2%
FrontierMath (Feb 2025 set)—1%

Knowledge Kimi K2.7 Code leads

Kimi K2.7 Code: 53.5 (#57), Qwen Max: 30.3 (#228)

Knowledge benchmarks
BenchmarkKimi K2.7 CodeQwen Max
GPQA Diamond87.9%56.1%
SimpleQA Verified36.5%—
LMArena Expert—1248

Multilingual Not comparable

Kimi K2.7 Code: —, Qwen Max: 41.8 (#202)

Multilingual benchmarks
BenchmarkKimi K2.7 CodeQwen Max
LMArena Non-English—1263
LMArena Chinese—1254
LMArena French—1330
LMArena German—1254
LMArena Japanese—1205
LMArena Korean—1142
LMArena Russian—1274
LMArena Spanish—1290

Instruction Following Not comparable

Kimi K2.7 Code: —, Qwen Max: 66.5 (#208)

Instruction Following benchmarks
BenchmarkKimi K2.7 CodeQwen Max
LMArena Instruction Following—1262

Long Context Not comparable

Kimi K2.7 Code: —, Qwen Max: 39.4 (#180)

Long Context benchmarks
BenchmarkKimi K2.7 CodeQwen Max
Fiction.LiveBench—66.7%
LMArena Longer Query—1288

Writing & Preference Not comparable

Kimi K2.7 Code: —, Qwen Max: 47.8 (#205)

Writing & Preference benchmarks
BenchmarkKimi K2.7 CodeQwen Max
LMArena Text—1282
LMArena Creative Writing—1248
LMArena Multi-Turn—1277

Frequently asked questions

Is Kimi K2.7 Code better than Qwen Max?

Kimi K2.7 Code is the stronger model overall, scoring 43.3 to 34.7 on the Noometry Index.

Which is cheaper, Kimi K2.7 Code or Qwen Max?

Kimi K2.7 Code is cheaper. It lists at $0.95 per million input tokens and $4 per million output tokens; Qwen Max lists at $1.60 and $6.40.

Is Kimi K2.7 Code or Qwen Max better for coding?

Kimi K2.7 Code scores higher on coding benchmarks: 42.9 versus 30.7 in the Noometry coding category.

Which has the bigger context window?

Kimi K2.7 Code does, with 262K tokens against 33K.

How many benchmarks do Kimi K2.7 Code and Qwen Max share?

2 benchmarks have published results for both models. Kimi K2.7 Code has 19 scored results on Noometry and Qwen Max has 23.

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