Model comparison

GLM-4.7-Flash vs Kimi K2.7 Code

Kimi K2.7 Code is the stronger model overall, scoring 43.3 to 38.8 on the Noometry Index. GLM-4.7-Flash costs 12× less per token, which makes it the better buy when Kimi K2.7 Code's lead doesn't matter for your workload.

Last verified . 3 shared benchmarks.

GLM-4.7-Flash Z.ai (Zhipu)

38.8

Rank #180 Confirmed

Kimi K2.7 Code Moonshot AI

43.3

Rank #94 Confirmed

Summary

  • They share 3 benchmarks with published results for both. GLM-4.7-Flash scores higher in 0 categories and Kimi K2.7 Code in 4 categories; 4 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where Kimi K2.7 Code leads 39.0 to 20.9.
  • The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 58.3% for GLM-4.7-Flash and 95.6% for Kimi K2.7 Code.
  • GLM-4.7-Flash is cheaper at $0.06 / $0.40 per million input/output tokens, against $0.95 / $4 for Kimi K2.7 Code.
  • Kimi K2.7 Code accepts more context: 262K tokens versus 200K.

Side by side

GLM-4.7-Flash and Kimi K2.7 Code specifications
GLM-4.7-FlashKimi K2.7 Code
ProviderZ.ai (Zhipu)Moonshot AI
Noometry Index38.843.3
Released2026-01-192026-06-12
WeightsOpenOpen
Context window200K262K
Max output131K262K
Input $ / M tokens$0.06$0.95
Output $ / M tokens$0.40$4
Results tracked2119

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Category by category

Coding Kimi K2.7 Code leads

GLM-4.7-Flash: 40.6 (#135), Kimi K2.7 Code: 42.9 (#95)

Coding benchmarks
BenchmarkGLM-4.7-FlashKimi K2.7 Code
DeepSWE—30.5%
FrontierCode—30.1%
LMArena WebDev—1473
SciCode—47.5%
WeirdML—54.1%
LMArena Coding1383—
ALE-Bench—886.23

Agentic & Tool Use Not comparable

GLM-4.7-Flash: —, Kimi K2.7 Code: 24.0 (#122)

Agentic & Tool Use benchmarks
BenchmarkGLM-4.7-FlashKimi K2.7 Code
APEX-Agents—37.6%
GBAEval—0.9%
Vending-Bench 2—5,083

Reasoning Kimi K2.7 Code leads

GLM-4.7-Flash: 20.9 (#229), Kimi K2.7 Code: 39.0 (#61)

Reasoning benchmarks
BenchmarkGLM-4.7-FlashKimi K2.7 Code
Chess Puzzles0%21%
SimpleBench—57.9%
CritPt—10%
LMArena Hard Prompts1356—
Surface Evolver Bench—48.8%
Epoch Capabilities Index—149.97

Math Kimi K2.7 Code leads

GLM-4.7-Flash: 36.1 (#173), Kimi K2.7 Code: 52.9 (#48)

Math benchmarks
BenchmarkGLM-4.7-FlashKimi K2.7 Code
OTIS Mock AIME 2024-202558.3%95.6%
FrontierMath (Tiers 1-3)—54%
FrontierMath Tier 4—12.2%
LMArena Math1355—

Knowledge Kimi K2.7 Code leads

GLM-4.7-Flash: 35.5 (#184), Kimi K2.7 Code: 53.5 (#57)

Knowledge benchmarks
BenchmarkGLM-4.7-FlashKimi K2.7 Code
GPQA Diamond60.5%87.9%
SimpleQA Verified—36.5%
Vectara Hallucination Rate9.3%—
LMArena Expert1357—

Multilingual Not comparable

GLM-4.7-Flash: 46.5 (#158), Kimi K2.7 Code: —

Multilingual benchmarks
BenchmarkGLM-4.7-FlashKimi K2.7 Code
LMArena Non-English1330—
LMArena Chinese1403—
LMArena French1332—
LMArena German1337—
LMArena Korean1283—
LMArena Russian1332—
LMArena Spanish1350—

Instruction Following Not comparable

GLM-4.7-Flash: 70.1 (#167), Kimi K2.7 Code: —

Instruction Following benchmarks
BenchmarkGLM-4.7-FlashKimi K2.7 Code
LMArena Instruction Following1327—

Long Context Not comparable

GLM-4.7-Flash: 40.9 (#148), Kimi K2.7 Code: —

Long Context benchmarks
BenchmarkGLM-4.7-FlashKimi K2.7 Code
LMArena Longer Query1345—

Writing & Preference Not comparable

GLM-4.7-Flash: 47.4 (#210), Kimi K2.7 Code: —

Writing & Preference benchmarks
BenchmarkGLM-4.7-FlashKimi K2.7 Code
LMArena Text1351—
LMArena Creative Writing1297—
EQ-Bench Creative Writing1125—
LMArena Multi-Turn1342—

Frequently asked questions

Is GLM-4.7-Flash better than Kimi K2.7 Code?

Kimi K2.7 Code is the stronger model overall, scoring 43.3 to 38.8 on the Noometry Index. GLM-4.7-Flash costs 12× less per token, which makes it the better buy when Kimi K2.7 Code's lead doesn't matter for your workload.

Which is cheaper, GLM-4.7-Flash or Kimi K2.7 Code?

GLM-4.7-Flash is cheaper. It lists at $0.06 per million input tokens and $0.40 per million output tokens; Kimi K2.7 Code lists at $0.95 and $4.

Is GLM-4.7-Flash or Kimi K2.7 Code better for coding?

Kimi K2.7 Code scores higher on coding benchmarks: 42.9 versus 40.6 in the Noometry coding category.

Which has the bigger context window?

Kimi K2.7 Code does, with 262K tokens against 200K.

How many benchmarks do GLM-4.7-Flash and Kimi K2.7 Code share?

3 benchmarks have published results for both models. GLM-4.7-Flash has 21 scored results on Noometry and Kimi K2.7 Code has 19.

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