Which is better: GLM-5.3 or Kimi K2.7?

Verdict: GLM-5.3 ranks higher (#13 vs #50) and wins 7 of 7 shared benchmarks; Kimi K2.7 costs less ($0.95/$4.00 vs $1.40/$4.40 per 1M tokens). AskClash compares GLM-5.3 and Kimi K2.7 side by side across SWE-bench, GPQA, HLE, Terminal-Bench, coding agent scores, token pricing, AskClash ACB, and context window so you can see which model wins on each benchmark.

How do GLM-5.3 and Kimi K2.7 compare on coding benchmarks?

The comparison table shows SWE-bench, SWE-Pro, SWE-Atlas, Terminal-Bench, DeepSWE, and coding agent index scores for both GLM-5.3 and Kimi K2.7 when publicly disclosed.

LLM Comparison

GLM-5.3 vs Kimi K2.7: benchmark scores, pricing & comparison.

Side-by-side GLM-5.3 vs Kimi K2.7 comparison across SWE-bench, GPQA, HLE, Terminal-Bench, coding agent scores, token pricing, context window, and AskClash RWT. Green marks the winner on each benchmark.

Verdict: GLM-5.3 ranks higher (#13 vs #50) and wins 7 of 7 shared benchmarks; Kimi K2.7 costs less ($0.95/$4.00 vs $1.40/$4.40 per 1M tokens).

Open live leaderboard GLM-5.3 model page Kimi K2.7 model page

Rank #13 vs #50AskClash overall scores 66.4 vs 38.1.

Pricing $1.40/$4.40 vs $0.95/$4.00Input and output token prices per 1M tokens when published.

Open Weight vs Open WeightZ.AI vs Moonshot AI.

GLM-5.3 vs Kimi K2.7 benchmark comparison

Green cells highlight the winning model for each metric. Scores are cached from the AskClash LLM leaderboard snapshot.

Metric	GLM-5.3	Kimi K2.7
Overall Score	66.4	38.1
Leaderboard Rank	#13	#50
ACB	62.2	43.0
RWT	8.5	7.5
HLE	62.5	35.0
GPQA	91.7	89.6
IFEval	—	63.1
Terminal-Bench	88.2	44.7
DeepSWE	69.0	30.5
GDPval-AA	1769.0	1025.0
MCP Atlas	—	76.0
Finance Agent	55.8	—
Tau2	—	90.1
Input Price (per 1M tokens)	$1.40	$0.95
Output Price (per 1M tokens)	$4.40	$4.00
Context Window	1M	256K
Benchmarks Published	10	10

GLM-5.3 vs Kimi K2.7 head-to-head charts

GLM-5.3 leads 8 and Kimi K2.7 leads 0 of 8 shared benchmarks. Kimi K2.7 is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

GLM-5.3Kimi K2.7

Overall

66.4GLM-5.3

38.1Kimi K2.7

ACB

62.2GLM-5.3

43.0Kimi K2.7

RWT

8.5GLM-5.3

7.5Kimi K2.7

HLE

62.5GLM-5.3

35.0Kimi K2.7

GPQA

91.7GLM-5.3

89.6Kimi K2.7

Terminal-Bench

88.2GLM-5.3

44.7Kimi K2.7

DeepSWE

69.0GLM-5.3

30.5Kimi K2.7

GDPval-AA

1769.0GLM-5.3

1025.0Kimi K2.7

GLM-5.3

Input$1.40

Output$4.40

Workload$2.28

Context1M

Kimi K2.7

Input$0.95

Output$4.00

Workload$1.75

Context256K

Workload = published cost of 1M input + 200K output tokens. Open the live leaderboard for interactive compare charts.

More GLM-5.3 and Kimi K2.7 comparisons

Explore how GLM-5.3 and Kimi K2.7 stack up against other top-ranked LLMs.

Claude Fable 5.1 vs GLM-5.3 Claude Fable 5.1 vs Kimi K2.7 Claude Opus 5.5 vs GLM-5.3 Claude Opus 5.5 vs Kimi K2.7 Claude Fable 5 vs GLM-5.3 Claude Fable 5 vs Kimi K2.7 Claude Opus 5 vs GLM-5.3 Claude Opus 5 vs Kimi K2.7 GPT-5.6 Sol vs GLM-5.3 GPT-5.6 Sol vs Kimi K2.7

How to read this comparison

Benchmark scores

Higher is better for all benchmark scores (SWE-bench, GPQA, HLE, Terminal-Bench, etc.). Green marks the model with the higher score.

Token pricing

Lower is better for input and output prices. Green marks the cheaper model per 1M tokens.

Coverage matters

Models with fewer disclosed benchmark cells may have inflated percentile scores. Check the benchmark cell count for context.

This comparison page is generated from the AskClash LLM leaderboard cache. Open the live leaderboard for real-time scores and interactive filtering.