LLM Comparison

GLM-5.2 vs Kimi K2.7: benchmark scores, pricing & comparison.

Side-by-side GLM-5.2 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.

Rank #11 vs #19AskClash overall scores 70.8 vs 56.8.
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-5.2 vs Kimi K2.7 benchmark comparison

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

MetricGLM-5.2Kimi K2.7
Overall Score70.856.8
Leaderboard Rank#11#19
RWT8.57.5
Coding Agent Index74.4
HLE54.754.0
GPQA91.290.5
IFEval73.3
SWE-bench80.2
SWE-Pro62.158.6
SWE-Atlas74.4
Terminal-Bench82.766.7
DeepSWE43.830.5
OSWorld73.1
MCP Atlas76.876.0
Finance Agent44.9
CharXiv80.4
MMMU-Pro79.4
Tau299.190.1
Input Price (per 1M tokens)$1.40$0.95
Output Price (per 1M tokens)$4.40$4.00
Context Window1M256K
Benchmarks Published1113

GLM-5.2 vs Kimi K2.7 head-to-head charts

GLM-5.2 leads 9 and Kimi K2.7 leads 0 of 9 shared benchmarks. Kimi K2.7 is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

GLM-5.2Kimi K2.7
Overall
70.8GLM-5.2
56.8Kimi K2.7
RWT
8.5GLM-5.2
7.5Kimi K2.7
HLE
54.7GLM-5.2
54.0Kimi K2.7
GPQA
91.2GLM-5.2
90.5Kimi K2.7
SWE-Pro
62.1GLM-5.2
58.6Kimi K2.7
Terminal-Bench
82.7GLM-5.2
66.7Kimi K2.7
DeepSWE
43.8GLM-5.2
30.5Kimi K2.7
MCP Atlas
76.8GLM-5.2
76.0Kimi K2.7
Tau2
99.1GLM-5.2
90.1Kimi K2.7
GLM-5.2
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-5.2 and Kimi K2.7 comparisons

Explore how GLM-5.2 and Kimi K2.7 stack up against other top-ranked LLMs.

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.