How do GPT-5.6 Luna and GLM-5.2 compare on coding benchmarks?

The comparison table shows SWE-bench, SWE-Pro, SWE-Atlas, Terminal-Bench, DeepSWE, and coding agent index scores for both GPT-5.6 Luna and GLM-5.2 when publicly disclosed.

LLM Comparison

GPT-5.6 Luna vs GLM-5.2: benchmark scores, pricing & comparison.

Q: Which is better: GPT-5.6 Luna or GLM-5.2?

AskClash compares GPT-5.6 Luna and GLM-5.2 side by side across SWE-bench, GPQA, HLE, Terminal-Bench, coding agent scores, token pricing, and context window so you can see which model wins on each benchmark.

Side-by-side GPT-5.6 Luna vs GLM-5.2 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.

Open live leaderboard GPT-5.6 Luna model page GLM-5.2 model page

Rank #12 vs #17AskClash overall scores 66.2 vs 54.8.

Pricing $1.00/$6.00 vs $1.40/$4.40Input and output token prices per 1M tokens when published.

Proprietary vs Open WeightOpenAI vs Z.AI.

GPT-5.6 Luna vs GLM-5.2 benchmark comparison

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

Metric	GPT-5.6 Luna	GLM-5.2
Overall Score	66.2	54.8
Leaderboard Rank	#12	#17
RWT	9.5	8.5
Coding Agent Index	75.0	74.4
HLE	—	54.7
GPQA	92.3	91.2
IFEval	—	73.3
SWE-Pro	62.7	62.1
SWE-Atlas	81.0	74.4
Terminal-Bench	84.7	82.7
DeepSWE	67.2	43.8
MCP Atlas	—	76.8
Finance Agent	55.0	—
MMMU-Pro	78.4	—
ARC-AGI 2	59.5	—
Tau2	—	99.1
MRCR	41.3	—
Input Price (per 1M tokens)	$1.00	$1.40
Output Price (per 1M tokens)	$6.00	$4.40
Context Window	1M	1M
Benchmarks Published	13	11

GPT-5.6 Luna vs GLM-5.2 head-to-head charts

GPT-5.6 Luna leads 8 and GLM-5.2 leads 0 of 8 shared benchmarks. GPT-5.6 Luna is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

GPT-5.6 LunaGLM-5.2

Overall

66.2GPT-5.6 Luna

54.8GLM-5.2

RWT

9.5GPT-5.6 Luna

8.5GLM-5.2

Coding Agent Index

75.0GPT-5.6 Luna

74.4GLM-5.2

GPQA

92.3GPT-5.6 Luna

91.2GLM-5.2

SWE-Pro

62.7GPT-5.6 Luna

62.1GLM-5.2

SWE-Atlas

81.0GPT-5.6 Luna

74.4GLM-5.2

Terminal-Bench

84.7GPT-5.6 Luna

82.7GLM-5.2

DeepSWE

67.2GPT-5.6 Luna

43.8GLM-5.2

GPT-5.6 Luna

Input$1.00

Output$6.00

Workload$2.20

Context1M

GLM-5.2

Input$1.40

Output$4.40

Workload$2.28

Context1M

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

More GPT-5.6 Luna and GLM-5.2 comparisons

Explore how GPT-5.6 Luna and GLM-5.2 stack up against other top-ranked LLMs.

Claude Opus 5 vs GPT-5.6 Luna Claude Opus 5 vs GLM-5.2 Claude Fable 5 vs GPT-5.6 Luna Claude Fable 5 vs GLM-5.2 GPT-5.6 Sol vs GPT-5.6 Luna GPT-5.6 Sol vs GLM-5.2 Kimi K3 vs GPT-5.6 Luna Kimi K3 vs GLM-5.2 Claude Opus 4.8 vs GPT-5.6 Luna Claude Opus 4.8 vs GLM-5.2

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.