Which is better: GPT-5.5 or GLM-5.2?

Verdict: GPT-5.5 ranks higher (#28 vs #30); GLM-5.2 wins 6 of 10 shared benchmarks; GLM-5.2 costs less ($1.40/$4.40 vs $5.00/$30.0 per 1M tokens). AskClash compares GPT-5.5 and GLM-5.2 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 GPT-5.5 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-5.5 and GLM-5.2 when publicly disclosed.

LLM Comparison

GPT-5.5 vs GLM-5.2: benchmark scores, pricing & comparison.

Side-by-side GPT-5.5 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.

Verdict: GPT-5.5 ranks higher (#28 vs #30); GLM-5.2 wins 6 of 10 shared benchmarks; GLM-5.2 costs less ($1.40/$4.40 vs $5.00/$30.0 per 1M tokens).

Open live leaderboard GPT-5.5 model page GLM-5.2 model page

Rank #28 vs #30AskClash overall scores 54.5 vs 52.8.

Pricing $5.00/$30.0 vs $1.40/$4.40Input and output token prices per 1M tokens when published.

Proprietary vs Open WeightOpenAI vs Z.AI.

GPT-5.5 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-5.5	GLM-5.2
Overall Score	54.5	52.8
Leaderboard Rank	#28	#30
ACB	62.0	—
RWT	8.0	8.5
Coding Agent Index	—	74.4
HLE	52.2	54.7
GPQA	93.6	91.2
IFEval	75.9	73.3
SWE-Pro	58.6	62.1
SWE-Atlas	—	74.4
Terminal-Bench	14.7	—
DeepSWE	67.0	43.8
GDPval-AA	1353.2	1373.9
OSWorld	78.7	—
MCP Atlas	75.3	76.8
Finance Agent	51.8	49.7
MMMU-Pro	81.2	—
ARC-AGI 2	85.0	—
Tau2	98.0	99.1
Input Price (per 1M tokens)	$5.00	$1.40
Output Price (per 1M tokens)	$30.0	$4.40
Context Window	1M	1M
Benchmarks Published	14	12

GPT-5.5 vs GLM-5.2 head-to-head charts

GPT-5.5 leads 5 and GLM-5.2 leads 6 of 11 shared benchmarks. GLM-5.2 is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

GPT-5.5GLM-5.2

Overall

54.5GPT-5.5

52.8GLM-5.2

RWT

8.0GPT-5.5

8.5GLM-5.2

HLE

52.2GPT-5.5

54.7GLM-5.2

GPQA

93.6GPT-5.5

91.2GLM-5.2

IFEval

75.9GPT-5.5

73.3GLM-5.2

SWE-Pro

58.6GPT-5.5

62.1GLM-5.2

DeepSWE

67.0GPT-5.5

43.8GLM-5.2

GDPval-AA

1353.2GPT-5.5

1373.9GLM-5.2

MCP Atlas

75.3GPT-5.5

76.8GLM-5.2

Finance Agent

51.8GPT-5.5

49.7GLM-5.2

Tau2

98.0GPT-5.5

99.1GLM-5.2

GPT-5.5

Input$5.00

Output$30.0

Workload$11

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-5.5 and GLM-5.2 comparisons

Explore how GPT-5.5 and GLM-5.2 stack up against other top-ranked LLMs.

Claude Opus 5.5 vs GPT-5.5 Claude Opus 5.5 vs GLM-5.2 Claude Fable 5.1 vs GPT-5.5 Claude Fable 5.1 vs GLM-5.2 Claude Opus 5 vs GPT-5.5 Claude Opus 5 vs GLM-5.2 Claude Sonnet 5.5 vs GPT-5.5 Claude Sonnet 5.5 vs GLM-5.2 Claude Fable 5 vs GPT-5.5 Claude Fable 5 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.