How do GPT-5.6 Sol and GLM-5.3-Flash 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 Sol and GLM-5.3-Flash when publicly disclosed.

LLM Comparison

GPT-5.6 Sol vs GLM-5.3-Flash: benchmark scores, pricing & comparison.

Q: Which is better: GPT-5.6 Sol or GLM-5.3-Flash?

AskClash compares GPT-5.6 Sol and GLM-5.3-Flash 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.

Side-by-side GPT-5.6 Sol vs GLM-5.3-Flash 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 Sol model page GLM-5.3-Flash model page

Rank #5 vs #7AskClash overall scores 75.7 vs 71.8.

Pricing $5.00/$30.0 vs $0.15/$0.50Input and output token prices per 1M tokens when published.

Proprietary vs Open WeightOpenAI vs Z.AI.

GPT-5.6 Sol vs GLM-5.3-Flash benchmark comparison

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

Metric	GPT-5.6 Sol	GLM-5.3-Flash
Overall Score	75.7	71.8
Leaderboard Rank	#5	#7
ACB	63.2	61.2
RWT	9.5	8.5
Coding Agent Index	80.0	—
HLE	47.2	55.3
GPQA	94.1	91.2
SWE-Pro	64.6	—
SWE-Atlas	84.0	—
Terminal-Bench	88.8	84.3
DeepSWE	72.7	63.4
GDPval-AA	1748.0	1773.0
Finance Agent	53.8	—
CharXiv	—	89.4
MMMU-Pro	83.0	—
ARC-AGI 2	92.5	—
Tau2	85.1	—
MRCR	91.5	—
Input Price (per 1M tokens)	$5.00	$0.15
Output Price (per 1M tokens)	$30.0	$0.50
Context Window	1M	1M
Benchmarks Published	15	8

GPT-5.6 Sol vs GLM-5.3-Flash head-to-head charts

GPT-5.6 Sol leads 6 and GLM-5.3-Flash leads 2 of 8 shared benchmarks. GLM-5.3-Flash is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

GPT-5.6 SolGLM-5.3-Flash

Overall

75.7GPT-5.6 Sol

71.8GLM-5.3-Flash

ACB

63.2GPT-5.6 Sol

61.2GLM-5.3-Flash

RWT

9.5GPT-5.6 Sol

8.5GLM-5.3-Flash

HLE

47.2GPT-5.6 Sol

55.3GLM-5.3-Flash

GPQA

94.1GPT-5.6 Sol

91.2GLM-5.3-Flash

Terminal-Bench

88.8GPT-5.6 Sol

84.3GLM-5.3-Flash

DeepSWE

72.7GPT-5.6 Sol

63.4GLM-5.3-Flash

GDPval-AA

1748.0GPT-5.6 Sol

1773.0GLM-5.3-Flash

GPT-5.6 Sol

Input$5.00

Output$30.0

Workload$11

Context1M

GLM-5.3-Flash

Input$0.15

Output$0.50

Workload$0.25

Context1M

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

More GPT-5.6 Sol and GLM-5.3-Flash comparisons

Explore how GPT-5.6 Sol and GLM-5.3-Flash stack up against other top-ranked LLMs.

Claude Opus 5 vs GPT-5.6 Sol Claude Opus 5 vs GLM-5.3-Flash Claude Fable 5 vs GPT-5.6 Sol Claude Fable 5 vs GLM-5.3-Flash GLM-5.3 vs GPT-5.6 Sol GLM-5.3 vs GLM-5.3-Flash Grok 4.6 vs GPT-5.6 Sol Grok 4.6 vs GLM-5.3-Flash GPT-5.6 Sol vs Kimi K3 Kimi K3 vs GLM-5.3-Flash

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.