How do GLM-5.3-Flash and Qwen3.7 Plus 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-Flash and Qwen3.7 Plus when publicly disclosed.

LLM Comparison

GLM-5.3-Flash vs Qwen3.7 Plus: benchmark scores, pricing & comparison.

Q: Which is better: GLM-5.3-Flash or Qwen3.7 Plus?

AskClash compares GLM-5.3-Flash and Qwen3.7 Plus 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 GLM-5.3-Flash vs Qwen3.7 Plus 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 GLM-5.3-Flash model page Qwen3.7 Plus model page

Rank #7 vs #35AskClash overall scores 71.8 vs 33.4.

Pricing $0.15/$0.50 vs $0.40/$1.60Input and output token prices per 1M tokens when published.

Open Weight vs ProprietaryZ.AI vs Alibaba.

GLM-5.3-Flash vs Qwen3.7 Plus benchmark comparison

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

Metric	GLM-5.3-Flash	Qwen3.7 Plus
Overall Score	71.8	33.4
Leaderboard Rank	#7	#35
ACB	61.2	—
RWT	8.5	7.5
HLE	55.3	34.7
GPQA	91.2	90.3
IFEval	—	94.6
SWE-bench	—	77.7
SWE-Pro	—	57.6
Terminal-Bench	84.3	70.3
DeepSWE	63.4	—
GDPval-AA	1773.0	1522.1
OSWorld	—	73.3
MCP Atlas	—	73.2
Finance Agent	—	38.2
CharXiv	89.4	85.9
MMMU-Pro	—	79.0
Tau2	—	93.0
MRCR	—	91.7
Input Price (per 1M tokens)	$0.15	$0.40
Output Price (per 1M tokens)	$0.50	$1.60
Context Window	1M	1M
Benchmarks Published	8	15

GLM-5.3-Flash vs Qwen3.7 Plus head-to-head charts

GLM-5.3-Flash leads 7 and Qwen3.7 Plus leads 0 of 7 shared benchmarks. GLM-5.3-Flash is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

GLM-5.3-FlashQwen3.7 Plus

Overall

71.8GLM-5.3-Flash

33.4Qwen3.7 Plus

RWT

8.5GLM-5.3-Flash

7.5Qwen3.7 Plus

HLE

55.3GLM-5.3-Flash

34.7Qwen3.7 Plus

GPQA

91.2GLM-5.3-Flash

90.3Qwen3.7 Plus

Terminal-Bench

84.3GLM-5.3-Flash

70.3Qwen3.7 Plus

GDPval-AA

1773.0GLM-5.3-Flash

1522.1Qwen3.7 Plus

CharXiv

89.4GLM-5.3-Flash

85.9Qwen3.7 Plus

GLM-5.3-Flash

Input$0.15

Output$0.50

Workload$0.25

Context1M

Qwen3.7 Plus

Input$0.40

Output$1.60

Workload$0.72

Context1M

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

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Claude Opus 5 vs GLM-5.3-Flash Claude Opus 5 vs Qwen3.7 Plus Claude Fable 5 vs GLM-5.3-Flash Claude Fable 5 vs Qwen3.7 Plus GLM-5.3 vs GLM-5.3-Flash GLM-5.3 vs Qwen3.7 Plus Grok 4.6 vs GLM-5.3-Flash Grok 4.6 vs Qwen3.7 Plus GPT-5.6 Sol vs GLM-5.3-Flash GPT-5.6 Sol vs Qwen3.7 Plus

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.