LLM Comparison

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

Side-by-side GLM-5.3-Flash vs Qwen3.7 Max 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 #7 vs #22AskClash overall scores 71.8 vs 49.3.
Pricing $0.15/$0.50 vs $2.50/$7.50Input and output token prices per 1M tokens when published.
Open Weight vs ProprietaryZ.AI vs Alibaba.

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

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

MetricGLM-5.3-FlashQwen3.7 Max
Overall Score71.849.3
Leaderboard Rank#7#22
ACB61.2
RWT8.57.5
HLE55.341.4
GPQA91.292.4
IFEval94.3
SWE-bench80.4
Terminal-Bench84.369.7
DeepSWE63.4
GDPval-AA1773.01546.0
MCP Atlas76.4
Finance Agent48.4
CharXiv89.4
Tau294.7
MRCR90.4
Input Price (per 1M tokens)$0.15$2.50
Output Price (per 1M tokens)$0.50$7.50
Context Window1M1M
Benchmarks Published811

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

GLM-5.3-Flash leads 5 and Qwen3.7 Max leads 1 of 6 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 Max
Overall
71.8GLM-5.3-Flash
49.3Qwen3.7 Max
RWT
8.5GLM-5.3-Flash
7.5Qwen3.7 Max
HLE
55.3GLM-5.3-Flash
41.4Qwen3.7 Max
GPQA
91.2GLM-5.3-Flash
92.4Qwen3.7 Max
Terminal-Bench
84.3GLM-5.3-Flash
69.7Qwen3.7 Max
GDPval-AA
1773.0GLM-5.3-Flash
1546.0Qwen3.7 Max
GLM-5.3-Flash
Input$0.15
Output$0.50
Workload$0.25
Context1M
Qwen3.7 Max
Input$2.50
Output$7.50
Workload$4.00
Context1M

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

More GLM-5.3-Flash and Qwen3.7 Max comparisons

Explore how GLM-5.3-Flash and Qwen3.7 Max 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.