AI model matchup
GLM-5.2 vs Qwen3.7 Max
A side-by-side look at published capability scores, listed API pricing, speed, context, and license - to help you decide which trade-offs fit your work.
GLM-5.2vsQwen3.7 Max
Qwen3.7 Max leads the RankLLMs Index by 0.2 points (48.4 vs 48.2). Verified API Pricing: Free/Open Source (GLM-5.2) vs $2.50 (Qwen3.7 Max) per 1M tokens.
Capability profile
Speed duel
tpsPrice duel
$/1MShorter bar = cheaper. Blended per 1M tokens.
| Metric | GLM-5.2 | Qwen3.7 Max |
|---|---|---|
| RankLLMs Overall Score | 48.2 pts | 48.4 pts ▲ |
| Reasoning | 54.7 ▲ | 50.2 |
| Coding | 46.2 | 65.4 ▲ |
| Agentic Tool Use | 26.2 | 38.0 ▲ |
| Code Arena Elo | 1508 | 1538 ▲ |
| Inference Speed | 126 tps ▲ | 32 tps |
| API Price (per 1M tokens) | Free/Open Source | $2.50 |
| Context Window | 1M | 1M |
| License | Open Source | Proprietary |
| Global Rank | #42 | #41 ▲ |
Decision notes
What the numbers suggest
Qwen3.7 Max leads the RankLLMs overall score by 0.2 points. GLM-5.2 has the lower listed API rate (Free/Open Source per 1M tokens).
Treat the overall index as a starting point, then prioritize the benchmark that resembles your task. Published scores and provider pricing can change; this comparison does not represent a first-party test of either model.
- Overall index
- Qwen3.7 Max leads
- 48.2 to 48.4 pts
- Coding score
- Qwen3.7 Max leads
- 46.2 to 65.4 pts
- Reasoning score
- GLM-5.2 leads
- 54.7 to 50.2 pts
- Agentic score
- Qwen3.7 Max leads
- 26.2 to 38.0 pts
Choose by workload
Which profile fits your use?
Zhipu AI
Consider GLM-5.2 when
your workload gives more weight to the higher listed reasoning score, the lower listed API rate. Compare those signals with your own task mix, latency needs, and budget.
View GLM-5.2 profileQwen / Alibaba
Consider Qwen3.7 Max when
your workload gives more weight to the higher listed coding score, the higher overall index score. Compare those signals with your own task mix, latency needs, and budget.
View Qwen3.7 Max profile