Model Comparison
GLM-5.2 vs Qwen3.7 MaxWhich is better in 2026?
GLM-5.2 shows notably better performance in the majority of benchmarks. GLM-5.2 is 1.3x cheaper per token.
Verdict: GLM-5.2 vs Qwen3.7 Max — which is better?
GLM-5.2 (by Zhipu AI) and Qwen3.7 Max (by Alibaba Cloud / Qwen Team) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
GLM-5.2 outperforms in 6 benchmarks (CritPT, Humanity's Last Exam, IMO-AnswerBench, MCP Atlas, NL2Repo, SWE-Bench Pro), while Qwen3.7 Max is better at 2 benchmarks (GPQA, HMMT Feb 26). GLM-5.2 shows notably better performance in the majority of benchmarks.
On price, GLM-5.2 is roughly 1.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GLM-5.2 also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Choose GLM-5.2 if…
- you want the strongest raw capability — it leads on 6 of 8 shared benchmarks
- cost matters — it's about 1.3x cheaper per token
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Jun 2026
- you need open weights you can self-host or fine-tune
Choose Qwen3.7 Max if…
- you want predictable pricing at $1.25/M input and $3.75/M output
Performance Benchmarks
Comparative analysis across standard metrics
GLM-5.2 outperforms in 6 benchmarks (CritPT, Humanity's Last Exam, IMO-AnswerBench, MCP Atlas, NL2Repo, SWE-Bench Pro), while Qwen3.7 Max is better at 2 benchmarks (GPQA, HMMT Feb 26).
GLM-5.2 shows notably better performance in the majority of benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, GLM-5.2 ($0.95/1M tokens) is 1.3x cheaper than Qwen3.7 Max ($1.25/1M tokens).
For output processing, GLM-5.2 ($3.00/1M tokens) is 1.3x cheaper than Qwen3.7 Max ($3.75/1M tokens).
In conclusion, Qwen3.7 Max is more expensive than GLM-5.2.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GLM-5.2 accepts 1,048,576 input tokens compared to Qwen3.7 Max's 1,000,000 tokens. GLM-5.2 can generate longer responses up to 131,072 tokens, while Qwen3.7 Max is limited to 65,536 tokens.
License
Usage and distribution terms
GLM-5.2 is licensed under MIT, while Qwen3.7 Max uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
GLM-5.2 was released on 2026-06-16, while Qwen3.7 Max was released on 2026-05-19.
GLM-5.2 is 1 month newer than Qwen3.7 Max.
Jun 16, 2026
1 months ago
4w newerMay 19, 2026
2 months ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
GLM-5.2 is available from DeepInfra, Fireworks, FriendliAI, Novita, Together, ZAI. Qwen3.7 Max is available from Novita, Together.
GLM-5.2
Qwen3.7 Max
Outputs Comparison
Key Takeaways
GLM-5.2
View detailsZhipu AI
Qwen3.7 Max
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against GLM-5.2 and Qwen3.7 Max side-by-side, then vote on the output you prefer.
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FAQ
Common questions about GLM-5.2 vs Qwen3.7 Max.