Model Comparison
GLM-5.2 vs Qwen3.5-397B-A17BWhich is better in 2026?
GLM-5.2 significantly outperforms across most benchmarks. Qwen3.5-397B-A17B is 1.1x cheaper per token.
Verdict: GLM-5.2 vs Qwen3.5-397B-A17B — which is better?
GLM-5.2 (by Zhipu AI) and Qwen3.5-397B-A17B (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 5 benchmarks (AIME 2026, GPQA, Humanity's Last Exam, IMO-AnswerBench, Toolathlon), while Qwen3.5-397B-A17B is better at 1 benchmark (HMMT 2025). GLM-5.2 significantly outperforms across most benchmarks.
On price, Qwen3.5-397B-A17B is roughly 1.1x 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 5 of 6 shared benchmarks
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Jun 2026
Choose Qwen3.5-397B-A17B if…
- cost matters — it's about 1.1x cheaper per token
Performance Benchmarks
Comparative analysis across standard metrics
GLM-5.2 outperforms in 5 benchmarks (AIME 2026, GPQA, Humanity's Last Exam, IMO-AnswerBench, Toolathlon), while Qwen3.5-397B-A17B is better at 1 benchmark (HMMT 2025).
GLM-5.2 significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, GLM-5.2 ($0.95/1M tokens) is 1.6x more expensive than Qwen3.5-397B-A17B ($0.60/1M tokens).
For output processing, GLM-5.2 ($3.00/1M tokens) is 1.2x cheaper than Qwen3.5-397B-A17B ($3.60/1M tokens).
In conclusion, GLM-5.2 is more expensive than Qwen3.5-397B-A17B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
GLM-5.2 has 356.0B more parameters than Qwen3.5-397B-A17B, making it 89.7% larger.
Context Window
Maximum input and output token capacity
GLM-5.2 accepts 1,048,576 input tokens compared to Qwen3.5-397B-A17B's 262,144 tokens. GLM-5.2 can generate longer responses up to 131,072 tokens, while Qwen3.5-397B-A17B is limited to 64,000 tokens.
Input Capabilities
Supported data types and modalities
Qwen3.5-397B-A17B supports multimodal inputs, whereas GLM-5.2 does not.
Qwen3.5-397B-A17B can handle both text and other forms of data like images, making it suitable for multimodal applications.
GLM-5.2
Qwen3.5-397B-A17B
License
Usage and distribution terms
GLM-5.2 is licensed under MIT, while Qwen3.5-397B-A17B uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
GLM-5.2 was released on 2026-06-16, while Qwen3.5-397B-A17B was released on 2026-02-16.
GLM-5.2 is 4 months newer than Qwen3.5-397B-A17B.
Jun 16, 2026
1 months ago
4mo newerFeb 16, 2026
5 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. Qwen3.5-397B-A17B is available from Novita.
GLM-5.2
Qwen3.5-397B-A17B
Outputs Comparison
Key Takeaways
GLM-5.2
View detailsZhipu AI
Qwen3.5-397B-A17B
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against GLM-5.2 and Qwen3.5-397B-A17B side-by-side, then vote on the output you prefer.
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FAQ
Common questions about GLM-5.2 vs Qwen3.5-397B-A17B.