GLM-5.2 vs Qwen3.7-Plus
GLM-5.2 leads the LLM Stats Score 46.5 to 43.3. Qwen3.7-Plus is 2.6x cheaper per token.
Zhipu AI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
GLM-5.2 leads the overall LLM Stats Score 46.5 to 43.3, ranking #22 overall.
In the 9 individual benchmarks reported for both models, GLM-5.2 wins 8; this is a narrower head-to-head signal than the composite indexes.
On price, Qwen3.7-Plus is roughly 2.6x 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.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose GLM-5.2
- overall performance matters — it scores 46.5 and ranks #22 on LLM Stats
- your work emphasizes agents — it leads those capability indexes
- you value its reported benchmark strengths — it wins 8 of 9 exact shared results
- 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-Plus
- cost matters — it's about 2.6x cheaper per token
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
19 reported for GLM-5.2 · 70 for Qwen3.7-Plus
GLM-5.2 outperforms in 8 benchmarks (CritPT, FrontierCode 1.1, GPQA, Humanity's Last Exam, IMO-AnswerBench, MCP Atlas, NL2Repo, SWE-Bench Pro), while Qwen3.7-Plus is better at 1 benchmark (HMMT Feb 26).
GLM-5.2 significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GLM-5.2 ($0.95/1M tokens) is 3.0x more expensive than Qwen3.7-Plus ($0.32/1M tokens).
For output processing, GLM-5.2 ($3.00/1M tokens) is 2.3x more expensive than Qwen3.7-Plus ($1.28/1M tokens).
In conclusion, GLM-5.2 is more expensive than Qwen3.7-Plus.*
* 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-Plus's 1,000,000 tokens. GLM-5.2 can generate longer responses up to 131,072 tokens, while Qwen3.7-Plus is limited to 65,536 tokens.
Input capabilities
Documented input modalities across available providers
Qwen3.7-Plus supports multimodal inputs, whereas GLM-5.2 does not.
Qwen3.7-Plus can handle both text and other forms of data like images, making it suitable for multimodal applications.
GLM-5.2
Qwen3.7-Plus
License
Usage and distribution terms
GLM-5.2 is licensed under MIT, while Qwen3.7-Plus 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-Plus was released on 2026-05-31.
GLM-5.2 is 1 month newer than Qwen3.7-Plus.
Jun 16, 2026
2 months ago
2w newerMay 31, 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-Plus is available from Together, Fireworks.
GLM-5.2
Qwen3.7-Plus
Outputs Comparison
Judge for yourself.
Run your own prompts against GLM-5.2 and Qwen3.7-Plus side-by-side, then vote on the output you prefer.
FAQ
Common questions about GLM-5.2 vs Qwen3.7-Plus.