Model Comparison
GLM-4.7 vs Qwen3 MaxWhich is better in 2026?
GLM-4.7 significantly outperforms across most benchmarks. GLM-4.7 is 1.6x cheaper per token.
Verdict: GLM-4.7 vs Qwen3 Max — which is better?
GLM-4.7 (by Zhipu AI) and Qwen3 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-4.7 outperforms in 4 benchmarks (AIME 2025, GPQA, LiveCodeBench v6, SWE-Bench Verified), while Qwen3 Max is better at 0 benchmarks. GLM-4.7 significantly outperforms across most benchmarks.
On price, GLM-4.7 is roughly 1.6x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Qwen3 Max also accepts a larger context window (256,000 input tokens), making it the stronger choice for long documents and large codebases.
Choose GLM-4.7 if…
- you want the strongest raw capability — it leads on 4 of 4 shared benchmarks
- cost matters — it's about 1.6x cheaper per token
- you want the most recent training data — it shipped Dec 2025
- you need open weights you can self-host or fine-tune
Choose Qwen3 Max if…
- you process long inputs — it offers a 256,000 token context window
Performance Benchmarks
Comparative analysis across standard metrics
GLM-4.7 outperforms in 4 benchmarks (AIME 2025, GPQA, LiveCodeBench v6, SWE-Bench Verified), while Qwen3 Max is better at 0 benchmarks.
GLM-4.7 significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, GLM-4.7 ($0.60/1M tokens) is 1.2x more expensive than Qwen3 Max ($0.50/1M tokens).
For output processing, GLM-4.7 ($2.20/1M tokens) is 2.3x cheaper than Qwen3 Max ($5.00/1M tokens).
In conclusion, Qwen3 Max is more expensive than GLM-4.7.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Qwen3 Max has 642.0B more parameters than GLM-4.7, making it 179.3% larger.
Context Window
Maximum input and output token capacity
Qwen3 Max accepts 256,000 input tokens compared to GLM-4.7's 202,800 tokens. Both models can generate responses up to 131,072 tokens.
Input Capabilities
Supported data types and modalities
GLM-4.7 supports multimodal inputs, whereas Qwen3 Max does not.
GLM-4.7 can handle both text and other forms of data like images, making it suitable for multimodal applications.
GLM-4.7
Qwen3 Max
License
Usage and distribution terms
GLM-4.7 is licensed under MIT, while Qwen3 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-4.7 was released on 2025-12-22, while Qwen3 Max was released on 2025-12-15.
GLM-4.7 is 0 month newer than Qwen3 Max.
Dec 22, 2025
6 months ago
1w newerDec 15, 2025
7 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-4.7 is available from Fireworks, Novita. Qwen3 Max is available from Novita.
GLM-4.7
Qwen3 Max
Outputs Comparison
Key Takeaways
GLM-4.7
View detailsZhipu AI
Qwen3 Max
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against GLM-4.7 and Qwen3 Max side-by-side, then vote on the output you prefer.
FAQ
Common questions about GLM-4.7 vs Qwen3 Max.