GLM-5.3-Flash vs Qwen3.7 Max
GLM-5.3-Flash significantly outperforms across most benchmarks. GLM-5.3-Flash is 7.9x cheaper per token.
Zhipu AI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
GLM-5.3-Flash outperforms in 2 benchmarks (Humanity's Last Exam, NL2Repo), while Qwen3.7 Max is better at 0 benchmarks. GLM-5.3-Flash significantly outperforms across most benchmarks.
On price, GLM-5.3-Flash is roughly 7.9x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GLM-5.3-Flash 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 benchmark, pricing, and model metadata for 2026.
Choose GLM-5.3-Flash
- you want the strongest raw capability — it leads on 2 of 2 shared benchmarks
- cost matters — it's about 7.9x 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 Aug 2026
- you need open weights you can self-host or fine-tune
Choose Qwen3.7 Max
- you want predictable pricing at $1.25/M input and $3.75/M output
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
GLM-5.3-Flash outperforms in 2 benchmarks (Humanity's Last Exam, NL2Repo), while Qwen3.7 Max is better at 0 benchmarks.
GLM-5.3-Flash significantly outperforms across most benchmarks.
Arena Performance
Playground indexes and blind preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GLM-5.3-Flash ($0.15/1M tokens) is 8.3x cheaper than Qwen3.7 Max ($1.25/1M tokens).
For output processing, GLM-5.3-Flash ($0.50/1M tokens) is 7.5x cheaper than Qwen3.7 Max ($3.75/1M tokens).
In conclusion, Qwen3.7 Max is more expensive than GLM-5.3-Flash.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GLM-5.3-Flash accepts 1,048,576 input tokens compared to Qwen3.7 Max's 1,000,000 tokens. GLM-5.3-Flash can generate longer responses up to 131,072 tokens, while Qwen3.7 Max is limited to 65,536 tokens.
Input Capabilities
Supported data types and modalities
GLM-5.3-Flash supports multimodal inputs, whereas Qwen3.7 Max does not.
GLM-5.3-Flash can handle both text and other forms of data like images, making it suitable for multimodal applications.
GLM-5.3-Flash
Qwen3.7 Max
License
Usage and distribution terms
GLM-5.3-Flash 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-5.3-Flash was released on 2026-08-26, while Qwen3.7 Max was released on 2026-05-19.
GLM-5.3-Flash is 3 months newer than Qwen3.7 Max.
Aug 26, 2026
0 days ago
3mo newerMay 19, 2026
3 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-5.3-Flash is available from DeepInfra, Novita, ZAI. Qwen3.7 Max is available from Novita, Together.
GLM-5.3-Flash
Qwen3.7 Max
Outputs Comparison
Judge for yourself.
Run your own prompts against GLM-5.3-Flash and Qwen3.7 Max side-by-side, then vote on the output you prefer.
FAQ
Common questions about GLM-5.3-Flash vs Qwen3.7 Max.