GLM-4.7 vs Qwen3-Coder
Comparing GLM-4.7 and Qwen3-Coder across benchmarks, pricing, and capabilities.
Zhipu AI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
GLM-4.7 and Qwen3-Coder trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.
On price, Qwen3-Coder is roughly 5.6x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Qwen3-Coder also accepts a larger context window (256,000 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-4.7
- you want the most recent training data — it shipped Dec 2025
Choose Qwen3-Coder
- cost matters — it's about 5.6x cheaper per token
- you process long inputs — it offers a 256,000 token context window
At a glance
The differences that matter most.
Individual benchmarks
13 reported for GLM-4.7 · 0 for Qwen3-Coder
GLM-4.7 and Qwen3-Coderdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GLM-4.7 ($0.60/1M tokens) is 3.3x more expensive than Qwen3-Coder ($0.18/1M tokens).
For output processing, GLM-4.7 ($2.20/1M tokens) is 12.2x more expensive than Qwen3-Coder ($0.18/1M tokens).
In conclusion, GLM-4.7 is more expensive than Qwen3-Coder.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Qwen3-Coder has 122.0B more parameters than GLM-4.7, making it 34.1% larger.
Context Window
Maximum input and output token capacity
Qwen3-Coder accepts 256,000 input tokens compared to GLM-4.7's 202,800 tokens. Qwen3-Coder can generate longer responses up to 256,000 tokens, while GLM-4.7 is limited to 131,072 tokens.
Input capabilities
Documented input modalities across available providers
GLM-4.7 supports multimodal inputs, whereas Qwen3-Coder 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-Coder
License
Usage and distribution terms
GLM-4.7 is licensed under MIT, while Qwen3-Coder 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-4.7 was released on 2025-12-22, while Qwen3-Coder was released on 2025-01-01.
GLM-4.7 is 12 months newer than Qwen3-Coder.
Dec 22, 2025
8 months ago
11mo newerJan 1, 2025
1.7 years 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-Coder is available from DeepInfra, Fireworks.
GLM-4.7
Qwen3-Coder
Outputs Comparison
Judge for yourself.
Run your own prompts against GLM-4.7 and Qwen3-Coder side-by-side, then vote on the output you prefer.
FAQ
Common questions about GLM-4.7 vs Qwen3-Coder.