GLM-4.7-Flash vs QwQ-32B
GLM-4.7-Flash leads the LLM Stats Score 23.5 to 14.8.
Zhipu AI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
GLM-4.7-Flash leads the overall LLM Stats Score 23.5 to 14.8, ranking #175 overall.
In the 1 individual benchmarks reported for both models, GLM-4.7-Flash wins 1; this is a narrower head-to-head signal than the composite indexes.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose GLM-4.7-Flash
- overall performance matters — it scores 23.5 and ranks #175 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- you want the most recent training data — it shipped Jan 2026
Choose QwQ-32B
- you are already invested in the Alibaba Cloud / Qwen Team ecosystem
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
6 reported for GLM-4.7-Flash · 7 for QwQ-32B
GLM-4.7-Flash outperforms in 1 benchmarks (GPQA), while QwQ-32B is better at 0 benchmarks.
GLM-4.7-Flash significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Model Size
Parameter count comparison
QwQ-32B has 2.5B more parameters than GLM-4.7-Flash, making it 8.3% larger.
Context Window
Maximum input and output token capacity
Only GLM-4.7-Flash specifies input context (128,000 tokens). Only GLM-4.7-Flash specifies output context (16,384 tokens).
License
Usage and distribution terms
GLM-4.7-Flash is licensed under MIT, while QwQ-32B 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-Flash was released on 2026-01-19, while QwQ-32B was released on 2025-03-05.
GLM-4.7-Flash is 11 months newer than QwQ-32B.
Jan 19, 2026
8 months ago
10mo newerMar 5, 2025
1.5 years ago
Knowledge Cutoff
When training data ends
QwQ-32B has a documented knowledge cutoff of 2024-11-28, while GLM-4.7-Flash's cutoff date is not specified.
We can confirm QwQ-32B's training data extends to 2024-11-28, but cannot make a direct comparison without GLM-4.7-Flash's cutoff date.
—
Nov 2024
Outputs Comparison
Judge for yourself.
Run your own prompts against GLM-4.7-Flash and QwQ-32B side-by-side, then vote on the output you prefer.
FAQ
Common questions about GLM-4.7-Flash vs QwQ-32B.