GLM-5.3 vs Qwen3-235B-A22B-Instruct-2507
Comparing GLM-5.3 and Qwen3-235B-A22B-Instruct-2507 across benchmarks, pricing, and capabilities.
Zhipu AI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
GLM-5.3 and Qwen3-235B-A22B-Instruct-2507 trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.
On price, Qwen3-235B-A22B-Instruct-2507 is roughly 6.9x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GLM-5.3 also accepts a larger context window (1,000,000 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
- you process long inputs — it offers a 1,000,000 token context window
- you want the most recent training data — it shipped Aug 2026
Choose Qwen3-235B-A22B-Instruct-2507
- cost matters — it's about 6.9x cheaper per token
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
GLM-5.3 and Qwen3-235B-A22B-Instruct-2507don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Arena Performance
Playground indexes and blind preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GLM-5.3 ($1.40/1M tokens) is 9.3x more expensive than Qwen3-235B-A22B-Instruct-2507 ($0.15/1M tokens).
For output processing, GLM-5.3 ($4.40/1M tokens) is 5.5x more expensive than Qwen3-235B-A22B-Instruct-2507 ($0.80/1M tokens).
In conclusion, GLM-5.3 is more expensive than Qwen3-235B-A22B-Instruct-2507.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
GLM-5.3 has 518.0B more parameters than Qwen3-235B-A22B-Instruct-2507, making it 220.4% larger.
Context Window
Maximum input and output token capacity
GLM-5.3 accepts 1,000,000 input tokens compared to Qwen3-235B-A22B-Instruct-2507's 262,144 tokens. Qwen3-235B-A22B-Instruct-2507 can generate longer responses up to 131,072 tokens, while GLM-5.3 is limited to 128,000 tokens.
Release Timeline
When each model was launched
GLM-5.3 was released on 2026-08-14, while Qwen3-235B-A22B-Instruct-2507 was released on 2025-07-22.
GLM-5.3 is 13 months newer than Qwen3-235B-A22B-Instruct-2507.
Aug 14, 2026
1 weeks ago
1.1yr newerJul 22, 2025
1.1 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-5.3 is available from ZAI. Qwen3-235B-A22B-Instruct-2507 is available from Fireworks, Novita.
GLM-5.3
Qwen3-235B-A22B-Instruct-2507
Outputs Comparison
Judge for yourself.
Run your own prompts against GLM-5.3 and Qwen3-235B-A22B-Instruct-2507 side-by-side, then vote on the output you prefer.
FAQ
Common questions about GLM-5.3 vs Qwen3-235B-A22B-Instruct-2507.