GLM-5.3 vs Qwen3 VL 4B Thinking
Comparing GLM-5.3 and Qwen3 VL 4B Thinking across benchmarks, pricing, and capabilities.
Zhipu AI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
GLM-5.3 and Qwen3 VL 4B Thinking trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.
On price, Qwen3 VL 4B Thinking is roughly 6.6x 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 VL 4B Thinking
- cost matters — it's about 6.6x 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 VL 4B Thinkingdon'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 14.0x more expensive than Qwen3 VL 4B Thinking ($0.10/1M tokens).
For output processing, GLM-5.3 ($4.40/1M tokens) is 4.4x more expensive than Qwen3 VL 4B Thinking ($1.00/1M tokens).
In conclusion, GLM-5.3 is more expensive than Qwen3 VL 4B Thinking.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
GLM-5.3 has 749.0B more parameters than Qwen3 VL 4B Thinking, making it 18725.0% larger.
Context Window
Maximum input and output token capacity
GLM-5.3 accepts 1,000,000 input tokens compared to Qwen3 VL 4B Thinking's 262,144 tokens. Qwen3 VL 4B Thinking can generate longer responses up to 262,144 tokens, while GLM-5.3 is limited to 128,000 tokens.
Input Capabilities
Supported data types and modalities
Qwen3 VL 4B Thinking supports multimodal inputs, whereas GLM-5.3 does not.
Qwen3 VL 4B Thinking can handle both text and other forms of data like images, making it suitable for multimodal applications.
GLM-5.3
Qwen3 VL 4B Thinking
Release Timeline
When each model was launched
GLM-5.3 was released on 2026-08-14, while Qwen3 VL 4B Thinking was released on 2025-09-22.
GLM-5.3 is 11 months newer than Qwen3 VL 4B Thinking.
Aug 14, 2026
1 weeks ago
10mo newerSep 22, 2025
11 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 is available from ZAI. Qwen3 VL 4B Thinking is available from DeepInfra.
GLM-5.3
Qwen3 VL 4B Thinking
Outputs Comparison
Judge for yourself.
Run your own prompts against GLM-5.3 and Qwen3 VL 4B Thinking side-by-side, then vote on the output you prefer.
FAQ
Common questions about GLM-5.3 vs Qwen3 VL 4B Thinking.