GLM-5.2 vs Qwen3 VL 4B Thinking: Specs & Benchmark Comparison
| Characteristic | GLM-5.2 | Qwen3 VL 4B Thinking |
|---|---|---|
| Company | Zhipu AI | Alibaba |
| Release Date | June 16, 2026 | September 22, 2025 |
| Parameters | 753B | 4B |
| Multimodal | No | Yes |
| Context (input) | 1.0M | 262K |
| Context (output) | 131K | 262K |
| Input Price / 1M | $1.40 | $0.10 |
| Output Price / 1M | $4.40 | $1.00 |
| Average Score | 0.9 | 0.9 |
Verdict
GLM-5.2 leads in 2 out of 4 comparison categories.
Overall Performance
Both models show comparable average scores: GLM-5.2 — 0.9, Qwen3 VL 4B Thinking — 0.9.
API Cost
Qwen3 VL 4B Thinking is 5.3x cheaper: input $0.10/1M vs $1.40/1M tokens.
Context Window
GLM-5.2 supports a larger context: 1M vs 262K tokens.
Recency
GLM-5.2 is newer: released 6/16/2026 vs 9/22/2025.
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Frequently Asked Questions
Which is better for coding — GLM-5.2 or Qwen3 VL 4B Thinking?
Direct comparison on the SWE-Bench benchmark is not available. We recommend reviewing other metrics on the comparison page.
Which model is cheaper — GLM-5.2 or Qwen3 VL 4B Thinking?
Qwen3 VL 4B Thinking is cheaper for input: $0.10 per 1M tokens vs $1.40.
Which has a larger context window — GLM-5.2 or Qwen3 VL 4B Thinking?
GLM-5.2 supports a larger context: 1,000,000 tokens vs 262,144.
The GLM-5.2 and Qwen3 VL 4B Thinking comparison is updated for 2026. Data includes benchmark results, API pricing, context window size and other specifications. For more detailed information, visit the GLM-5.2 or Qwen3 VL 4B Thinking page. See also the complete list of AI model comparisons.