Model comparison
Qwen3-VL vs GLM-4.5V
- Input
- $0.20 / 1M tokens (0-32K tier)
- Output
- $1.60 / 1M tokens (0-32K tier)
- Context
- 256K
- Released
- 2025-09-23
- Input
- $0.60 / 1M tokens
- Output
- $1.80 / 1M tokens
- Context
- 64K
- Released
- 2025-08-11
Qwen3-VL scores higher on 2 of the 2 benchmarks both models report; Qwen3-VL is cheaper on input tokens ($0.2 vs $0.6 per 1M, 3×); Qwen3-VL has the larger context window (256K vs 64K).
Specs and pricing side by side
| Spec | Qwen3-VL | GLM-4.5V |
|---|---|---|
| Maker | Alibaba (Qwen) | Z.ai (Zhipu / GLM) |
| Released | 2025-09-23 | 2025-08-11 |
| Context window | 256K | 64K |
| Max output | 32K | 16K |
| Input price | $0.20 / 1M tokens (0-32K tier) | $0.60 / 1M tokens |
| Output price | $1.60 / 1M tokens (0-32K tier) | $1.80 / 1M tokens |
| Parameters | 235B total / 22B active (flagship MoE); also dense 2B/4B/8B/32B and MoE 30B-A3B | 106B total / 12B active (MoE) |
| License | Apache 2.0 | MIT |
| Weights | Open weights | Open weightssame |
| Modalities | Text, Vision, Video, PDF | Text, Vision, Video, PDFsame |
| Knowledge cutoff | Not publicly disclosed | December 2024 |
Benchmarks both models report
| Benchmark | Qwen3-VL | GLM-4.5V |
|---|---|---|
| MathVista | 85.8% | 84.6% |
| MMMU-Pro | 69.3% | 65.2% |
Scores are as published by each maker or its cited source; harness, reasoning effort and date can differ between rows, so treat small gaps as ties. Sources are listed on each model page.
Which one should you pick?
Pick Qwen3-VL if…
- You care about MathVista, MMMU-Pro (it scores higher on 2 shared benchmarks).
- Cost matters: input tokens cost 3× less ($0.2 vs $0.6 per 1M).
- You need the longer context (256K vs 64K).
- Your use case is: document, invoice, and form parsing with multilingual OCR.
Pick GLM-4.5V if…
- Your use case is: document, chart and long-PDF understanding and information extraction.
FAQ
Which is better, Qwen3-VL or GLM-4.5V?
Qwen3-VL scores higher on 2 of the 2 benchmarks both models report; Qwen3-VL is cheaper on input tokens ($0.2 vs $0.6 per 1M, 3×); Qwen3-VL has the larger context window (256K vs 64K). The better pick depends on whether you value benchmark scores, price per token, context length or openness for your workload.
How much cheaper is Qwen3-VL?
Qwen3-VL: $0.20 / 1M tokens (0-32K tier) input, $1.60 / 1M tokens (0-32K tier) output. GLM-4.5V: $0.60 / 1M tokens input, $1.80 / 1M tokens output (list API prices as published by each maker).
What are the context windows of Qwen3-VL and GLM-4.5V?
Qwen3-VL offers 256K with up to 32K output; GLM-4.5V offers 64K with up to 16K output.
Is Qwen3-VL newer than GLM-4.5V?
Qwen3-VL was released 2025-09-23; GLM-4.5V was released 2025-08-11.