Qwen3.5-9B is a multimodal foundation model from the Qwen3.5 family, designed to deliver strong reasoning, coding, and visual understanding in an efficient 9B-parameter architecture. It uses a unified vision-language design with early fusio…
Model details →Qwen: Qwen3.5-9B vs Z.ai: GLM 4.6 (exacto)
Qwen: Qwen3.5-9B wins on 4 of 6 axes — pricing and capability skew in its favour for most workloads.
Compared with GLM-4.5, this generation brings several key improvements: Longer context window: The context window has been expanded from 128K to 200K tokens, enabling the model to handle more complex agentic tasks. Superior coding performa…
Model details →Side-by-side comparison
| Capability | Qwen: Qwen3.5-9B | Z.ai: GLM 4.6 (exacto) | Winner |
|---|---|---|---|
| Context window Maximum number of input tokens the model can attend to in a single request. | 256K | 205K | 🏆 Qwen: Qwen3.5-9B |
| Input price (per 1M) Cost per million input tokens billed by the provider. | $0.05 | $0.44 | 🏆 Qwen: Qwen3.5-9B |
| Output price (per 1M) Cost per million output tokens billed by the provider. | $0.15 | $1.76 | 🏆 Qwen: Qwen3.5-9B |
| Tool / function calling First-class support for emitting structured tool calls. | Yes | Yes | Tie |
| Vision input Accepts image inputs alongside text. | Yes | — | 🏆 Qwen: Qwen3.5-9B |
| Reasoning mode Internal chain-of-thought / extended-thinking support. | Yes | Yes | Tie |
Frequently asked questions
Is Qwen: Qwen3.5-9B better than Z.ai: GLM 4.6 (exacto)?
Qwen: Qwen3.5-9B wins on 4 of 6 axes — pricing and capability skew in its favour for most workloads.
What's the price difference between Qwen: Qwen3.5-9B and Z.ai: GLM 4.6 (exacto)?
Input: $0.05 vs $0.44 per 1M tokens. Output: $0.15 vs $1.76 per 1M tokens.
What context windows do Qwen: Qwen3.5-9B and Z.ai: GLM 4.6 (exacto) support?
Qwen: Qwen3.5-9B supports up to 256K tokens. Z.ai: GLM 4.6 (exacto) supports up to 205K tokens.
Do both Qwen: Qwen3.5-9B and Z.ai: GLM 4.6 (exacto) support tool calling?
Qwen: Qwen3.5-9B: yes. Z.ai: GLM 4.6 (exacto): yes.