Qwen3-32B is a dense 32.8B parameter causal language model from the Qwen3 series, optimized for both complex reasoning and efficient dialogue. It supports seamless switching between a "thinking" mode for...
Model details →Qwen: Qwen3 32B vs Tencent: Hunyuan A13B Instruct
Qwen: Qwen3 32B wins on 3 of 6 axes — pricing and capability skew in its favour for most workloads.
Hunyuan-A13B is a 13B active parameter Mixture-of-Experts (MoE) language model developed by Tencent, with a total parameter count of 80B and support for reasoning via Chain-of-Thought. It offers competitive benchmark...
Model details →Side-by-side comparison
| Capability | Qwen: Qwen3 32B | Tencent: Hunyuan A13B Instruct | Winner |
|---|---|---|---|
| Context window Maximum number of input tokens the model can attend to in a single request. | 131K | 131K | Tie |
| Input price (per 1M) Cost per million input tokens billed by the provider. | $0.08 | $0.14 | 🏆 Qwen: Qwen3 32B |
| Output price (per 1M) Cost per million output tokens billed by the provider. | $0.28 | $0.57 | 🏆 Qwen: Qwen3 32B |
| Tool / function calling First-class support for emitting structured tool calls. | Yes | — | 🏆 Qwen: Qwen3 32B |
| Vision input Accepts image inputs alongside text. | — | — | Tie |
| Reasoning mode Internal chain-of-thought / extended-thinking support. | Yes | Yes | Tie |
Frequently asked questions
Is Qwen: Qwen3 32B better than Tencent: Hunyuan A13B Instruct?
Qwen: Qwen3 32B wins on 3 of 6 axes — pricing and capability skew in its favour for most workloads.
What's the price difference between Qwen: Qwen3 32B and Tencent: Hunyuan A13B Instruct?
Input: $0.08 vs $0.14 per 1M tokens. Output: $0.28 vs $0.57 per 1M tokens.
What context windows do Qwen: Qwen3 32B and Tencent: Hunyuan A13B Instruct support?
Qwen: Qwen3 32B supports up to 131K tokens. Tencent: Hunyuan A13B Instruct supports up to 131K tokens.
Do both Qwen: Qwen3 32B and Tencent: Hunyuan A13B Instruct support tool calling?
Qwen: Qwen3 32B: yes. Tencent: Hunyuan A13B Instruct: not advertised.