Kimi K2 Instruct is a large-scale Mixture-of-Experts (MoE) language model developed by Moonshot AI, featuring 1 trillion total parameters with 32 billion active per forward pass. It is optimized for agentic capabilities, including advanced …
Model details →MoonshotAI: Kimi K2 0711 vs Qwen: Qwen VL Max
Qwen: Qwen VL Max wins on 3 of 6 axes — pricing and capability skew in its favour for most workloads.
Qwen VL Max is a visual understanding model with 7500 tokens context length. It excels in delivering optimal performance for a broader spectrum of complex tasks.
Model details →Side-by-side comparison
| Capability | MoonshotAI: Kimi K2 0711 | Qwen: Qwen VL Max | 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. | $0.57 | $0.52 | 🏆 Qwen: Qwen VL Max |
| Output price (per 1M) Cost per million output tokens billed by the provider. | $2.30 | $2.08 | 🏆 Qwen: Qwen VL Max |
| Tool / function calling First-class support for emitting structured tool calls. | Yes | Yes | Tie |
| Vision input Accepts image inputs alongside text. | — | Yes | 🏆 Qwen: Qwen VL Max |
| Reasoning mode Internal chain-of-thought / extended-thinking support. | — | — | Tie |
Frequently asked questions
Is MoonshotAI: Kimi K2 0711 better than Qwen: Qwen VL Max?
Qwen: Qwen VL Max wins on 3 of 6 axes — pricing and capability skew in its favour for most workloads.
What's the price difference between MoonshotAI: Kimi K2 0711 and Qwen: Qwen VL Max?
Input: $0.57 vs $0.52 per 1M tokens. Output: $2.30 vs $2.08 per 1M tokens.
What context windows do MoonshotAI: Kimi K2 0711 and Qwen: Qwen VL Max support?
MoonshotAI: Kimi K2 0711 supports up to 131K tokens. Qwen: Qwen VL Max supports up to 131K tokens.
Do both MoonshotAI: Kimi K2 0711 and Qwen: Qwen VL Max support tool calling?
MoonshotAI: Kimi K2 0711: yes. Qwen: Qwen VL Max: yes.