LongCat 2.0 is a sparse mixture-of-experts language model from Meituan, with 48B active parameters out of 1.6T total. It is suited for coding, repository-level changes, long-horizon problem solving, and agentic...
Model details →Meituan: LongCat 2.0 vs Qwen: Qwen3.5-Flash
Qwen: Qwen3.5-Flash wins on 3 of 6 axes — pricing and capability skew in its favour for most workloads.
The Qwen3.5 native vision-language Flash models are built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. Compared to the...
Model details →Side-by-side comparison
| Capability | Meituan: LongCat 2.0 | Qwen: Qwen3.5-Flash | Winner |
|---|---|---|---|
| Context window Maximum number of input tokens the model can attend to in a single request. | 1.0M | 1M | 🏆 Meituan: LongCat 2.0 |
| Input price (per 1M) Cost per million input tokens billed by the provider. | $0.30 | $0.07 | 🏆 Qwen: Qwen3.5-Flash |
| Output price (per 1M) Cost per million output tokens billed by the provider. | $1.20 | $0.26 | 🏆 Qwen: Qwen3.5-Flash |
| 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-Flash |
| Reasoning mode Internal chain-of-thought / extended-thinking support. | Yes | Yes | Tie |
Frequently asked questions
Is Meituan: LongCat 2.0 better than Qwen: Qwen3.5-Flash?
Qwen: Qwen3.5-Flash wins on 3 of 6 axes — pricing and capability skew in its favour for most workloads.
What's the price difference between Meituan: LongCat 2.0 and Qwen: Qwen3.5-Flash?
Input: $0.30 vs $0.07 per 1M tokens. Output: $1.20 vs $0.26 per 1M tokens.
What context windows do Meituan: LongCat 2.0 and Qwen: Qwen3.5-Flash support?
Meituan: LongCat 2.0 supports up to 1.0M tokens. Qwen: Qwen3.5-Flash supports up to 1M tokens.
Do both Meituan: LongCat 2.0 and Qwen: Qwen3.5-Flash support tool calling?
Meituan: LongCat 2.0: yes. Qwen: Qwen3.5-Flash: yes.
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