DeepSeek V4 Pro is a large-scale Mixture-of-Experts model from DeepSeek with 1.6T total parameters and 49B activated parameters, supporting a 1M-token context window. It is designed for advanced reasoning, coding,...
Model details →DeepSeek: DeepSeek V4 Pro vs Meituan: LongCat 2.0
Meituan: LongCat 2.0 wins on 2 of 6 axes — pricing and capability skew in its favour for most workloads.
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 →Side-by-side comparison
| Capability | DeepSeek: DeepSeek V4 Pro | Meituan: LongCat 2.0 | Winner |
|---|---|---|---|
| Context window Maximum number of input tokens the model can attend to in a single request. | 1.0M | 1.0M | 🏆 Meituan: LongCat 2.0 |
| Input price (per 1M) Cost per million input tokens billed by the provider. | $0.43 | $0.30 | 🏆 Meituan: LongCat 2.0 |
| Output price (per 1M) Cost per million output tokens billed by the provider. | $0.87 | $1.20 | 🏆 DeepSeek: DeepSeek V4 Pro |
| Tool / function calling First-class support for emitting structured tool calls. | Yes | Yes | Tie |
| Vision input Accepts image inputs alongside text. | — | — | Tie |
| Reasoning mode Internal chain-of-thought / extended-thinking support. | Yes | Yes | Tie |
Frequently asked questions
Is DeepSeek: DeepSeek V4 Pro better than Meituan: LongCat 2.0?
Meituan: LongCat 2.0 wins on 2 of 6 axes — pricing and capability skew in its favour for most workloads.
What's the price difference between DeepSeek: DeepSeek V4 Pro and Meituan: LongCat 2.0?
Input: $0.43 vs $0.30 per 1M tokens. Output: $0.87 vs $1.20 per 1M tokens.
What context windows do DeepSeek: DeepSeek V4 Pro and Meituan: LongCat 2.0 support?
DeepSeek: DeepSeek V4 Pro supports up to 1.0M tokens. Meituan: LongCat 2.0 supports up to 1.0M tokens.
Do both DeepSeek: DeepSeek V4 Pro and Meituan: LongCat 2.0 support tool calling?
DeepSeek: DeepSeek V4 Pro: yes. Meituan: LongCat 2.0: yes.
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