DeepSeek V4 Flash — 1M context, thinking and non-thinking modes; see DeepSeek pricing/docs for current capabilities.
Model details →DeepSeek V4 Flash vs omni-research/Tarsier2-Recap-7b
DeepSeek V4 Flash wins on 1 of 6 axes — pricing and capability skew in its favour for most workloads.
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Model details →Side-by-side comparison
| Capability | DeepSeek V4 Flash | omni-research/Tarsier2-Recap-7b | Winner |
|---|---|---|---|
| Context window Maximum number of input tokens the model can attend to in a single request. | 1M | Unknown | 🏆 DeepSeek V4 Flash |
| Input price (per 1M) Cost per million input tokens billed by the provider. | Custom | Custom | — |
| Output price (per 1M) Cost per million output tokens billed by the provider. | Custom | Custom | — |
| Tool / function calling First-class support for emitting structured tool calls. | — | — | Tie |
| Vision input Accepts image inputs alongside text. | — | — | Tie |
| Reasoning mode Internal chain-of-thought / extended-thinking support. | — | — | Tie |
Frequently asked questions
Is DeepSeek V4 Flash better than omni-research/Tarsier2-Recap-7b?
DeepSeek V4 Flash wins on 1 of 6 axes — pricing and capability skew in its favour for most workloads.
What's the price difference between DeepSeek V4 Flash and omni-research/Tarsier2-Recap-7b?
Input: Custom vs Custom per 1M tokens. Output: Custom vs Custom per 1M tokens.
What context windows do DeepSeek V4 Flash and omni-research/Tarsier2-Recap-7b support?
DeepSeek V4 Flash supports up to 1M tokens. omni-research/Tarsier2-Recap-7b supports up to Unknown tokens.
Do both DeepSeek V4 Flash and omni-research/Tarsier2-Recap-7b support tool calling?
DeepSeek V4 Flash: not advertised. omni-research/Tarsier2-Recap-7b: not advertised.