DeepSeek V4.1 Flash is a sparse mixture-of-experts model from DeepSeek, and the first built on the company's Causal Encoder-Decoder (CED) architecture. It activates 8B parameters on input and 16B on...
Model details →DeepSeek: DeepSeek V4.1 Flash vs Space Bunny Alpha
Space Bunny Alpha wins on 2 of 6 axes — pricing and capability skew in its favour for most workloads.
Space Bunny Alpha is an anonymous large model with blazing-fast inference, strong coding capabilities and native multimodal input support. It delivers adjustable reasoning effort, and a 1M-token context window. Space...
Model details →Side-by-side comparison
| Capability | DeepSeek: DeepSeek V4.1 Flash | Space Bunny Alpha | Winner |
|---|---|---|---|
| Context window Maximum number of input tokens the model can attend to in a single request. | 1.0M | 1M | 🏆 DeepSeek: DeepSeek V4.1 Flash |
| Input price (per 1M) Cost per million input tokens billed by the provider. | $0.14 | $0.00 | 🏆 Space Bunny Alpha |
| Output price (per 1M) Cost per million output tokens billed by the provider. | $0.42 | $0.00 | 🏆 Space Bunny Alpha |
| Tool / function calling First-class support for emitting structured tool calls. | Yes | Yes | Tie |
| Vision input Accepts image inputs alongside text. | Yes | Yes | Tie |
| Reasoning mode Internal chain-of-thought / extended-thinking support. | Yes | Yes | Tie |
Frequently asked questions
Is DeepSeek: DeepSeek V4.1 Flash better than Space Bunny Alpha?
Space Bunny Alpha wins on 2 of 6 axes — pricing and capability skew in its favour for most workloads.
What's the price difference between DeepSeek: DeepSeek V4.1 Flash and Space Bunny Alpha?
Input: $0.14 vs $0.00 per 1M tokens. Output: $0.42 vs $0.00 per 1M tokens.
What context windows do DeepSeek: DeepSeek V4.1 Flash and Space Bunny Alpha support?
DeepSeek: DeepSeek V4.1 Flash supports up to 1.0M tokens. Space Bunny Alpha supports up to 1M tokens.
Do both DeepSeek: DeepSeek V4.1 Flash and Space Bunny Alpha support tool calling?
DeepSeek: DeepSeek V4.1 Flash: yes. Space Bunny Alpha: yes.