Open-weight multimodal language model
DeepSeek-V4.1-Flash-1017
DeepSeek-V4.1-Flash-1017 is a minor update to DeepSeek-V4.1-Flash released by DeepSeek on 17 October 2026 under the MIT license. It keeps the 1M-token context and image input of V4.1-Flash, and DeepSeek says it scores higher on reasoning, coding, agentic and visual benchmarks while finishing tasks faster with shorter outputs.
Last reviewed 28 Oct 2026 · by DeepSeek
Facts at a glance
| Developer | DeepSeek |
|---|---|
| Released | 17 October 2026 source |
| License | MIT (repository and weights) |
| Model size | 763B parameters listed on Hugging Face; V4.1-Flash card gives 552B backbone, 8B to 16B active source |
| Context window | 1M tokens source |
| API name | deepseek-flash source |
| API price | $0.30 per 1M input tokens (cache miss) and $1.20 per 1M output tokens at peak; half price off-peak source |
What DeepSeek-V4.1-Flash-1017 is used for
DeepSeek says the update was trained with reinforcement learning with self-feedback to improve end-to-end project development, and that it is optimized for DeepSeek Harness, Tencent CodeBuddy and WorkBuddy. In the API it serves the deepseek-flash model name, and the legacy deepseek-v4-flash and deepseek-v4-flash-vision-exp names are routed to it. Vision input is supported on deepseek-flash.
Questions people ask
- Is DeepSeek-V4.1-Flash-1017 open weight?
- Yes. DeepSeek published the weights on Hugging Face and ModelScope, and the model card states the MIT license for the repository and weights.
- What does deepseek-flash cost?
- DeepSeek's pricing page lists $0.30 per 1M cache-miss input tokens, $0.006 per 1M cache-hit input tokens and $1.20 per 1M output tokens at peak, with off-peak rates at half those prices.