DeepSeek
DeepSeek: DeepSeek V4.1 Flash 1017
deepseek/deepseek-v4.1-flash-1017
DeepSeek V4.1 Flash 1017 is the October 17, 2026 snapshot of DeepSeek V4.1 Flash, served by DeepSeek under the `deepseek-flash` API model name. 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 output from a 552B-parameter backbone, an asymmetric split that keeps per-token compute low relative to the model's total size. Image understanding is native to the architecture, with visual and text embeddings trained jointly from the start of pre-training rather than added afterward as in the earlier experimental V4 Flash Vision Exp. It is suited for coding, terminal, and computer-use agents, along with long-horizon tasks that must run to completion across many steps and long-context analysis. Compressed KV caching cuts cache memory to roughly a quarter of the previous Flash generation, significantly reducing costs on agentic workloads. DeepSeek positions it as the cost-efficient tier of the V4.1 family and reports that it exceeds V4 Pro on performance, speed, and task completion time.
/ 1M tokens
/ 1M tokens
tokens
Limits
Context
1,048,576
tokens
Max output
393,216
38% of the context window
Parameters
763,205,315,794
Model facts
Author
DeepSeek
Tokenizer
DeepSeek
Modality
Text + Image -> Text
License
MIT
Created
Oct 17, 2026
Hugging Face
deepseek-ai/DeepSeek-V4.1-Flash-1017
Reasoning
Publication status
Modalities
Generation controls
Capability scores
Better than 83% of models compared