# DeepSeek Releases V4.1-Flash-1017 Open Weights Under MIT; Artificial Analysis Scores It 45.10

Times of AI Desk · 2026-10-20 · Models

[https://timesof.ai/2026/10/deepseek-v4-1-flash-1017-open-weights-mit](https://timesof.ai/2026/10/deepseek-v4-1-flash-1017-open-weights-mit)

> DeepSeek released DeepSeek-V4.1-Flash-1017 on Oct. 17 as MIT-licensed weights, a 763B-parameter model with 1M-token context that it calls a minor update. Artificial Analysis scores it 45.10 on its Intelligence Index, second among open-weight models in the payload we parsed behind MiMo-V2.6-Pro at 46.32. Lab agentic gains are DeepSeek's own.

A cheap, permissively licensed Chinese open model moved up on agentic coding the same week a DeepSeek Flash variant appeared in a hacking campaign and DHS ordered DeepSeek out of civilian agencies. **DeepSeek** released **DeepSeek-V4.1-Flash-1017** on **Saturday, October 17** as MIT-licensed weights on Hugging Face and ModelScope. The model card calls it a "**minor update**" to a **763B**-parameter model with a **1M**-token context.

## Lab-reported scores

Compared with base V4.1-Flash, DeepSeek reports Humanity's Last Exam without tools at **42.6** vs 36.8; Terminal-Bench 4.0 at **42.3** vs 31.2 (Claude Code harness; the card lists Opus 5 at 51.8); DeepSWE v1.1 at **77.0** vs 74.2 (Mini-SWE-V2 harness); and ProgramBench at **29.1** vs 20.3. **The Decoder** says DeepSeek also opened Search and Fetch APIs at **$0.75** per 1,000 calls and that DeepSWE tasks cost just under **$0.20** each against about **$0.50** for the predecessor.

## Independent score

**Artificial Analysis** scores DeepSeek V4.1 Flash 1017 (Max) at **45.10** on its Intelligence Index. In the payload we parsed, that is second among open-weight models behind MiMo-V2.6-Pro (**46.32**). We covered [earlier V4 pricing](https://timesof.ai/2026/08/deepseek-v4-api-pricing) separately. NorForge's Cairn worker used an unspecified `deepseek-v4.1-flash` snapshot; we do not say 1017 was used.

## Limits

- Agentic and coding figures are DeepSeek's, run in different harnesses. Only the Artificial Analysis index is independent here.

## Sources

- [Hugging Face: DeepSeek-V4.1-Flash-1017 model card](https://huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash-1017)
- [Artificial Analysis Intelligence Index](https://artificialanalysis.ai/evaluations/artificial-analysis-intelligence-index)
- [The Decoder: Deepseek V4.1 Flash 1017 agentic gains and API pricing (October 17, 2026)](https://the-decoder.com/deepseek-v4-1-flash-1017-beats-larger-rivals-in-agentic-tasks-while-once-again-massively-cutting-per-task-costs/)
- [Times of AI: DeepSeek V4 API pricing (August 13, 2026)](https://timesof.ai/2026/08/deepseek-v4-api-pricing)