DeepSeek V4.1 Flash
DeepSeek's open-weight model, released under the MIT license on Hugging Face. The official DeepSeek-V4.1-Flash-1017 repository page calls it a minor update to V4.1-Flash (launched 2026-09-10 according to press coverage): 763 billion parameters in total (press also quotes 552 billion for the model body, so figures diverge), a 1-million-token context window, text and image input. DeepSeek reports gains in reasoning, coding, agentic tasks and vision, with shorter runs and shorter outputs, hence a lower bill for the same task. Publisher-reported, unverified figures: 42.3 on Terminal-Bench 4.0 (versus 31.2 for the previous version), 77.0 on DeepSWE v1.1, 42.6 on HLE without tools. In DeepSeek's own table, Opus 5 still leads on several of these tests.
Strengths
- Open weights under the MIT license: self-hosting possible, no vendor lock-in
- 1-million-token context and image input, rare at this price
- Reports shorter outputs and runs than the previous version: fewer tokens burned per task (per DeepSeek)
- Available behind OpenRouter: a single key to compare it against your usual model
Limitations
- Benchmarks come from the publisher only, and its own table shows Opus 5 ahead on several tests
- 763 billion parameters: self-hosting needs datacenter hardware, not a laptop
- Plugged into a coding agent built for Claude, tool calling is the first breaking point
- The "1017" release is a dated snapshot of a minor update: identifiers and prices move fast, check before committing
Best for
- Builders wanting to cut their LLM bill on high-volume repetitive tasks
- Teams testing a multi-model strategy through OpenRouter without switching tools
- Tech leads wanting a very long-context model under a permissive license