DeepSeek V4.1 Flash 1017: What Changed, the Price and Claude Code Setup DeepSeek released DeepSeek V4.1 Flash 1017 on 17 October 2026, a 763B-parameter open-weights update to V4.1 Flash published under the MIT License, with a 1M-token context window and 384K-token maximum API output. DeepSeek's own benchmark table shows the update scoring 42.3 on Terminal-Bench 4.0 (up from 31.2 for V4.1 Flash) and 77.0 on DeepSWE v1.1, while Opus 5 leads Terminal-Bench 4.0 at 51.8; DeepSeek says the model "uses reinforcement learning with self-feedback to improve end-to-end project development." The model now serves the deepseek-flash name in DeepSeek's API, with weights free to download and per-million-token pricing listed on DeepSeek's pricing page. DeepSeek V4.1 Flash 1017: What Changed, the Price and Claude Code Setup DeepSeek V4.1 Flash 1017, released 17 Oct 2026 under MIT: what changed, DeepSeek's benchmarks, the API price and Claude Code setup. DeepSeek V4.1 Flash 1017 is an update to DeepSeek’s V4.1 Flash model, released on 17 October 2026 with open weights under the MIT License. DeepSeek’s release note promises “Stronger benchmark performance, faster task completion, and shorter outputs than the previous version”. It now serves the deepseek-flash name in DeepSeek’s API. Checked 17 Oct 2026. Open weight coding models need an agent to drive them. Munder Difflin https://harnessmd.com/download is free and open source: a desktop app that runs a team of coding agents such as Claude Code, Codex and Gemini CLI on your own computer. Our guide to running it on open models https://munderdiffl.in/blog/run-munder-difflin-on-open-models/ covers local runtimes and providers, and our install guide https://munderdiffl.in/blog/how-to-install-and-use-munder-difflin/ covers setup. What is DeepSeek V4.1 Flash 1017? what-is-deepseek-v41-flash-1017 The model card https://huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash-1017 calls it “a minor update to DeepSeek-V4.1-Flash, delivering substantial improvements across reasoning, coding, agentic tasks, and visual benchmarks.” It adds that the model “reduces task execution time and output length”. Hugging Face created the repo on 17 Oct 2026 and lists the model size as 763B parameters. | Detail | DeepSeek V4.1 Flash 1017 17 Oct 2026 | |---|---| | Licence | MIT, for the repository and the weights | | Size | 763B parameters, per Hugging Face | | Weights | FP8, with the experts in FP4, per the model’s config file | | Context | 1M tokens | | Max output in the API | 384K tokens | | Input | Text and images the API lists Vision for deepseek-flash | | Recommended sampling | temperature 1.0, top p 1.0, max tokens of at least 256K | The release ships no Jinja chat template. Instead the repo has an encoding folder with a Python reference implementation, and the model card also points to DeepSeek’s deepseek-recipe https://github.com/deepseek-ai/deepseek-recipe , Rust libraries with Python bindings for the same prompt format. The inference folder calls itself “A readable reference implementation rather than a production serving engine.” How does it score? how-does-it-score DeepSeek’s table compares the update with the previous Flash and with models it labels K3, GLM-5.3, GPT-5.6 Sol and Opus 5. Selected rows: | Benchmark | V4.1 Flash 1017 | V4.1 Flash | Opus 5 | |---|---|---|---| | Terminal-Bench 4.0 | 42.3 | 31.2 | 51.8 | | DeepSWE v1.1 | 77.0 | 74.2 | 74.0 | | ProgramBench | 29.1 | 20.3 | 37.0 | | Automation-Bench v1.0.6 | 60.5 | 54.8 | 50.3 | | Agents’ Last Exam | 35.4 | 31.8 | 28.6 | DeepSeek notes: “We use the Claude Code harness for Terminal-Bench 4.0 and the Mini-SWE-V2 harness for DeepSWE v1.1.” Of the eleven rows in its table, the update has the top score on four DeepSWE v1.1, Automation-Bench, Agents’ Last Exam and Apex Bench , Opus 5 on six, including Terminal-Bench 4.0 and ProgramBench, and GPT-5.6 Sol on one. These are DeepSeek’s own numbers. DeepSeek’s release note https://api-docs.deepseek.com/news/news261017 says the model “uses reinforcement learning with self-feedback to improve end-to-end project development” and is “Optimized for DeepSeek Harness, Tencent CodeBuddy, WorkBuddy, and more.” On Hacker News, two posts about the release had more than 200 points each on 17 Oct. How much does DeepSeek V4.1 Flash 1017 cost? how-much-does-deepseek-v41-flash-1017-cost The weights are free to download. DeepSeek’s first API call page https://api-docs.deepseek.com/ says deepseek-flash “is now served by DeepSeek-V4.1-Flash-1017”. DeepSeek’s pricing page https://api-docs.deepseek.com/quick start/pricing lists these rates per million tokens on 17 Oct 2026: | deepseek-flash | Off peak | Peak | |---|---|---| | Input, cache hit | $0.003 | $0.006 | | Input, cache miss | $0.15 | $0.30 | | Output | $0.60 | $1.20 | DeepSeek says “Off-peak rates are half of the peak rates.” Peak hours are 01:00 to 04:00 and 06:00 to 10:00 UTC, Monday through Friday, excluding Chinese public holidays; weekends are off peak. On OpenRouter https://openrouter.ai/deepseek/deepseek-v4.1-flash-1017 on 17 Oct, several providers served it, including DeepSeek, whose own endpoint listed $0.15 input and $0.60 output per million tokens with a 1,048,576 token context. The old names still work. The API docs say deepseek-v4-flash and deepseek-v4-flash-vision-exp “are still accepted, but the corresponding models have been retired”, with requests served by the new model “and billed at the Flash price.” The release note also opens DeepSeek’s Search and Fetch APIs to everyone at “$0.75 per 1,000 calls” per endpoint. Search and Fetch calls through server side tools in DeepSeek Harness, Claude Code and Codex are free for DeepSeek API users until billing starts on 31 Oct 2026 at 16:00 UTC. How do you use it in Claude Code? how-do-you-use-it-in-claude-code DeepSeek’s API speaks the Anthropic format at https://api.deepseek.com/anthropic https://api.deepseek.com/anthropic , and its Claude Code guide https://api-docs.deepseek.com/quick start/agent integrations/claude code sets these variables before you run claude in your project: export ANTHROPIC BASE URL=https://api.deepseek.com/anthropic export ANTHROPIC AUTH TOKEN=