DeepSeek V4.1 Flash hands-on tests and comparisons

Against GLM 5.3's 744B A40B, V4.1 Flash 1017 is 763B A16B with only 1/2.5 the decode active parameters, which the author expects to yield at least 2x the speed.

Web, app and API all switch to the new model at unchanged pricing with MIT weights; official tests show Terminal-Bench 31.2→42.3 and DeepSWE 74.2→77.0, with Harness 0.2.1-rc.1 recommended.

A user who just finished a local model pipeline notes new DeepSeek-V4.1-Flash-1017 weights on HuggingFace and plans another test round.

Responding to claims that V4.1 Flash 1017 was distilled because its style resembles GPT and Claude, the author says getting comparable quality at Flash prices would justify it.

Identical config.json and 16B active params to the September build; DeepSWE hits 77% at ~$0.20 per task versus 74% at $0.50 before, and 72.5% at $0.11 in low effort.

A rundown of vendor-chart figures: MIT-licensed open weights, 77% on their own DeepSWE, about $0.20 per task, with a caveat to await independent benchmarks.

Niels Rogge shares the Hugging Face release: DeepSeek-V4.1-Flash-1017 is a minor update to V4.1-Flash with substantial gains in reasoning, coding, agentic tasks and visual benchmarks.

A blogger condenses DeepSeek's official update into one image: no price increase and across-the-board capability gains, linking the official announcement.

A Harness test generating a DeepSeek whale promo video with SVG, Canvas and Three.js: 247 tok/s, 49.4M tokens, 99% cache hit, total cost ¥2.17.

Using DSH plus the API, DeepSeek-V4.1-Flash-1017 reviewed recent Opus 5.5 commits, found one P0 and several P1 issues that Opus 5.5 confirmed, all for about ¥0.3.

Per its model card, V4.1-Flash-1017 improves reasoning, coding, agentic and visual benchmarks while cutting execution time and output length; Search and Fetch APIs open at $0.75 per 1,000 calls each, with free weights on Hugging Face and ModelScope.

The model card reports Terminal-Bench 4.0 at 42.3, ProgramBench at 29.1 and DeepSWE at 77.0, beating GPT-5.6 Sol and Opus 5, though HLE and Terminal-Bench still trail Opus 5; web, app and API are live, weights are on Hugging Face, and it is tuned for DeepSeek Harness and CodeBuddy.