DeepSeek V4.1 Flash hands-on tests and comparisons

Benchmark comparison of V4.1 Flash 1017 against Opus 5: DeepSWE 77.0 vs 74.0 and Automation-Bench 60.5 vs 50.3, while Terminal-Bench 4.0 and HLE still trail; also lists 1M context, image input, MIT weights and API pricing.

After 10+ complex agent tasks and nearly 500M tokens on the new V4.1 Flash, the author reports a 99.41% cache hit rate and calls its cache-based cost reduction unmatched.

Same voxel-style event video task cost $0.89 with DeepSeek V4.1 Flash 1017 and $1.07 with GPT-6 Luna; the post also promotes a free Workbuddy trial.

A user's early notes on DeepSeek V4.1-Flash-1017: fewer wasted steps, more decisive coding, new Search + Fetch for agents, though complex multi-file edits still need review.

A market recap notes DeepSeek officially launched V4.1 Flash 1017 with wish-style coding and a new search API, at unchanged pricing, while outages suggest compute shortages.

DeepSeek V4.1 Flash 1017 weights are on Hugging Face at 763B parameters under the MIT license, available for local deployment.

A collected comparison of pelican generations across harnesses concludes that DeepSeek Harness and Codex produce the best results with V4.1 Flash 1017.

The poster is torn over rumors that V4.1 Flash is distilled from GPT-6 Astra, hoping it is false for domestic-model pride yet true for cheap Astra-level capability.

A roundup of the 1017 release: MIT open weights, faster and cheaper outputs, Search and Fetch APIs for agents, and 77.0 on DeepSWE.

A user says the 1017 release averages about 5 points above 0910, with Terminal-Bench 4.0 jumping from 31.2 to 42.3, beating GPT-5.6 Sol at the same price.

After two Claude accounts were banned, the author switched to Codex for a few days, found DeepSeek 1017 comparable for AI explainer videos, and plans to keep testing its coding ability.

A same-prompt comparison generating a Tesla Roadster with DeepSeek V4.1 Flash 1017 and GPT-6 Luna, with the author calling the DeepSeek result a near clean win.