DeepSeek V4.1 Flash hands-on tests and comparisons

A Japanese user says OpenCode lets them use GLM 5.3 Flash and DeepSeek V4.1 Flash for free, making local inference with its power and heat costs pointless.

The author notes V4.1-Flash-1017 replaced models on web, app and API and was tuned for DeepSeek Harness and Tencent CodeBuddy, warning teams to re-test and keep rollback options.

Relaying another user's build: every texture generated with no imported files, 3D game work just under Opus 5.5 but ahead of other open models, a big jump from the last Flash.

At max reasoning, Astra took 20 minutes and $7 while DeepSeek took 1 hour 40 minutes and $0.9; the author concedes Astra is more refined but says the Flash model nearly matches it at about one-tenth the cost.

Official claims the new version improves benchmarks, finishes tasks faster and gives shorter answers, cutting output-token cost.

A roundup of official figures: coding and agent results improve with three listed tests ahead of Opus 5, MIT-licensed weights are available, and the deepseek-flash API name and token prices stay the same.

An Arabic-language user says DeepSeek V4.1 Flash now matches Opus 5 and GPT 5.6 Sol in strength, but argues benchmarks are of limited use and one should test it personally.

A Persian-language post says DeepSeek V4.1 Flash 1017 beat all models on cost per cycle in Bug Hunt Bench and posted an impressive overall score for a Flash-tier model.

The author had V4.1 Flash 1017 one-shot a Three.js robot assembly and launch test via AiHubMix for just $0.04, noting how cheap DeepSeek is for the output quality.

On the same 15-second motion graphics showreel task, Opus 5.5 took 26 minutes and cost $5.75 while DeepSeek used about 68M tokens as open weights; Opus looked better but DeepSeek was far cheaper.

A video comparison on the same three.js 3D modeling task finds the 1017 build far stronger than the previous V4.1 Flash, which the author finds hard to believe for the same parameter count.

A poster says a side-by-side video makes switching to DeepSeek hard to resist, though no specific tests or numbers are given.