DeepSeek V4.1 Flash hands-on tests and comparisons

A user tested V4.1 Flash 1017, finding coding performance roughly on par with Grok 4.6–4.7 and fast, but local Q2_K quantization still needs 246GiB.

Relayed official claims: stronger reasoning, coding and agentic performance, better visual understanding, and more done with fewer output tokens and faster task completion.

A Japanese post says model fingerprint matching suggests DeepSeek V4.1 Flash could be the same model as GPT-6 Astra, while noting fingerprints alone do not prove identity and more evidence is needed.

A reply recommends trying DeepSeek V4.1 Flash with the officially recommended harness to see how it performs, without reporting any results.

A developer's custom Xolotl engine runs the 552B DeepSeek V4.1 Flash on one RTX 4090 via tiered storage and per-expert loading, hitting ~27 tok/s decode with 512K context.

NetEase LobsterAI's office-agent report says 73.6% of casual users stick to one model, with DeepSeek Flash + GLM 5.3 Flash the most common pairing at 14.0%; the poster claims the new 1017 build nears GPT 5.6 Sol.

A same-task coding cost comparison lists Opus 5.5 at about $74, Gemini 4 Argon at $2.5, DeepSeek Flash 1017 at just $0.34 and Grok 4.7 at about $7.

Post claims V4.1-Flash-1017 ranks #1 among open models and #12 overall on LM Arena's webdev code arena with 1670 points, ahead of Opus 5 high, at $0.30/$1.20 per million tokens.

WebDev Arena's first rating of V4.1 Flash 1017 is 1670 (#12), overlapping Gemini 4 Argon's 1678 and beating GPT-5.6 Sol's 1616 and its own September version's 1619; Opus 5.5 still leads at 1806.

The user asks whether Command Code still has not upgraded to DeepSeek V4.1 Flash 1017.

In a thread, a commenter agrees quantized models cover most needs but insists DeepSeek V4.1 Flash 1017 still trails 5.6 Sol, and the quantized version is further off.

The poster suspects DeepSeek-V4.1-Flash-1017 was distilled from GPT-6-Astra, but says it is cheap and good enough that it doesn't matter.