Today · event date October 17

DeepSeek releases V4.1-Flash-1017; scores are self-reported

DeepSeek releases V4.1-Flash-1017 weights under the MIT license, self-reporting wins over GPT-5.6 Sol on 9 of 11 benchmarks

Concept illustration: on the left, a person with long dark hair, wearing a black turtleneck, a badge on a lanyard, wide grey-brown trousers and white shoes, rests one hand on the top edge of the screen of an oversized red laptop. The laptop's black screen shows a light grey speech bubble with three grey lines, and the front of its base below the cream keyboard is lettered "V4.1-FLASH-1017"; at top right a light grey panel shows a blue whale emblem and the lettering "DEEPSEEK", with a pale pink circle behind the laptop against a cream wall and floor.

Why it matters: DeepSeek self-reports Terminal-Bench 4.0 up 11.1 points, from 31.2 to 42.3, in a release about a month after the previous one. One month-long gap between releases is too little to show a pattern.

On October 17 DeepSeek released the weights of V4.1-Flash-1017 on Hugging Face under the MIT license, and the model card calls it a "minor update" (DeepSeek model card, 2026-10-17). The card's table has 11 benchmarks, with Kimi K3, GLM-5.3, GPT-5.6 Sol and Opus 5 in the comparison columns. By SecondSource's column-by-column count, the model beats GPT-5.6 Sol on 9 and beats Opus 5 on 4 while trailing it on 7.

Against V4.1-Flash from a month earlier, the largest gains are Terminal-Bench 4.0, from 31.2 to 42.3, and ProgramBench, from 20.3 to 29.1. Terminal-Bench 4.0 tests whether a model can finish tasks in a terminal. ProgramBench asks a model to rebuild a program from compiled binaries and documentation. The whole table is DeepSeek's own report. The card doesn't say whether rival scores were run by DeepSeek or taken from published figures. The comparison set is a generation behind: the card compares against Opus 5 and GPT-5.6 Sol, while evaluation tables compiled the same week by Paweł Huryn and others already compare Opus 5.5 and GPT-6 Astra.

DeepSeek calls the release "a Pareto improvement in performance and cost" (DeepSeek, 2026-10-17). Susan Zhang, an AI researcher, notes that DeepSeek shipped again after about a month, while V4 to V4.1 took about five months (Susan Zhang, 2026-10-17). Her post gives no start dates for either interval.

There is outside evidence beyond the table. BugBunny, a vulnerability evaluator, built its own set of 100 pull requests containing bugs. The 1017 release found 54 for US$7.53; the previous version found 44 for US$12.79 (BugBunny, 2026-10-17). That is a separate test, not a rerun of DeepSeek's table.

Our read: DeepSeek is competing on price-performance in its cheapest tier, Flash, moving forward through small dated refreshes rather than waiting for the next flagship. Another explanation isn't ruled out: the V4.1-Pro flagship hasn't shipped, so the Flash refresh may just be filling the gap.

Not proven yet: all 11 benchmarks are self-reported, with no third-party rerun How we checked →

Judgment update: Our read: to gauge the pressure Chinese models put on API prices and agent workloads, the thing to watch is how often the low-price tier refreshes and how far each refresh moves, not flagship rankings. There is only one interval, September 10 to October 17, which isn't enough of a sample. The checkable markers are whether the next dated refresh appears within six weeks, and whether Terminal-Bench 4.0 approaches Opus 5's 51.8.

Source and checks

This item ran in the brief of Oct 18, 2026, alongside 14 other items. How we checked it, the quote checks and what was still missing that day are on that issue's How we checked page.

Cite this item

SecondSource (2026). "DeepSeek releases V4.1-Flash-1017; scores are self-reported." https://secondsource.io/en/news/2026-10-18-1/. Accessed access date.