DeepSeek-V4.1-FlashOpen Weight

Released

DeepSeek-V4.1-Flash is an AI model released by DeepSeek on Thursday, Sep 10 2026, 28 days after DeepSeek-V4-Pro-0813. It is an open-weight model — the trained weights are available to download and run. Benchmark results (shown below) cover NL2Repo-Bench, Terminal-Bench 3.0, Terminal-Bench 2.1, CyberGym, BullshitBench v2, DeepSWE 1.1, and 6 more.

Available from

Decart—$0.09$0.181Mfp4
InferenceNet—$0.07$0.301M—
Morph—$0.098$0.391Mfp8
Sail Research—$0.08$0.401Mfp4
DeepInfra—$0.14$0.421Mfp8
AtlasCloud—$0.141$0.5641Mfp8
StreamLake—$0.141$0.5641Mfp8
DeepSeek—$0.15$0.601M—
CoreWeave—$0.20$0.651Mfp8
DigitalOcean—$0.18$0.721M—
GMICloud—$0.18$0.721Mfp8
Novita—$0.195$0.781Mfp8
NextBit—$0.21$0.841Mfp8
Phala—$0.21$0.841M—
Ionstream—$0.1386$1.151M—
Makora—$0.27$1.151Mfp8
Relace—$0.0268$1.201M—
Wafer—$0.06$1.201M—
Alibaba—$0.30$1.201M—
Baidu—$0.30$1.201Mfp8
BaseTen—$0.30$1.201Mfp8
Modal—$0.30$1.201M—
Parasail—$0.30$1.201Mfp8
SiliconFlow—$0.30$1.201Mfp8
Together—$0.30$1.201M—
Venice—$0.30$1.201Mfp8
OpenInference—$0.0368$1.321Mfp4
Reka—$0.18$1.801M—
Fireworksus$0.45$1.801M—
DekaLLM—$0.12$2.401M—
USD per 1M tokens

Benchmarks

Coding

NL2Repo-Bench
65.4%
#1
DeepSWE 1.1
74.2%
#4 of 32

Terminal & CLI

Terminal-Bench 3.0
30%
#1
Terminal-Bench 2.1
90.6%
#1
Terminal-Bench 4.0
31.2%
#12 of 21

Agentic & tool use

CyberGym
88.1%
#1
Agent's Last Exam
31.8%pass@1
#4 of 9
AutomationBench
54.8%
#2 of 16

Reasoning & science

Humanity's Last Exam
36.8%no tools
63.9%with tools
no tools
#12 of 22
with tools
#6 of 45
GPQA Diamond
90.9%
#14 of 59

Multimodal

Chartography
78.9%with tools
#4 of 5

Robustness

BullshitBench v2
57%
#26 of 84

Compare DeepSeek-V4.1-Flash with

DeepSeek-V4.1-Flash

About

DeepSeek-V4.1-Flash, released September 10, 2026, opened a new architecture family for the lab — and did it from the bottom, as the smallest model in the line rather than a flagship. DeepSeek described it as built for greater capability, faster inference and higher throughput, with the architecture meant to scale up to larger models still to come, and with native visual understanding rather than a vision encoder attached after the fact. On the lab's own harness it scored 90.6 on Terminal-Bench 2.1, 74.2 on DeepSWE v1.1 and 88.1 on CyberGym, all ahead of the larger V4-Pro-0813 from four weeks earlier, and 54.8 on AutomationBench. Terminal-Bench 3.0 at 30.0 and 4.0 at 31.2 were around two and a half times the V4-Pro-0813 figures on the same boards.

The visual side of the launch was the genuinely new part for DeepSeek, whose V3 and V4 lines had been text-only: the launch table reported 78.9 on Chartography and 89.6 on BabyVision, both run with tools, putting a DeepSeek model on multimodal boards for the first time. Reasoning was the softer spot — 36.8% on Humanity's Last Exam without tools, the one unstarred figure on a row where the other DeepSeek columns reported the text-only subset, while 63.9% with tools was the highest in the comparison. As with the July and August snapshots, the code-agent numbers came from DeepSeek's own unreleased harness and its figures for rival models did not always match those labs' published ones, so the chart reads best as a within-family comparison. Weights for this checkpoint are available under the MIT License on Hugging Face.

Frequently asked questions

DeepSeek-V4.1-Flash was released by DeepSeek on Thursday, Sep 10 2026.

All DeepSeek releases

23 tracked