PyyanThe AI Index

Pyyan / Compare / Qwen3.8-Flash-Next vs DeepSeek V4.1 Flash

Qwen3.8-Flash-Next vs DeepSeek V4.1 Flash

2 of 5

Open-Weight Models · verified 13 Sept 2026

Qwen3.8-Flash-NextAlibabacurrent
DeepSeek V4.1 FlashDeepSeekcurrent
3 slots left
SpecificationQwen3.8-Flash-NextDeepSeek V4.1 Flash
SummaryThe most downloaded thing on Hugging Face right now, and a stated Qwen4 preview.Twice the parameters of the Flash it replaces, and cheaper to run.
Context262K native, ~1M extended1M
Input ($/Mtok)$0.15$0.3
Output ($/Mtok)$0.47$1.2
LicenceOpen weightsMIT
Max output32K256K
Parameters125B total, 6B active552B total, 8B / 16B active
Released26 Aug 202610 Sep 2026
Model IDQwen/Qwen3.8-Flash-Nextdeepseek-flash
CategoryOpen-Weight ModelsOpen-Weight Models
Official—DeepSeek ↗

Highlighted rows are where these differ.

Qwen3.8-Flash-Next

  • 125B total parameters with only 6B active per token
  • Alibaba describes it as a preview of the Qwen4 architecture
  • Top of the Hugging Face trending list, with a GGUF build close behind it

Best for open weights at speed.

Full spec sheet →

DeepSeek V4.1 Flash

  • 552B total, 8B active while reading the prompt and 16B while generating, with a 1M token context
  • DeepSeek says it beats V4-Pro; V4-Pro requests route to it from 14 September 2026
  • MIT licence, native image input, and a KV cache about a quarter the size of V4-Flash's

Best for cheap agentic coding with images.

Full spec sheet →