PyyanThe AI Index

Pyyan / Compare / DeepSeek V4.1 Flash vs Muse Spark Open

DeepSeek V4.1 Flash vs Muse Spark Open

2 of 5

Open-Weight Models · verified 20 Oct 2026

DeepSeek V4.1 FlashDeepSeekcurrent
Muse Spark OpenMetacurrent
3 slots left
SpecificationDeepSeek V4.1 FlashMuse Spark Open
SummaryTwice the parameters of the Flash it replaces, and cheaper to run.The largest American open weights, under a licence with a revenue trigger.
Context1M1M
Input ($/Mtok)$0.3Weights only
Output ($/Mtok)$1.2Weights only
LicenceMITMuse Model License
Max output256KNot published
Parameters552B total, 8B / 16B active816B total, 42B active
Released10 Sep 2026, refreshed 17 Oct15 Oct 2026
Model IDdeepseek-flashmeta-models/Muse-Spark-Open-816B-A42B
CategoryOpen-Weight ModelsOpen-Weight Models
OfficialDeepSeek ↗Meta ↗

Highlighted rows are where these differ.

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
  • Refreshed on 17 October as V4.1-Flash-1017, still MIT, improving on all eleven benchmarks DeepSeek published

Best for cheap agentic coding with images.

Full spec sheet →

Muse Spark Open

  • Text, image, video and audio in, text out, with a 1M token context
  • Muse Model License, not open source: attribution required, and a separate agreement above $20m of model-service revenue
  • About 1.5TB in BF16, or two Mac Studios at 4-bit

Best for multimodal work you host yourself.

Full spec sheet →