Muse Spark Open vs DeepSeek-V4.1-Flash
Compare Muse Spark Open and DeepSeek-V4.1-Flash.
| Dimension | Muse Spark Open | DeepSeek-V4.1-Flash | Source |
|---|---|---|---|
| License | other (Muse Model License, limited commercial) | MIT (1017 LICENSE + card, 2026-10-19) | Official cards |
| Developer | Meta | DeepSeek | Official cards |
| Parameters | 816B total / 42B active sparse MoE | 552B backbone; 8B prefill / 16B decode; 196B Engram (README) | Official cards + docs |
| Modalities | Text + image + audio + video → text | Images + text in, text out | Meta docs; DeepSeek cards |
| Context length | 1,048,576 tokens | 1M tokens | Meta docs; DeepSeek README |
| Hardware (vendor) | ~700 GB VRAM (NVFP4) or ~2 TB (BF16); 4-GPU Blackwell or 8 × B300 | Not independently measured (1017 usedStorage ~475 GiB) | Meta docs; HF API 2026-10-19 |
| Gated | Yes (manual gate on HF) | No (open download) | Hugging Face |
| Hugging Face likes | 264 (as of 2026-10-16, BF16 repo) | 1,333 on -1017; 4,635 on original Flash card (2026-10-19) | Hugging Face |
| First seen | 2026-09-15 (HF card created) | 2026-09-10 original Flash; 2026-10-17 1017 card | Official hosts |
| Quality vs ChatGPT | Not independently tested (Meta blog "most capable US open-weight" is self-reported) | Not independently tested (vendor benchmarks are self-reported) | n/a |
When to choose which
- Native audio + video input (plus image): Muse Spark Open — Muse ingests text+image+audio+video. Flash natively processes images and text. No quality ranking.
- Permissive MIT weights / 1017 point release: DeepSeek-V4.1-Flash — MIT versus Muse Model License MaaS threshold. Not legal advice. Hardware untested by us.
- 1M context: Tie — Both cards/docs quote 1M context.
Read the entity pages: Muse Spark Open and DeepSeek-V4.1-Flash (1017 checkpoint). Both are listed on ChatGPT alternatives and closed LLM APIs.
This comparison was first published 2026-10-16 and re-verified 2026-10-19 against the MIT 1017 Flash card. Earlier draft rows that called Flash a 671B/37B text-only 128K model were wrong relative to the official README (552B backbone, 8B/16B active, images+text, 1M context) and have been corrected.
See also Beam vs Muse Spark Open and DeepSeek-V4.1-Flash vs Kimi K3.
FAQ
Which one is better for chat or coding?
We have no sourced bake-off. Meta blog "most capable" and DeepSeek vendor benchmarks are self-reported. Arena.ai WebDev open-source ranks are third-party, not a forkalt test.
Can I run both locally?
Both are datacenter-class downloads. Muse Spark Open needs 700 GB+ VRAM (NVFP4) or 2 TB (BF16) per Meta. Flash 1017 usedStorage is ~475 GiB; peak VRAM is not independently measured. Muse is gated.
Which license is better for commercial use?
DeepSeek-V4.1-Flash-1017 is MIT. Muse Model License requires attribution and has a $20M MaaS revenue threshold. Not legal advice; read LICENSE files.
Sources & verification
- https://huggingface.co/meta-models/Muse-Spark-Open-816B-A42B
- https://huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash-1017
- https://huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash
- https://research.meta.ai/blog/muse-spark-open
- https://dev.meta.ai/docs/muse-spark-open
- https://github.com/deepseek-ai/deepseek-recipe
License notes are not legal advice. Read the original LICENSE. Trademark & disclaimer.