Atria Dawn Preview vs Muse Spark Open
Shanghai AI Laboratory · China | Meta · US · Updated June 2026
Quick verdict
Pick Atria Dawn Preview for best-in-class among tested models on several of shanghai ai lab's own benchmarks, including browsecomp (92.5, ahead of gpt-5.6 sol's 92.2) and deepsearchqa (96.0) or 744b-parameter moe built on a glm-5.2 base, released under a fully open mit license. Pick Muse Spark Open for meta's first open-weight muse model - 816b-parameter moe with 42b active, accepting text, image, video and audio input or artificial analysis intelligence index of 39, first among us open-weight models.
Atria Dawn Preview (Shanghai AI Laboratory, China) and Muse Spark Open (Meta, US) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. Atria Dawn Preview is a free, MIT-licensed 744B open-weight model from Shanghai AI Lab that beat GPT-5.6 Sol on the BrowseComp benchmark — released quietly, weights before paper. Muse Spark Open is meta's October 15, 2026 open-weight Muse Spark - an 816B/42B-active multimodal MoE with a 1M context under a gated Muse Model License. Their biggest split is context window, and the breakdown below shows exactly how that plays out for your workload.
Key differences at a glance
- ▸Context window: Muse Spark Open holds 3.8× more — 1M tokens (~1,500 pages) vs 256K tokens (~393 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
- ▸Recency: Muse Spark Open is the newer model by about 34 days (released October 15, 2026), usually meaning fresher training data and capabilities.
- ▸Ecosystem: this is a China-vs-US matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Side-by-side specs
| Spec | Atria Dawn Preview | Muse Spark Open |
|---|---|---|
| Provider | Shanghai AI Laboratory (China) | Meta (US) |
| Released | September 11, 2026 | October 15, 2026 |
| Context window | 256K tokens (~393 pages) | 1M tokens (~1,500 pages) |
| Price (in/out) | Open weight (self-host / free) | Open weight (self-host / free) |
| Open weight? | Yes — self-hostable | Yes — self-hostable |
| Modalities | text | text, image, video, audio, code |
| SWE-Bench Verified | Not published | Not published |
| MRCR v2 @ 1M | Not published | Not published |
Who wins what
Best-in-class among tested models on several of Shanghai AI Lab's own benchmarks, including BrowseComp (92.5, ahead of GPT-5.6 Sol's 92.2) and DeepSearchQA (96.0)
Atria Dawn Preview
Muse Spark Open is comparatively weak here — weakest of the three Muse models (Wonder Full scores 56, Wonder 52)
744B-parameter MoE built on a GLM-5.2 base, released under a fully open MIT license
Atria Dawn Preview
Muse Spark Open is comparatively weak here — muse Model License: attribution required and a revenue threshold (reported as about $20M; check the license text) before a separate license is needed
Free to self-host — no API pricing, run entirely on your own hardware
Atria Dawn Preview
Atria Dawn Preview lists free to self-host — no API pricing, run entirely on your own hardware among its strengths; Muse Spark Open does not.
Meta's first open-weight Muse model - 816B-parameter MoE with 42B active, accepting text, image, video and audio input
Muse Spark Open
Atria Dawn Preview is comparatively weak here — released quietly, with weights and an API posted to GitHub before Shanghai AI Lab's own technical report went up on arXiv days later
Artificial Analysis Intelligence Index of 39, first among US open-weight models
Muse Spark Open
Meta's October 15, 2026 open-weight Muse Spark - an 816B/42B-active multimodal MoE with a 1M context under a gated Muse Model License — and it carries the larger 1M tokens context.
About 143 output tokens/sec; up to 128K output tokens
Muse Spark Open
Its 1M tokens window holds about 3.8× more than Atria Dawn Preview's 256K tokens in a single prompt.
Largest single-prompt input
Muse Spark Open
Its 1M tokens window is about 3.8× larger than Atria Dawn Preview's 256K tokens, fitting roughly 1,500 pages in one prompt.
Which should you pick?
Someone analysing very long documents or codebases
→ Muse Spark Open
Larger 1M tokens window fits more in one prompt.
Anyone whose priority is best-in-class among tested models on several of shanghai ai lab's own benchmarks, including browsecomp (92.5, ahead of gpt-5.6 sol's 92.2) and deepsearchqa (96.0)
→ Atria Dawn Preview
It is specifically built for that.
Anyone whose priority is meta's first open-weight muse model - 816b-parameter moe with 42b active, accepting text, image, video and audio input
→ Muse Spark Open
That is its strongest area.
An enterprise with regional data-residency rules
→ Muse Spark Open or Atria Dawn Preview
Origin (China vs US) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
Atria Dawn Preview: where it fits
A free, MIT-licensed 744B open-weight model from Shanghai AI Lab that beat GPT-5.6 Sol on the BrowseComp benchmark — released quietly, weights before paper. Released September 11, 2026 by Shanghai AI Laboratory, it is built for best-in-class among tested models on several of Shanghai AI Lab's own benchmarks, including BrowseComp (92.5, ahead of GPT-5.6 Sol's 92.2) and DeepSearchQA (96.0), 744B-parameter MoE built on a GLM-5.2 base, released under a fully open MIT license, and free to self-host — no API pricing, run entirely on your own hardware.
Its trade-offs are real: context window is reported inconsistently across trackers — most list 256K tokens, at least one lists 1M; unconfirmed which is accurate, released quietly, with weights and an API posted to GitHub before Shanghai AI Lab's own technical report went up on arXiv days later, and a lab research preview rather than a commercial product — support and update cadence are unclear. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
Muse Spark Open: where it fits
Meta's October 15, 2026 open-weight Muse Spark - an 816B/42B-active multimodal MoE with a 1M context under a gated Muse Model License. Released October 15, 2026 by Meta, it is built for meta's first open-weight Muse model - 816B-parameter MoE with 42B active, accepting text, image, video and audio input, artificial Analysis Intelligence Index of 39, first among US open-weight models, and about 143 output tokens/sec; up to 128K output tokens.
Its trade-offs: weakest of the three Muse models (Wonder Full scores 56, Wonder 52), muse Model License: attribution required and a revenue threshold (reported as about $20M; check the license text) before a separate license is needed, and needs about 1 TB of memory at 4-bit; no first-party per-token price confirmed. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
The bottom line for this matchup
This is less "which is smarter" and more "which ecosystem fits." Atria Dawn Preview (China) and Muse Spark Open (US) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. The pragmatic move is to run one real task through both and judge the outputs against your own constraints — including where your data is allowed to be processed.
Want both Atria Dawn Preview and Muse Spark Open without two subscriptions? LumiChats gives you these plus 40+ models under one ₹69/day pass (about $1/day) — draft with one, cross-check with the other.
See pricingFrequently asked questions
Is Atria Dawn Preview or Muse Spark Open better for coding?
Public SWE-Bench figures are not available for either model, so the honest test is your own repository — run an identical real bug through both. By design, Atria Dawn Preview leans toward best-in-class among tested models on several of shanghai ai lab's own benchmarks, including browsecomp (92.5, ahead of gpt-5.6 sol's 92.2) and deepsearchqa (96.0) while Muse Spark Open leans toward meta's first open-weight muse model - 816b-parameter moe with 42b active, accepting text, image, video and audio input, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Atria Dawn Preview or Muse Spark Open?
They are priced almost identically, so cost will not decide between them.
Which has the bigger context window?
Muse Spark Open — 1M tokens vs 256K tokens, about 3.8× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Atria Dawn Preview and Muse Spark Open together?
Yes — a multi-model platform like LumiChats gives you Atria Dawn Preview, Muse Spark Open and 40+ others under one ₹69/day pass (about $1/day), so you can draft with one and cross-check with the other instead of buying two subscriptions.
Which is newer, Atria Dawn Preview or Muse Spark Open?
Muse Spark Open — released October 15, 2026, about 34 days after Atria Dawn Preview.
Related comparisons
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.