MAI-1-preview vs Muse Spark Open

Microsoft · US  |  Meta · US · Updated June 2026

Quick verdict

Pick MAI-1-preview for microsoft's first fully in-house, end-to-end foundation model - a historic break from relying solely on openai or ranked in the top 15 on lm arena at launch. 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. Choose Muse Spark Open if you need self-hosting or data privacy; MAI-1-preview if you want a managed API.

MAI-1-preview (Microsoft) and Muse Spark Open (Meta) are two of the models people most often weigh against each other in 2026. MAI-1-preview is microsoft's first fully in-house foundation model - a strategic break from sole reliance on OpenAI, trained on ~15,000 H100 GPUs. 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. They diverge most on context window and open vs. closed weights — each quantified below from the models' real specs.

Key differences at a glance

Side-by-side specs

SpecMAI-1-previewMuse Spark Open
ProviderMicrosoft (US) Meta (US)
ReleasedAugust 28, 2025 October 15, 2026
Context window128K (~192 pages) 1M tokens (~1,500 pages)
Price (in/out)Not published Open weight (self-host / free)
Open weight?No — API only Yes — self-hostable
Modalitiestext, code text, image, video, audio, code
SWE-Bench VerifiedNot published Not published
MRCR v2 @ 1MNot published Not published

Who wins what

Microsoft's first fully in-house, end-to-end foundation model - a historic break from relying solely on OpenAI

MAI-1-preview

Muse Spark Open is comparatively weak here — weakest of the three Muse models (Wonder Full scores 56, Wonder 52)

Ranked in the top 15 on LM Arena at launch

MAI-1-preview

MAI-1-preview lists ranked in the top 15 on LM Arena at launch among its strengths; Muse Spark Open does not.

Trained on roughly 15,000 NVIDIA H100 GPUs, a genuine internal infrastructure investment

MAI-1-preview

MAI-1-preview lists trained on roughly 15,000 NVIDIA H100 GPUs, a genuine internal infrastructure investment 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

Open weights make this possible at all — MAI-1-preview is API-only, so it cannot leave the vendor's servers.

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 7.8× more than MAI-1-preview's 128K in a single prompt.

Largest single-prompt input

Muse Spark Open

Its 1M tokens window is about 7.8× larger than MAI-1-preview's 128K, 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.

A team with data-privacy or self-hosting needs

→ Muse Spark Open

Open weights let you run it on your own hardware; MAI-1-preview is API-only.

Anyone whose priority is microsoft's first fully in-house, end-to-end foundation model - a historic break from relying solely on openai

→ MAI-1-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.

MAI-1-preview: where it fits

Microsoft's first fully in-house foundation model - a strategic break from sole reliance on OpenAI, trained on ~15,000 H100 GPUs. Released August 28, 2025 by Microsoft, it is built for microsoft's first fully in-house, end-to-end foundation model - a historic break from relying solely on OpenAI, ranked in the top 15 on LM Arena at launch, trained on roughly 15,000 NVIDIA H100 GPUs, a genuine internal infrastructure investment, and rolled into Copilot alongside OpenAI models, giving Microsoft a real second option.

Its trade-offs are real: a 'preview' release, not yet positioned as Microsoft's primary Copilot model, no public per-token API pricing - not sold as a standalone product, and distinct from Microsoft's later MAI-Thinking-1 reasoning model - an earlier, more general-purpose entry.

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

The defining split here is open vs. closed. Muse Spark Open gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. MAI-1-preview gives you a managed, always-updated API with no infrastructure to run. Teams with GPUs, privacy requirements, or huge volume often favour the open model; teams that want zero ops and the latest capabilities favour the closed one. Capability is close enough that this operational question, not the benchmark, usually decides it.

Want both MAI-1-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 pricing

Frequently asked questions

Is MAI-1-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, MAI-1-preview leans toward microsoft's first fully in-house, end-to-end foundation model - a historic break from relying solely on openai 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, MAI-1-preview or Muse Spark Open?

Muse Spark Open is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while MAI-1-preview is API-metered at Not published. For most teams without GPUs, the API model is cheaper to start; at very high volume, self-hosting can win.

Which has the bigger context window?

Muse Spark Open — 1M tokens vs 128K, about 7.8× larger. Useful only if the model actually reasons over the full window, which not all do.

Can I use both MAI-1-preview and Muse Spark Open together?

Yes — a multi-model platform like LumiChats gives you MAI-1-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, MAI-1-preview or Muse Spark Open?

Muse Spark Open — released October 15, 2026, about 14 months after MAI-1-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.