Gemini 3.1 Pro vs Muse Spark Open

Google · US  |  Meta · US · Updated June 2026

Quick verdict

Pick Gemini 3.1 Pro for full multimodal input — text, image, audio and video in one 1m-token window or long video and document analysis. 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; Gemini 3.1 Pro if you want a managed API.

Gemini 3.1 Pro (Google) and Muse Spark Open (Meta) are two of the models people most often weigh against each other in 2026. Gemini 3.1 Pro is a 1M-token multimodal workhorse — huge breadth across text, image, audio and video, but recall fades deep in the window. 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 price, context window and open vs. closed weights — each quantified below from the models' real specs.

Key differences at a glance

Side-by-side specs

SpecGemini 3.1 ProMuse Spark Open
ProviderGoogle (US) Meta (US)
ReleasedFebruary 19, 2026 October 15, 2026
Context window1M (~1,573 pages) 1M tokens (~1,500 pages)
Price (in/out)$2/$12 per 1M tokens Open weight (self-host / free)
Open weight?No — API only Yes — self-hostable
Modalitiestext, image, audio, video, code text, image, video, audio, code
SWE-Bench VerifiedNot published Not published
MRCR v2 @ 1M26.3% Not published

Who wins what

Full multimodal input — text, image, audio and video in one 1M-token window

Gemini 3.1 Pro

Muse Spark Open is comparatively weak here — needs about 1 TB of memory at 4-bit; no first-party per-token price confirmed

Long video and document analysis

Gemini 3.1 Pro

Gemini 3.1 Pro lists long video and document analysis among its strengths; Muse Spark Open does not.

Agentic reasoning (high ARC-AGI-2)

Gemini 3.1 Pro

Gemini 3.1 Pro lists agentic reasoning (high ARC-AGI-2) 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 — Gemini 3.1 Pro 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 its weights are open while Gemini 3.1 Pro is API-only.

About 143 output tokens/sec; up to 128K output tokens

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 is the newer of the two.

Lowest cost at scale

Muse Spark Open

Its weights are open, so at volume you pay for your own hardware instead of Gemini 3.1 Pro's $2/$12 per 1M tokens.

Which should you pick?

A cost-sensitive startup shipping high volume

→ Muse Spark Open

At Open weight (self-host / free) it undercuts Gemini 3.1 Pro, and on millions of tokens that margin decides the monthly bill.

Someone analysing very long documents or codebases

→ Gemini 3.1 Pro

Larger 1M 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; Gemini 3.1 Pro is API-only.

Anyone whose priority is full multimodal input — text, image, audio and video in one 1m-token window

→ Gemini 3.1 Pro

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.

Gemini 3.1 Pro: where it fits

A 1M-token multimodal workhorse — huge breadth across text, image, audio and video, but recall fades deep in the window. Released February 19, 2026 by Google, it is built for full multimodal input — text, image, audio and video in one 1M-token window, long video and document analysis, agentic reasoning (high ARC-AGI-2), and broad multimodal understanding across formats.

Its trade-offs are real: long-context recall drops sharply past 256K (26.3% on MRCR v2 at 1M), premium price per token at $2/$12, and superseded within Google's own line by the newer 3.5/3.6 Flash releases for cost-sensitive work. At $2 in / $12 out per million tokens, it sits in the mid price band.

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. Gemini 3.1 Pro 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 Gemini 3.1 Pro 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 Gemini 3.1 Pro 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, Gemini 3.1 Pro leans toward full multimodal input — text, image, audio and video in one 1m-token window 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, Gemini 3.1 Pro or Muse Spark Open?

Muse Spark Open is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Gemini 3.1 Pro is API-metered at $2/$12 per 1M tokens. 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?

Effectively neither — 1M vs 1M tokens is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.

Can I use both Gemini 3.1 Pro and Muse Spark Open together?

Yes — a multi-model platform like LumiChats gives you Gemini 3.1 Pro, 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, Gemini 3.1 Pro or Muse Spark Open?

Muse Spark Open — released October 15, 2026, about 8 months after Gemini 3.1 Pro.

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.