Muse Spark Open vs Qwen 3.7 Max

Meta · US  |  Alibaba · China · Updated June 2026

Quick verdict

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. Pick Qwen 3.7 Max for long-horizon agentic coding (swe-bench pro 60.6, terminal-bench 2.0 69.7) or 1m-token long-document and full-codebase analysis. Choose Muse Spark Open if you need self-hosting or data privacy; Qwen 3.7 Max if you want a managed API.

Muse Spark Open (Meta, US) and Qwen 3.7 Max (Alibaba, China) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. 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. Qwen 3.7 Max is alibaba's agent-first frontier model — a 1M-token context and long-horizon coding at about half the cost of US flagships. They diverge most on price and open vs. closed weights — each quantified below from the models' real specs.

Key differences at a glance

Side-by-side specs

SpecMuse Spark OpenQwen 3.7 Max
ProviderMeta (US) Alibaba (China)
ReleasedOctober 15, 2026 May 20, 2026
Context window1M tokens (~1,500 pages) 1M (~1,500 pages)
Price (in/out)Open weight (self-host / free) $2.5/$7.5 per 1M tokens
Open weight?Yes — self-hostable No — API only
Modalitiestext, image, video, audio, code text, code
SWE-Bench VerifiedNot published Not published
MRCR v2 @ 1MNot published Not published

Who wins what

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 — Qwen 3.7 Max 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

Qwen 3.7 Max is comparatively weak here — closed-weight, API-only — no self-hosting

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 its weights are open while Qwen 3.7 Max is API-only.

Long-horizon agentic coding (SWE-Bench Pro 60.6, Terminal-Bench 2.0 69.7)

Qwen 3.7 Max

Qwen 3.7 Max lists long-horizon agentic coding (SWE-Bench Pro 60.6, Terminal-Bench 2.0 69.7) among its strengths; Muse Spark Open does not.

1M-token long-document and full-codebase analysis

Qwen 3.7 Max

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

MCP tool orchestration and multi-hour autonomous runs

Qwen 3.7 Max

Qwen 3.7 Max lists mCP tool orchestration and multi-hour autonomous runs among its strengths; Muse Spark Open does not.

Lowest cost at scale

Muse Spark Open

Its weights are open, so at volume you pay for your own hardware instead of Qwen 3.7 Max's $2.5/$7.5 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 Qwen 3.7 Max, and on millions of tokens that margin decides the monthly bill.

A team with data-privacy or self-hosting needs

→ Muse Spark Open

Open weights let you run it on your own hardware; Qwen 3.7 Max is API-only.

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

It is specifically built for that.

Anyone whose priority is long-horizon agentic coding (swe-bench pro 60.6, terminal-bench 2.0 69.7)

→ Qwen 3.7 Max

That is its strongest area.

An enterprise with regional data-residency rules

→ Muse Spark Open or Qwen 3.7 Max

Origin (US vs China) affects where data is processed and which compliance regime applies — check the provider's terms for your region.

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 are real: 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.

Qwen 3.7 Max: where it fits

Alibaba's agent-first frontier model — a 1M-token context and long-horizon coding at about half the cost of US flagships. Released May 20, 2026 by Alibaba, it is built for long-horizon agentic coding (SWE-Bench Pro 60.6, Terminal-Bench 2.0 69.7), 1M-token long-document and full-codebase analysis, mCP tool orchestration and multi-hour autonomous runs, and frontier intelligence at roughly half the price of US flagships.

Its trade-offs: text-only — no vision input (the Plus variant adds images), closed-weight, API-only — no self-hosting, trails GPT-5.5 and Claude Opus on the hardest one-shot reasoning, and chinese-jurisdiction data-residency considerations. At $2.5 in / $7.5 out per million tokens, it sits in the mid price band.

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. Qwen 3.7 Max 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 Muse Spark Open and Qwen 3.7 Max 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 Muse Spark Open or Qwen 3.7 Max 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, 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 while Qwen 3.7 Max leans toward long-horizon agentic coding (swe-bench pro 60.6, terminal-bench 2.0 69.7), and that positioning usually predicts which feels better on your codebase.

Which is cheaper, Muse Spark Open or Qwen 3.7 Max?

Muse Spark Open is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Qwen 3.7 Max is API-metered at $2.5/$7.5 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?

Both advertise 1M tokens (~1,500 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.

Can I use both Muse Spark Open and Qwen 3.7 Max together?

Yes — a multi-model platform like LumiChats gives you Muse Spark Open, Qwen 3.7 Max 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, Muse Spark Open or Qwen 3.7 Max?

Muse Spark Open — released October 15, 2026, about 5 months after Qwen 3.7 Max.

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.