Muse Spark Open vs Microsoft Phi-4
Meta · US | Microsoft · US · 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 Microsoft Phi-4 for strong reasoning for a small 14b open-weight model or mit-licensed — fully self-hostable at no per-token cost. On a tight budget at scale, Muse Spark Open is the value pick.
Muse Spark Open (Meta) and Microsoft Phi-4 (Microsoft) are two of the models people most often weigh against each other in 2026. 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. Microsoft Phi-4 is microsoft's MIT-licensed 14B open model — strong reasoning for its size and very cheap, but a tiny 16K context and text-only. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
- ▸Context window: Muse Spark Open holds 61× more — 1M tokens (~1,500 pages) vs 16K (~25 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 21 months (released October 15, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
| Spec | Muse Spark Open | Microsoft Phi-4 |
|---|---|---|
| Provider | Meta (US) | Microsoft (US) |
| Released | October 15, 2026 | January 10, 2025 |
| Context window | 1M tokens (~1,500 pages) | 16K (~25 pages) |
| Price (in/out) | Open weight (self-host / free) | $0.07/$0.14 per 1M tokens |
| Open weight? | Yes — self-hostable | Yes — self-hostable |
| Modalities | text, image, video, audio, code | text, code |
| SWE-Bench Verified | Not published | Not published |
| MRCR v2 @ 1M | Not 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
Microsoft Phi-4 is comparatively weak here — text only — no image, audio or video input
Artificial Analysis Intelligence Index of 39, first among US open-weight models
Muse Spark Open
Microsoft Phi-4 is comparatively weak here — no first-party per-token API; hosted prices are third-party
About 143 output tokens/sec; up to 128K output tokens
Muse Spark Open
Its 1M tokens window holds about 61× more than Microsoft Phi-4's 16K in a single prompt.
Strong reasoning for a small 14B open-weight model
Microsoft Phi-4
Muse Spark Open is comparatively weak here — weakest of the three Muse models (Wonder Full scores 56, Wonder 52)
MIT-licensed — fully self-hostable at no per-token cost
Microsoft Phi-4
Muse Spark Open is comparatively weak here — needs about 1 TB of memory at 4-bit; no first-party per-token price confirmed
Runs on modest or local hardware
Microsoft Phi-4
Microsoft Phi-4 lists runs on modest or local hardware 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 Microsoft Phi-4's $0.07/$0.14 per 1M tokens.
Largest single-prompt input
Muse Spark Open
Its 1M tokens window is about 61× larger than Microsoft Phi-4's 16K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Muse Spark Open
At Open weight (self-host / free) it undercuts Microsoft Phi-4, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Muse Spark Open
Larger 1M tokens window fits more in one prompt.
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 strong reasoning for a small 14b open-weight model
→ Microsoft Phi-4
That is its strongest area.
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.
Microsoft Phi-4: where it fits
Microsoft's MIT-licensed 14B open model — strong reasoning for its size and very cheap, but a tiny 16K context and text-only. Released January 10, 2025 by Microsoft, it is built for strong reasoning for a small 14B open-weight model, mIT-licensed — fully self-hostable at no per-token cost, runs on modest or local hardware, and very cheap hosted inference at about $0.07/$0.14.
Its trade-offs: a tiny 16K context — by far the smallest window in this comparison, text only — no image, audio or video input, an early-2025 small model, outclassed on hard tasks by 2026 flagships, and no first-party per-token API; hosted prices are third-party. At $0.07 in / $0.14 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
Muse Spark Open and Microsoft Phi-4 overlap enough that the right pick depends on your specific job. Muse Spark Open costs less per token; Muse Spark Open holds the larger context; and each leads in its own area — Muse Spark Open for meta's first open-weight muse model - 816b-parameter moe with 42b active, accepting text, image, video and audio input, Microsoft Phi-4 for strong reasoning for a small 14b open-weight model. Rather than crowning one, run the same hard task through both once and let the results decide.
Want both Muse Spark Open and Microsoft Phi-4 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 Muse Spark Open or Microsoft Phi-4 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 Microsoft Phi-4 leans toward strong reasoning for a small 14b open-weight model, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Muse Spark Open or Microsoft Phi-4?
Muse Spark Open is cheaper — Open weight (self-host / free) vs $0.07/$0.14 per 1M tokens.
Which has the bigger context window?
Muse Spark Open — 1M tokens vs 16K, about 61× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Muse Spark Open and Microsoft Phi-4 together?
Yes — a multi-model platform like LumiChats gives you Muse Spark Open, Microsoft Phi-4 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 Microsoft Phi-4?
Muse Spark Open — released October 15, 2026, about 21 months after Microsoft Phi-4.
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.