Muse Wonder 1.0 vs Microsoft Phi-4
Meta · US | Microsoft · US · Updated June 2026
Quick verdict
Pick Muse Wonder 1.0 for meta superintelligence labs' first frontier-class reasoning model — a new line distinct from the agentic-coding-focused muse spark family or artificial analysis intelligence index score of 52 (a gated 'wonder full' subscription variant scores 56, tied with claude sonnet 5.5, behind only opus 5.5 at 58). 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. Choose Microsoft Phi-4 if you need self-hosting or data privacy; Muse Wonder 1.0 if you want a managed API.
Muse Wonder 1.0 (Meta) and Microsoft Phi-4 (Microsoft) are two of the models people most often weigh against each other in 2026. Muse Wonder 1.0 is meta Superintelligence Labs' October 12, 2026 debut frontier model — distinct from Muse Spark, scoring 52 on the independent Artificial Analysis Index with a 1M-token, four-modality context window. 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, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences at a glance
- ▸Price: Microsoft Phi-4 is about 57× cheaper on input ($0.07/$0.14 per 1M tokens vs $4/$20 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
- ▸Context window: Muse Wonder 1.0 holds 64× more — 1M tokens (~1,573 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 Wonder 1.0 is the newer model by about 21 months (released October 12, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
| Spec | Muse Wonder 1.0 | Microsoft Phi-4 |
|---|---|---|
| Provider | Meta (US) | Microsoft (US) |
| Released | October 12, 2026 | January 10, 2025 |
| Context window | 1M tokens (~1,573 pages) | 16K (~25 pages) |
| Price (in/out) | $4/$20 per 1M tokens | $0.07/$0.14 per 1M tokens |
| Open weight? | No — API only | Yes — self-hostable |
| Modalities | text, image, video, audio | text, code |
| SWE-Bench Verified | Not published | Not published |
| MRCR v2 @ 1M | Not published | Not published |
Who wins what
Meta Superintelligence Labs' first frontier-class reasoning model — a new line distinct from the agentic-coding-focused Muse Spark family
Muse Wonder 1.0
Microsoft Phi-4 is comparatively weak here — an early-2025 small model, outclassed on hard tasks by 2026 flagships
Artificial Analysis Intelligence Index score of 52 (a gated 'Wonder Full' subscription variant scores 56, tied with Claude Sonnet 5.5, behind only Opus 5.5 at 58)
Muse Wonder 1.0
Meta Superintelligence Labs' October 12, 2026 debut frontier model — distinct from Muse Spark, scoring 52 on the independent Artificial Analysis Index with a 1M-token, four-modality context window — and it carries the larger 1M tokens context.
78.8% on DeepSWE v1.1 long-horizon coding, ahead of both Claude Opus 5.5 (74.2%) and GPT-6 Astra (74.1%)
Muse Wonder 1.0
Its 1M tokens window holds about 64× more than Microsoft Phi-4's 16K in a single prompt.
Strong reasoning for a small 14B open-weight model
Microsoft Phi-4
Open weights make this possible at all — Muse Wonder 1.0 is API-only, so it cannot leave the vendor's servers.
MIT-licensed — fully self-hostable at no per-token cost
Microsoft Phi-4
At $0.07/$0.14 per 1M tokens it undercuts Muse Wonder 1.0 ($4/$20 per 1M tokens), and that gap compounds at volume.
Runs on modest or local hardware
Microsoft Phi-4
Microsoft's MIT-licensed 14B open model — strong reasoning for its size and very cheap, but a tiny 16K context and text-only — and it runs cheaper at $0.07/$0.14 per 1M tokens.
Lowest cost at scale
Microsoft Phi-4
At $0.07/$0.14 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
Muse Wonder 1.0
Its 1M tokens window is about 64× larger than Microsoft Phi-4's 16K, fitting roughly 1,573 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Microsoft Phi-4
At $0.07/$0.14 per 1M tokens it undercuts Muse Wonder 1.0, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Muse Wonder 1.0
Larger 1M tokens window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ Microsoft Phi-4
Open weights let you run it on your own hardware; Muse Wonder 1.0 is API-only.
Anyone whose priority is meta superintelligence labs' first frontier-class reasoning model — a new line distinct from the agentic-coding-focused muse spark family
→ Muse Wonder 1.0
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 Wonder 1.0: where it fits
Meta Superintelligence Labs' October 12, 2026 debut frontier model — distinct from Muse Spark, scoring 52 on the independent Artificial Analysis Index with a 1M-token, four-modality context window. Released October 12, 2026 by Meta, it is built for meta Superintelligence Labs' first frontier-class reasoning model — a new line distinct from the agentic-coding-focused Muse Spark family, artificial Analysis Intelligence Index score of 52 (a gated 'Wonder Full' subscription variant scores 56, tied with Claude Sonnet 5.5, behind only Opus 5.5 at 58), 78.8% on DeepSWE v1.1 long-horizon coding, ahead of both Claude Opus 5.5 (74.2%) and GPT-6 Astra (74.1%), and accepts text, image, video, audio, and PDF input against a 1,048,576-token context window.
Its trade-offs are real: the stronger 'Wonder Full' variant is gated behind $50/$200-per-month Muse Code subscriptions, with no public API or independently verifiable pricing, meta's full safety report had not been published as of launch, first release in a brand-new model family — no track record yet next to Meta's more established Muse Spark line, and benchmark comparisons against Opus 5.5 and GPT-6 Astra are Meta's own self-reported figures. At $4 in / $20 out per million tokens, it sits in the mid price band.
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
The defining split here is open vs. closed. Microsoft Phi-4 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Muse Wonder 1.0 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 Wonder 1.0 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 Wonder 1.0 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 Wonder 1.0 leans toward meta superintelligence labs' first frontier-class reasoning model — a new line distinct from the agentic-coding-focused muse spark family 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 Wonder 1.0 or Microsoft Phi-4?
Microsoft Phi-4 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Muse Wonder 1.0 is API-metered at $4/$20 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?
Muse Wonder 1.0 — 1M tokens vs 16K, about 64× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Muse Wonder 1.0 and Microsoft Phi-4 together?
Yes — a multi-model platform like LumiChats gives you Muse Wonder 1.0, 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 Wonder 1.0 or Microsoft Phi-4?
Muse Wonder 1.0 — released October 12, 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.