Muse Wonder 1.0 vs Particle-1
Meta · US | Particle AI · 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 Particle-1 for token-efficient coding model, post-trained with reinforcement learning on deepseek v4.1 flash or particle reports 72.57% task pass rate versus 71.15% for deepseek v4.1 flash, at $0.2211 versus $0.3368 per task. On a tight budget at scale, Particle-1 is the value pick.
Muse Wonder 1.0 (Meta) and Particle-1 (Particle AI) 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. Particle-1 is particle AI's October 28, 2026 debut - a closed, token-efficient coding model post-trained on DeepSeek V4.1 Flash, with 1M context at $0.25/$1.00 at peak rates. Their biggest split is price, and the breakdown below shows exactly how that plays out for your workload.
Key differences at a glance
- ▸Price: Particle-1 is about 16× cheaper on input ($0.25/$1 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: both advertise 1M tokens (~1,573 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
- ▸Recency: Particle-1 is the newer model by about 16 days (released October 28, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
| Spec | Muse Wonder 1.0 | Particle-1 |
|---|---|---|
| Provider | Meta (US) | Particle AI (US) |
| Released | October 12, 2026 | October 28, 2026 |
| Context window | 1M tokens (~1,573 pages) | 1M tokens (~1,573 pages) |
| Price (in/out) | $4/$20 per 1M tokens | $0.25/$1 per 1M tokens |
| Open weight? | No — API only | No — API only |
| Modalities | text, image, video, audio | text, image, 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
Particle-1 is comparatively weak here — aPI-only with no published weights, although its DeepSeek base model is open
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
Muse Wonder 1.0 lists 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) among its strengths; Particle-1 does not.
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
Muse Wonder 1.0 lists 78.8% on DeepSWE v1.1 long-horizon coding, ahead of both Claude Opus 5.5 (74.2%) and GPT-6 Astra (74.1%) among its strengths; Particle-1 does not.
Token-efficient coding model, post-trained with reinforcement learning on DeepSeek V4.1 Flash
Particle-1
Muse Wonder 1.0 is comparatively weak here — first release in a brand-new model family — no track record yet next to Meta's more established Muse Spark line
Particle reports 72.57% task pass rate versus 71.15% for DeepSeek V4.1 Flash, at $0.2211 versus $0.3368 per task
Particle-1
Particle AI's October 28, 2026 debut - a closed, token-efficient coding model post-trained on DeepSeek V4.1 Flash, with 1M context at $0.25/$1.00 at peak rates — and it runs cheaper at $0.25/$1 per 1M tokens.
Particle reports 28.4% to 52.2% fewer output tokens than the base model across four benchmarks
Particle-1
Particle AI's October 28, 2026 debut - a closed, token-efficient coding model post-trained on DeepSeek V4.1 Flash, with 1M context at $0.25/$1.00 at peak rates — and it is the newer of the two.
Lowest cost at scale
Particle-1
At $0.25/$1 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Particle-1
At $0.25/$1 per 1M tokens it undercuts Muse Wonder 1.0, and on millions of tokens that margin decides the monthly bill.
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 token-efficient coding model, post-trained with reinforcement learning on deepseek v4.1 flash
→ Particle-1
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.
Particle-1: where it fits
Particle AI's October 28, 2026 debut - a closed, token-efficient coding model post-trained on DeepSeek V4.1 Flash, with 1M context at $0.25/$1.00 at peak rates. Released October 28, 2026 by Particle AI, it is built for token-efficient coding model, post-trained with reinforcement learning on DeepSeek V4.1 Flash, particle reports 72.57% task pass rate versus 71.15% for DeepSeek V4.1 Flash, at $0.2211 versus $0.3368 per task, particle reports 28.4% to 52.2% fewer output tokens than the base model across four benchmarks, and peak API price of $0.25/$1.00 per million tokens, halved off-peak to $0.125/$0.50 (20:30-04:00 New York time).
Its trade-offs: aPI-only with no published weights, although its DeepSeek base model is open, all benchmarks are vendor-reported on Particle's own harness; none were independently reproduced as of October 31, and pricing is inconsistent across sources: Particle's launch post said $0.30/$1.20 and OpenRouter shows $0.05/$0.50, while its billing docs say $0.25/$1.00. At $0.25 in / $1 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
Muse Wonder 1.0 and Particle-1 overlap enough that the right pick depends on your specific job. Particle-1 costs less per token; and each leads in its own area — 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, Particle-1 for token-efficient coding model, post-trained with reinforcement learning on deepseek v4.1 flash. Rather than crowning one, run the same hard task through both once and let the results decide.
Want both Muse Wonder 1.0 and Particle-1 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 Particle-1 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 Particle-1 leans toward token-efficient coding model, post-trained with reinforcement learning on deepseek v4.1 flash, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Muse Wonder 1.0 or Particle-1?
Particle-1 is cheaper — $4/$20 per 1M tokens vs $0.25/$1 per 1M tokens, roughly 16× apart on input.
Which has the bigger context window?
Both advertise 1M tokens (~1,573 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Muse Wonder 1.0 and Particle-1 together?
Yes — a multi-model platform like LumiChats gives you Muse Wonder 1.0, Particle-1 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 Particle-1?
Particle-1 — released October 28, 2026, about 16 days after Muse Wonder 1.0.
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.