Muse Spark Open vs Reflection Beam 1.0
Meta · US | Reflection AI · 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 Reflection Beam 1.0 for 501b-parameter sparse moe (about 23b active per token) with weights on hugging face under apache 2.0 or reflection claims 3-4x less inference compute than rival models (vendor claim).
Muse Spark Open (Meta) and Reflection Beam 1.0 (Reflection AI) 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. Reflection Beam 1.0 is reflection AI's first open-weight model - a 501B Apache 2.0 MoE announced October 5 with weights published October 16, 2026, pitched as a US alternative to Chinese open models. The breakdown below works through their capabilities and ideal use cases so you can match one to your task.
Key differences at a glance
- ▸Context window: both advertise 1M tokens (~1,500 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
Side-by-side specs
| Spec | Muse Spark Open | Reflection Beam 1.0 |
|---|---|---|
| Provider | Meta (US) | Reflection AI (US) |
| Released | October 15, 2026 | October 16, 2026 |
| Context window | 1M tokens (~1,500 pages) | 1M tokens (~1,500 pages) |
| Price (in/out) | Open weight (self-host / free) | Open weight (self-host / free) |
| 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
Reflection Beam 1.0 is comparatively weak here — text-only input; some users report reasoning loops on long agent runs
Artificial Analysis Intelligence Index of 39, first among US open-weight models
Muse Spark Open
Reflection Beam 1.0 is comparatively weak here — artificial Analysis Intelligence Index of 30, well below DeepSeek V4.1 Flash and GLM-5.3 (45)
About 143 output tokens/sec; up to 128K output tokens
Muse Spark Open
Reflection Beam 1.0 is comparatively weak here — self-hosting needs about 353 GB of GPU memory even at NVFP4, and kernels are CUDA-only for now
501B-parameter sparse MoE (about 23B active per token) with weights on Hugging Face under Apache 2.0
Reflection Beam 1.0
Muse Spark Open is comparatively weak here — muse Model License: attribution required and a revenue threshold (reported as about $20M; check the license text) before a separate license is needed
Reflection claims 3-4x less inference compute than rival models (vendor claim)
Reflection Beam 1.0
Muse Spark Open is comparatively weak here — weakest of the three Muse models (Wonder Full scores 56, Wonder 52)
Fast and cheap to run: Artificial Analysis measured about 385 output tokens/sec and $0.12 per index task
Reflection Beam 1.0
Reflection AI's first open-weight model - a 501B Apache 2.0 MoE announced October 5 with weights published October 16, 2026, pitched as a US alternative to Chinese open models — and it is the newer of the two.
Which should you pick?
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 501b-parameter sparse moe (about 23b active per token) with weights on hugging face under apache 2.0
→ Reflection Beam 1.0
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.
Reflection Beam 1.0: where it fits
Reflection AI's first open-weight model - a 501B Apache 2.0 MoE announced October 5 with weights published October 16, 2026, pitched as a US alternative to Chinese open models. Released October 16, 2026 by Reflection AI, it is built for 501B-parameter sparse MoE (about 23B active per token) with weights on Hugging Face under Apache 2.0, reflection claims 3-4x less inference compute than rival models (vendor claim), fast and cheap to run: Artificial Analysis measured about 385 output tokens/sec and $0.12 per index task, and third-party hosts list it from $0.25/$1.00 per million tokens (Nebius, as of Oct 27); Reflection's own API is in free beta.
Its trade-offs: artificial Analysis Intelligence Index of 30, well below DeepSeek V4.1 Flash and GLM-5.3 (45), text-only input; some users report reasoning loops on long agent runs, self-hosting needs about 353 GB of GPU memory even at NVFP4, and kernels are CUDA-only for now, and headline benchmarks come from Reflection's own model card; independent evaluation was limited at launch. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
The bottom line for this matchup
Muse Spark Open and Reflection Beam 1.0 overlap enough that the right pick depends on your specific job. 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, Reflection Beam 1.0 for 501b-parameter sparse moe (about 23b active per token) with weights on hugging face under apache 2.0. Rather than crowning one, run the same hard task through both once and let the results decide.
Want both Muse Spark Open and Reflection Beam 1.0 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 Reflection Beam 1.0 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 Reflection Beam 1.0 leans toward 501b-parameter sparse moe (about 23b active per token) with weights on hugging face under apache 2.0, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Muse Spark Open or Reflection Beam 1.0?
They are priced almost identically, so cost will not decide between them.
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 Reflection Beam 1.0 together?
Yes — a multi-model platform like LumiChats gives you Muse Spark Open, Reflection Beam 1.0 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 Reflection Beam 1.0?
Reflection Beam 1.0 — released October 16, 2026, about 1 days after Muse Spark Open.
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.