Beam vs Muse Spark Open: Which Should You Use?

Official Reflection artwork from the 16 October 2026 “Beam is now available” blog Open Graph image — Reflection official blog OG (16 October 2026). Source · License: Reflection product image.

Official Meta blog Open Graph artwork for Muse Spark Open Weights, blue flow lines on a pale field — Meta AI Research official blog OG. Source · License: Meta product image.

Verdict. Pick Reflection Beam if you want ungated Apache-2.0 text-only weights (501.3B/23.4B, 1M context) aimed at coding and long-horizon agents, plus Mirror CLI. Pick Muse Spark Open if you accept a manual Hugging Face gate and the Muse Model License for a natively multimodal 816B/42B MoE (text+image+audio+video). We have no sourced head-to-head quality test.

Compare Reflection Beam and Muse Spark Open.

Dimension	Reflection Beam	Muse Spark Open	Source
License	Apache-2.0 (ungated)	Muse Model License (SPDX other; limited commercial / MaaS threshold)	HF LICENSE files (2026-10-19 vs 2026-10-16)
Gating	No (click-through download)	Yes (manual gate)	Hugging Face API
Developer	Reflection	Meta	Official cards
Parameters	501.3B total / 23.4B active sparse MoE	816B total / 42B active sparse MoE	Official cards
Modalities	Text in / text out	Text + image + audio + video in / text out	Official cards
Context length	1,048,576 tokens	1,048,576 tokens	Official cards
Hardware (vendor)	NVFP4 ~280 GB weights; practical 4× B200 (720 GB) per HF blog	NVFP4 ≥700 GB VRAM (4-GPU Blackwell) or ~2 TB BF16 per Meta	HF Beam blog 2026-10-16; Meta docs 2026-10-16
Coding harness	Mirror CLI (Apache-2.0, reflection-oss/mirror, 180 GitHub stars)	Not a first-party terminal harness on the Muse card	GitHub + Reflection docs vs Muse card
Hugging Face likes	148 (BF16 card, 2026-10-19)	264 (BF16 card, 2026-10-16)	Hugging Face API
Weights opened	16 October 2026 (Reflection + HF blogs); card created 2026-10-07	15 October 2026 public post; card created 2026-09-15	Official blogs
Quality vs ChatGPT	Not independently tested	Not independently tested	n/a

When to choose which

Permissive ungated Apache-2.0 weights: Reflection Beam — Apache-2.0 versus Muse Model License MaaS threshold. Not legal advice.
Native image / audio / video input: Muse Spark Open — Beam’s card lists text only. No quality ranking.
Coding agent + first-party terminal harness: Reflection Beam — Mirror CLI is Apache-2.0 and defaults to Beam. Muse is a model card, not a CLI. Unmeasured.
Larger total-parameter multimodal MoE (816B/42B): Muse Spark Open — Gated manual access and limited commercial terms. Scale is not a quality score.

Read the entity pages: Reflection Beam and Muse Spark Open. Both are listed on ChatGPT alternatives and closed LLM APIs. Beam also hangs off Cursor alternatives.

Key differences

License and gating

Reflection Beam weights are ungated Apache-2.0 (HF LICENSE + card apache-2.0, checked 2026-10-19). Muse Spark Open is gated: manual under the Muse Model License (SPDX other), including a USD 20 million Model-as-a-Service notification threshold. Not legal advice.

Job and modalities

Beam: text-only sparse MoE (501.3B / 23.4B), 1M context, English predominantly, aimed at coding, reasoning, and agentic tool use. Ships with Mirror CLI (Apache-2.0, 180 GitHub stars on 2026-10-19).

Muse Spark Open: natively multimodal (text + image + audio + video → text), 816B / 42B, 1M context, datacenter-class Meta checkpoint.

Hardware (vendor)

Beam NVFP4 ~280 GB weights, practical 4× B200 (Hugging Face blog, 16 October 2026). Muse NVFP4 ≥700 GB VRAM / BF16 ~2 TB (Meta docs, 16 October 2026). Neither figure is a forkalt measurement.

Arena.ai snapshot (third-party)

Code Arena WebDev, open-source filter, page dated Oct 18, 2026 on the copy we opened:

Model (leaderboard name)	Open-source rank	Overall rank	Score	Note
Muse Spark Open (Max)	14	50	1524	muse-model-license
beam-1.0-501b-a23b	24	80	1437	Preliminary; Apache 2.0

That board is not a forkalt ranking. Votes, rank spreads, and hosted prices on Arena.ai are not copied into a quality verdict here.

How to choose

Need ungated Apache-2.0 text weights and a first-party coding CLI: Reflection Beam.
Need native image/audio/video input and accept gating + Muse Model License: Muse Spark Open.
Need MIT multimodal Fast/Flash-class weights instead: DeepSeek-V4.1-Flash.
Need NVIDIA ungated multimodal with OpenMDW-1.1: Nemotron 3.5 Super VL (vs Muse).

FAQ

Which one is better for coding?

We have no sourced bake-off. Beam’s card emphasizes coding, agentic tool use, and Mirror CLI. Muse’s card is natively multimodal. Arena.ai Code Arena WebDev (open-source filter, 2026-10-18 snapshot) lists Muse Spark Open (Max) above beam-1.0-501b-a23b on that board; both rows are third-party, and Beam’s row is marked preliminary. Not a forkalt ranking.

Can I run both locally?

Both are datacenter-class downloads. Beam NVFP4 is quoted at ~280 GB weights (practical 4× B200). Muse NVFP4 is quoted at ≥700 GB VRAM. Hardware not independently measured. Muse also requires accepting the license form before download.

Which license is better for commercial use?

Beam is Apache-2.0. Muse Model License requires “Built with Muse Spark Open” attribution and has a USD 20 million MaaS notification threshold. Not legal advice; read both LICENSE files.

Why compare these two?

Same-week US open-weight MoE drops (Muse public post 15 October 2026; Beam weights 16 October 2026), both 1M context, opposite license/gate/modality stories. DeepSeek already has its own vs Muse page on this site.

Sources & verification

Last verified 2026-10-19 · Last updated 2026-10-19· Edited by forkalt editors · Editorial policy

License notes are not legal advice. Read the original LICENSE. Trademark & disclaimer.