---
title: "Muse Spark Open"
url: "https://handyai.news/modeldrop/muse-spark-open"
published: "2026-10-15T17:00:00.000Z"
section: "Model Drop"
description: "Muse Spark Open, which Meta released on October 15, 2026, is the open-weights version of Muse Spark: an 816B-parameter mixture-of-experts model with 42B…"
publisher: "handyai.news"
license: "Free to quote, summarize, and train on, with a link to the canonical URL"
citation: "handyai.news, \"Muse Spark Open,\" October 15, 2026, https://handyai.news/modeldrop/muse-spark-open."
comments: "https://handyai.news/api/article/82343/comments"
---

# Muse Spark Open

*Published October 15, 2026 · Model Drop*

Muse Spark Open, which Meta released on October 15, 2026, is the open-weights version of Muse Spark: an 816B-parameter mixture-of-experts model with 42B active, built for coding and agents and small enough to run on two Mac Studios.

- Model: Muse Spark Open (`meta-models/Muse-Spark-Open-816B-A42B`)
- Maker: Meta
- Ship date: October 15, 2026
- Pricing: Free (open weights)
- Context: 1M tokens
- Weights: Open (Muse Model License, Hugging Face)
- Where you can use it: Hugging Face weights, BF16 and NVFP4
- OpenRouter, Together AI, Groq, Fireworks

**When to reach for it**:

- Self-hosted coding and tool-calling agents
- Frontier-class model on two Mac Studios
- Skip it if you resell model access at scale

**How it compares**:

- Leads GLM-5.3 and Kimi K3 on tool use
- Trails both on coding and overall

**What makes it different**:

- Text, image, video and audio input
- Extra safety training for open release

**Early reactions**: Hacker News cheered a big US open-weight release but argued over the license, which makes API sellers above $20M in revenue sign a deal with Meta, and pointed out it scores below GLM-5.3 on Artificial Analysis.

**Read more**: [Introducing Muse Spark Open](https://research.meta.ai/blog/muse-spark-open), [Hugging Face model card](https://huggingface.co/meta-models/Muse-Spark-Open-816B-A42B), [Evaluation methodology](https://research.meta.ai/static/muse-spark-open-evaluation-methodology)

## The benchmarks

Meta ran Muse Spark Open at xhigh reasoning effort and compared it only with open-weight models (Qwen3.8-2.4T-A95B at xhigh, GLM-5.3 and Kimi K3 at max, plus Mistral Large 4, Nemotron 3 Ultra, Inkling and Beam on some rows); coding scores use each model's preferred harness and Terminal-Bench uses the Terminus 2 agent.

#### Meta's numbers

- MCP Atlas (tool use over MCP): 89.2%. +4.7 over Qwen3.8-2.4T-A95B (84.5%), +5.0 over GLM-5.3 (84.2%), +6.9 over Kimi K3 (82.3%).
- JobBench (professional tool use): 61.8. +9.1 over Qwen3.8-2.4T-A95B (52.7), +0.4 over GLM-5.3 (61.4), +7.5 over Kimi K3 (54.3).
- GDPval-AA v2 (office task Elo): 1401. −23 under Mistral Large 4 (1424), −212 under Qwen3.8-2.4T-A95B (1613), −252 under GLM-5.3 (1653), −136 under Kimi K3 (1537).
- DeepSWE v1.1 (long-horizon agentic coding): 60%. −2 under Mistral Large 4 (62%), +3 over Qwen3.8-2.4T-A95B (57%), −7 under GLM-5.3 (67%), −8 under Kimi K3 (68%).
- Terminal-Bench 2.1 (Terminus 2 agent): 76.4%. −5.6 under Qwen3.8-2.4T-A95B (82.0%), −7.5 under GLM-5.3 (83.9%), −8.6 under Kimi K3 (85.0%).
- HLE-Diamond (no tools) (hardest expert questions): 26.1%. +8.8 over Qwen3.8-2.4T-A95B (17.3%), +9.7 over GLM-5.3 (16.4%), +3.9 over Kimi K3 (22.2%).
- GPQA Diamond (PhD-level science): 89.0%. −4.5 under Qwen3.8-2.4T-A95B (93.5%), −2.7 under GLM-5.3 (91.7%), −4.5 under Kimi K3 (93.5%).
- ZeroBench (with tools) (hard visual reasoning): 50.0%. +36.0 over Inkling (14.0%), +9.0 over Kimi K3 (41.0%).

#### Independent numbers

- Artificial Analysis Intelligence Index (current v4.3.2): 38.9. −5.9 under GLM-5.3 (44.8), −4.7 under Kimi K3 (43.6), −1.0 under Qwen3.8-2.4T-A95B (39.9), +0.5 over Mistral Large 4 (38.4).


---

Source: https://handyai.news/modeldrop/muse-spark-open

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