Mistral Large 4 vs Muse Spark Open

Official Mistral Large 4 Artificial Analysis Coding Agent Index figure from the Hugging Face card — mistralai/Mistral-Large-4-1T-A52B images/coding_index.png. Source · License: Mistral card 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 Mistral Large 4 if you want ungated Mistral Ecosystem Open-Weight multimodal MoE weights (~1T total / 52B active including embeddings; text + image in; 1M context; FP8 + NVFP4). Pick Muse Spark Open if you accept a manual Hugging Face gate and the Muse Model License for Meta’s natively multimodal 816B/42B MoE (text + image + audio + video in). MaaS rules differ. We have no sourced bake-off.

Compare Mistral Large 4 and Muse Spark Open.

Dimension	Mistral Large 4	Muse Spark Open	Source
License	Mistral Ecosystem Open-Weight (modified MIT; MaaS needs a separate Mistral commercial license)	Muse Model License (SPDX other; MaaS + USD 20M revenue notification)	LICENSE files (2026-10-30 / 2026-10-16)
Gating	No	Yes (manual)	Hugging Face API
Developer	Mistral AI	Meta	Official cards
Parameters	~1T total; 49B active/token; 52B including embeddings (card)	816B total / 42B active sparse MoE	Official cards
Modalities	Text + image in, text out	Text + image + audio + video in, text out	Official cards
Context length	1M tokens	1,048,576 tokens	Official cards
Official quants opened	FP8 lead card + NVFP4 sibling (both ungated)	BF16 lead card + NVFP4 sibling (both gated)	Hugging Face API
Hardware (vendor)	Datacenter; vLLM example TP8. FP8 usedStorage ~1.06 TB. Untested here.	NVFP4 ≥700 GB VRAM (card); ~2 TB BF16 (Meta docs). Untested here.	Official cards / Meta docs
Hugging Face likes	1,301 on the FP8 card (2026-10-30)	264 on the BF16 card (2026-10-16)	Hugging Face API
Quality vs ChatGPT	Not independently tested	Not independently tested	n/a

When to choose which

Ungated download (no Hugging Face access form): Mistral Large 4 — Both Mistral cards were gated false on 2026-10-30. Muse is gated manual.
Native audio and video input: Muse Spark Open — Muse card is text+image+audio+video. Mistral card is text+image. Not a quality rank.
Modified-MIT grant with a defined MaaS carve-out for internal use: Mistral Large 4 — Read both LICENSE files. Muse has a USD 20 million MaaS notification threshold. Not legal advice.
Meta-hosted / Apple MLX two-Mac-Studio vendor path: Muse Spark Open — Copied from Meta docs and blog. Not a forkalt run.

Read the entity pages: Mistral Large 4 and Muse Spark Open. Both hang off ChatGPT alternatives and closed LLM APIs. Mistral also hangs off Claude Code alternatives because the card names coding/agent recipes and Mistral Vibe — that is editorial, not a Claude Code clone.

Why this comparison exists

Searchers who want a recent open-weight frontier multimodal MoE now have Mistral’s ungated Le Chonk card next to Meta’s gated Muse Spark Open. Same job family (long-context multimodal chat weights). Different gate, license, and input modalities (Mistral is text+image; Muse adds audio and video). This is identification, not a bake-off.

Sourced snapshot (2026-10-30 / 2026-10-16)

Field	Mistral Large 4	Muse Spark Open
Host	huggingface.co/mistralai/Mistral-Large-4-1T-A52B (not gated)	huggingface.co/meta-models/Muse-Spark-Open-816B-A42B (gated: manual)
HF likes	1,301 (2026-10-30)	264 (2026-10-16)
License	Ecosystem Open-Weight (modified MIT; MaaS extra license)	Muse Model License (MaaS + USD 20M notify)
Size	~1T / 49B per token / 52B with embeddings	816B / 42B
Job	Text + image in, text out	Text + image + audio + video in, text out
Context	1M	1,048,576
NVFP4 sibling	Ungated	Gated manual
Quality vs ChatGPT	Not independently tested	Not independently tested

License

Mistral: Mistral Ecosystem Open-Weight License — modified MIT; MaaS needs a separate commercial license with Mistral; internal use is carved out. Muse: Muse Model License — “Built with Muse Spark Open” attribution; MaaS plus USD 20 million aggregate revenue in any consecutive 12 months requires notifying Meta. Not legal advice.

How to choose

Need ungated Mistral weights (FP8 or NVFP4) and can accept the Ecosystem Open-Weight MaaS clause: Mistral Large 4.
Need native audio/video input and can accept a manual gate: Muse Spark Open.
Need ungated Apache-2.0 text MoE instead: Reflection Beam — Beam vs Muse Spark Open.
Need ungated MIT multimodal (552B backbone): DeepSeek-V4.1-Flash.
Need a self-hosted chat UI, not weights: Open WebUI vs ChatGPT.

See also comparisons and AI Chat & Agents.

FAQ

Which model is smaller / easier to host?

Both are datacenter-class. Mistral’s published vLLM recipe uses tensor parallel 8; FP8 usedStorage is ~1.06 TB. Muse quotes ≥700 GB VRAM for NVFP4. We have not measured peak VRAM for either.

Which one scores higher?

We have no sourced bake-off. Mistral’s Artificial Analysis / FrontierCode / Cyber Index rows and Muse’s JobBench / MCP-Atlas tables stay self-reported. Do not merge those tables.

Can I offer either as a hosted API?

Mistral’s Ecosystem Open-Weight License requires a separate commercial license for Model-as-a-Service. Muse’s Model License has a USD 20 million MaaS notification threshold. Read the files. Not legal advice.

Why this pairing?

Both are recent open-weight frontier multimodal MoEs already (or now) on this site, with 1M context and NVFP4 siblings. Same search class, different gates and licenses.

Sources & verification

Last verified 2026-10-30 · Last updated 2026-10-30· Edited by forkalt editors · Editorial policy

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