M
META / meta-models/Muse-Spark-Open-816B-A42B

Muse Spark Open

Meta multimodal model released on October 15, 2026, with 816 billion total and 42 billion active parameters. It accepts text, images, audio and video and returns text. It has a combined one-million-token context and BF16 and NVFP4 variants.

01 / SUMMARY

The essential

ORIENTATIONMultimodal agents

Primary use stated or inferred cautiously from official documentation.

CONTEXT1,000,000 tokens

Maximum input capacity when published by the source.

EXITCombined context: 1,000,000 tokens

Documented maximum generation limit.

ACCESSHugging Face · approved access

Verified availability channels.

MODEL TYPEMultimodal · Code · Text and reasoning

Primary functional family and verified specialties.

LICENSEMuse Model License

Declared terms for API access, model weights, or self-hosting.

02 / TECHNICAL SHEET

Limits and integration

API IDmeta-models/Muse-Spark-Open-816B-A42B
Model typeMultimodal · Code · Text and reasoning
Access modelRestricted weights
LicenseMuse Model License
DeploymentSelf-hosted or third-party providers
Release15 OCT 2026
Knowledge cutoffNot published
EntranceText · Image · Audio · Video
ExitText
Context window1,000,000 tokens
maximum outputCombined context: 1,000,000 tokens
Reasoninglow / medium / high / xhigh
Published toolsFeatures
Structured OutingsNot published
Batch processingNot published
Prompt cacheNot published
Fine-tuningNot published
Verified platformsHugging Face · SGLang · vLLM · TensorRT-LLM
BEST SUITED FOR

Coding, reasoning and tool-using agents. Reasoning effort supports low, medium, high and xhigh; the default is xhigh. The guide recommends temperature 1 and top-p 1. Weights require access approval and large-scale infrastructure.

WORTH MONITORING

The Muse license is neither MIT nor Llama: it requires attribution and specific conditions for model-serving businesses. No weights were downloaded or terms accepted. BF16 and NVFP4 are formats of the same model, not two independent launches.

03 / CAPABILITIES

What it can do

01

Orientation

Coding, reasoning and tool-using agents. Reasoning effort supports low, medium, high and xhigh; the default is xhigh. The guide recommends temperature 1 and top-p 1. Weights require access approval and large-scale infrastructure.

02

Context

1,000,000 tokens · Combined context: 1,000,000 tokens

03

Tools and integration

Features

04

Access

Hugging Face · approved access

Input modalities
TextImageAudioVideo
04 / PRICES

Documented cost

ConceptWorthUnit/condition
Standard inputDepends on the providerStandard API rate
Cached inputNot publishedReading reused prefixes
Cache write or storageNot publishedThe condition varies by provider
Standard outputDepends on the providerMay include reasoning tokens
Batch inputNot publishedAsynchronous processing
Batch outputNot publishedAsynchronous processing

No single tariff has been verified: hosted APIs belong to third-party providers. The guide states about 700 GB of GPU memory for NVFP4 and 2 TB for BF16. Downloads do not remove infrastructure, operations or safety-review costs.

i Prices change and may depend on level, region or context length. Check the source before making a decision.

05 / EVALUATIONS

How to read the results

“

Meta-reported results with xhigh effort, temperature 1, top-p 1 and top-k disabled; not reproduced by Inferama. Preserve each test harness. Tool, coding and video metrics are not interchangeable and do not guarantee results for your own agent.

BenchmarkResultMetricSource
JobBench61,8Higher is betterView source ↗
MCP-Atlas89,2Higher is betterView source ↗
OSWorld Verified80,4Higher is betterView source ↗
Toolathlon Verified72,8Higher is betterView source ↗
GPQA Diamond89,0Higher is betterView source ↗
DeepSWE 1.1 (Preferred harness)60Higher is betterView source ↗
Terminal-Bench 2.1 (Terminus 2)76,4Higher is betterView source ↗
ZeroBench (con herramientas)50,0Higher is betterView source ↗
IntPhys268,3Higher is betterView source ↗
VideoMMEv261,5Higher is betterView source ↗

Inferama only highlights a “best result” when the metric, test set, configuration, and date allow for an equivalent comparison. The supplier's figures are presented as claims from its own source.

06 / VERSIONS

Chronology

BF16 / NVFP4

The Muse license is neither MIT nor Llama: it requires attribution and specific conditions for model-serving businesses. No weights were downloaded or terms accepted. BF16 and NVFP4 are formats of the same model, not two independent launches.

NVIDIA DFlash2

Auxiliary speculative-decoding checkpoint; requires the target model and is not a standalone assistant.

07 / SOURCES

Traceability