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Muse Spark Open

Ready
model path:accounts/fireworks/models/muse-spark-open

Muse Spark Open is an open weights reasoning model from Meta for coding and agentic workflows. It supports tool calling and native image understanding in a single checkpoint. It uses a sparse Mixture-of-Experts architecture with 816B total / 42B active parameters, routing each token to 8 of 256 experts, and hybrid attention that repeats three sliding-window layers (2,048-token window) for every full-attention layer. Inputs: text and images. Output: text.

→ Serverless: Available on serverless on US-only capacity at standard serverless pricing, with no US-only premium.
→ Production: For dedicated capacity, deploy on-demand or move to reserved throughput.
→ Fine-tuning: Train LoRA adapters through the Serverless Training API using base model accounts/fireworks/models/muse-spark-open-nvfp4. Managed fine-tuning in the Fireworks UI isn’t available for this model yet. Fine-tuned models deploy on-demand.

Muse Spark Open API Features

Serverless

Docs

Muse Spark Open is available via Fireworks' serverless API, where you pay per token. There are several ways to call the Fireworks API, including Fireworks' Python client, the REST API, or OpenAI's Python client.

On-demand Deployment

Docs

On-demand deployments allow you to use Muse Spark Open on dedicated GPUs with Fireworks' high-performance serving stack with high reliability and no rate limits.

Available Serverless

$1.25 / $0.15 / $4.25

Run queries immediately, pay only for usage

Per 1M Tokens (input/cached input/output)

Metadata

State
Ready
Created on
14 OCT, 2026
Kind
Base model
Provider
Meta

Specifications

Calibrated
No
Mixture-of-Experts
Yes
Parameters
816B

Supporting Functionality

Fine-tuning
Not Supported
Serverless
Supported
Context Length
1040k tokens
Function Calling
Supported
Embeddings
Not Supported
Rerankers
Not Supported
Supporting image input
Supported