muse-spark-1-3-contributor
Muse Spark 1.3 Contributor is the cost-efficient contributor tier of Meta’s multimodal reasoning model, meant for experimentation, learning and early-stage agentic, multi-agent and coding workflows.
Pricing: Input 20 credits / 1M tokens (≈ $0.10), Output 40 credits / 1M tokens (≈ $0.20).
Prices updated
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This demo page does not include the full memory features of the client. For the complete experience, please use the client or the CLI.
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Muse Spark 1.3 Contributor API on ModelFold
Muse Spark 1.3 Contributor is the cost-efficient contributor tier of Meta’s multimodal reasoning model, meant for experimentation, learning and early-stage agentic, multi-agent and coding workflows. Try Muse Spark 1.3 Contributor in the ModelFold Playground, then call it from your own code through an OpenAI-compatible chat completions API.
What Is the Muse Spark 1.3 Contributor API
Muse Spark 1.3 Contributor at a glance
Muse Spark 1.3 Contributor is a chat model from Meta. It accepts text, images, video and files (such as PDF) as input and returns text, with a context window of up to 1M tokens.
Use it without hosting anything
On ModelFold you call Muse Spark 1.3 Contributor with a single API key — no model weights to download and no inference servers to run. The same key also works for the other chat, image, video and audio models on ModelFold.
Core Capabilities of Muse Spark 1.3 Contributor
Up to 1M tokens of context
Keep long conversations, large documents and sizeable code in a single request, so the model can reason over the full material instead of fragments.
Understands images, video and files (such as PDF)
Besides text, Muse Spark 1.3 Contributor accepts images, video and files (such as PDF) as input, so a single request can combine instructions with visual or other media.
Function calling
Muse Spark 1.3 Contributor supports tool (function) calling: describe your functions in the request and the model returns structured calls your code can run — the basis for agents and integrations.
Adjustable reasoning effort
Choose a reasoning effort level (low, medium or high) per request to balance depth of thinking against speed and token usage.
Structured outputs
Ask for JSON that follows a schema (response_format), which makes extraction, classification and system integrations more reliable.
How to Use Muse Spark 1.3 Contributor on ModelFold
- 1
Step 1: Try it in the Playground
Open the Playground at the top of this page, type a prompt and see how Muse Spark 1.3 Contributor responds before writing any code.
- 2
Step 2: Create an API key
Sign in to ModelFold and create an API key in the console. Keep it secret and send it as a Bearer token.
- 3
Step 3: Send a request
Call POST https://modelfold.ai/v1/chat/completions with "model": "muse-spark-1-3-contributor" and your messages. Existing OpenAI-compatible SDKs work by changing the base URL and key.
- ✓
Step 4: Ship and monitor
Integrate the response into your product and check token usage and spend for every call in the console logs.
What You Can Build with Muse Spark 1.3 Contributor
High-volume pipelines
Run classification, extraction, rewriting and batch jobs at scale where cost per request matters.
Autonomous agents
Build agents that plan multi-step tasks, call your tools and APIs, and keep working toward a goal across long sessions.
AI coding assistants
Generate, explain, debug and refactor code, review pull requests and work through multi-file changes in developer tools and IDE plugins.
Screenshot and image understanding
Read screenshots, charts, diagrams and photos alongside text — for UI review, visual QA or turning images into structured data.
Frequently Asked Questions
What is Muse Spark 1.3 Contributor?⌄
Muse Spark 1.3 Contributor is the cost-efficient contributor tier of Meta’s multimodal reasoning model, meant for experimentation, learning and early-stage agentic, multi-agent and coding workflows.
Which inputs does Muse Spark 1.3 Contributor support?⌄
Muse Spark 1.3 Contributor accepts text, images, video and files (such as PDF) and returns text. Through ModelFold you can send text and images (OpenAI-style image_url content); in the Playground you can also attach documents, which are converted to text.
How long is the context window of Muse Spark 1.3 Contributor?⌄
Up to 1M tokens, shared between your input and the model’s output.
Does Muse Spark 1.3 Contributor support function calling?⌄
Yes. Muse Spark 1.3 Contributor supports tools / function calling through the standard tools parameter of the chat completions API.
How is Muse Spark 1.3 Contributor billed on ModelFold?⌄
Pay as you go by tokens: input and output tokens are charged at the per-million-token prices shown on this page. There is no monthly fee, and failed requests are not charged.
How do I call Muse Spark 1.3 Contributor through the API?⌄
Send a POST request to https://modelfold.ai/v1/chat/completions with "model": "muse-spark-1-3-contributor", using your ModelFold API key as the Bearer token.
| Input | 20 credits 1M tokens≈ $0.10 |
| Output | 40 credits 1M tokens≈ $0.20 |
Billed per token: input and output are priced separately, and thinking tokens count as output. The Playground charges exactly the same way.
Read API docs →AI Agents · Claude Code / Cursor / Trae →curl https://modelfold.ai/v1/chat/completions \
-H "Authorization: Bearer $MODELFOLD_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"muse-spark-1-3-contributor","messages":[{"role":"user","content":"Hello"}]}'