About
Muse Spark 1.3 Contributor is the cost-efficient contributor tier of Meta’s multimodal reasoning model for experimentation, learning, and early-stage agentic, multi-agent, and coding workflows.
Pricing
| Input | $0.14 | per 1M prompt tokens |
|---|---|---|
| Output | $0.28 | per 1M generated tokens, reasoning included |
| Cached input | <$0.01 | per 1M tokens read back from the prompt cache |
| Web search | $0.0035 | per request that uses the provider’s built-in search |
What a request costs
| Typical request | Each | Per 1,000 |
|---|---|---|
| Short chat reply1,500 in · 400 out | $0.0003 | $0.322 |
| Question over a long document40,000 in · 800 out | $0.0058 | $5.82 |
| Agent tool step20,000 in · 1,200 out | $0.0031 | $3.14 |
At the developer-API rate, before any provider promotion or prompt-cache saving. In the app, the model picker shows what a message costs on your plan before you send it.
Call it from code
OpenAI-compatible: point any OpenAI SDK at https://api.privateer.pro/v1 and set
model. Keys are created in the app under Settings.
cURL
curl https://api.privateer.pro/v1/chat/completions \
-H "Authorization: Bearer $PRIVATEER_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "meta/muse-spark-1.3-contributor",
"messages": [{ "role": "user", "content": "Hello" }]
}'
Python
import os
from openai import OpenAI
client = OpenAI(
base_url="https://api.privateer.pro/v1",
api_key=os.environ["PRIVATEER_API_KEY"],
)
reply = client.chat.completions.create(
model="meta/muse-spark-1.3-contributor",
messages=[{"role": "user", "content": "Hello"}],
)
print(reply.choices[0].message.content)
JavaScript
import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://api.privateer.pro/v1",
apiKey: process.env.PRIVATEER_API_KEY,
});
const reply = await client.chat.completions.create({
model: "meta/muse-spark-1.3-contributor",
messages: [{ role: "user", content: "Hello" }],
});
console.log(reply.choices[0].message.content);
Parameters this model accepts
include_reasoningmax_tokensreasoningreasoning_effortrepetition_penaltyresponse_formatstructured_outputstemperaturetool_choicetoolstop_ktop_p