Muse Spark 1.3
Where it stands
Quality in independent tests against price, next to 135 other models. Up means more capable, left means cheaper.
About this model
Muse Spark 1.3 is an AI model from Meta, made available through the API on September 2, 2026. It can read up to 1,048,576 tokens in one request, roughly 1,966 pages of text, and write up to 943,718 tokens in a single answer. Besides text, it accepts images, video and files such as PDFs as input.
Through the API it costs $1.25 per million input tokens and $4.25 per million output tokens. Its pricing sits in the middle of the market.
It supports extended reasoning: it can "think" step by step before answering, which helps on maths, code and complex questions. It can call tools and functions, so developers can connect it to search, databases or other software.
Quality scores
Rankings →- AIME mathCompetition-level math problems in the style of the American Invitational Mathematics Examination. Share solved.99.2%#9 of 112
- FrontierMathOriginal, unpublished math problems written by professional mathematicians, from advanced to research level. Share solved.74.4%#16 of 73
Where to use it
Companies that serve this model through an API: 1. Prices per million tokens, cheapest first.
Availability and prices come from OpenRouter’s public API and are refreshed daily. Uptime is the share of successful requests over the last 24 hours. Some providers run a compressed version of open models (fp8, int4), which is cheaper but can be slightly less accurate.
Use it in your code
Call Muse Spark 1.3 through OpenRouter’s OpenAI-compatible API: create a key on openrouter.ai, then run one of these examples.
curl https://openrouter.ai/api/v1/chat/completions \
-H "Authorization: Bearer $OPENROUTER_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model": "meta/muse-spark-1.3", "messages": [{"role": "user", "content": "Hello! What can you do?"}]}'import os
from openai import OpenAI
client = OpenAI(base_url="https://openrouter.ai/api/v1", api_key=os.environ["OPENROUTER_API_KEY"])
reply = client.chat.completions.create(
model="meta/muse-spark-1.3",
messages=[{"role": "user", "content": "Hello! What can you do?"}],
)
print(reply.choices[0].message.content)import OpenAI from "openai";
const client = new OpenAI({ baseURL: "https://openrouter.ai/api/v1", apiKey: process.env.OPENROUTER_API_KEY });
const reply = await client.chat.completions.create({
model: "meta/muse-spark-1.3",
messages: [{ role: "user", content: "Hello! What can you do?" }],
});
console.log(reply.choices[0].message.content);The same code works with every model on this site: only the model ID changes. Many labs also offer their own API and SDK.
What it costs in practice
- 1,000 chat replies$1.90
- Summarise a 100-page document$0.067
- An app with 10,000 requests a day for a month$885
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News about Meta
See all →Frequently asked questions
- How much does Muse Spark 1.3 cost?
- Muse Spark 1.3 costs $1.25 per million input tokens and $4.25 per million output tokens through the API. For example, 1,000 chat replies of about 500 tokens in and 300 out cost around $1.90.
- What is the context window of Muse Spark 1.3?
- Muse Spark 1.3 can read up to 1,048,576 tokens in one request, about 1,966 pages of text. It can write up to 943,718 tokens in a single answer.
- Is Muse Spark 1.3 open source?
- No. Muse Spark 1.3 is a closed model: its weights are not published, so you use it through Meta’s own apps and API, or through cloud providers.
- Who makes Muse Spark 1.3?
- Muse Spark 1.3 is made by Meta. It became available through the API on September 2, 2026.
- How good is Muse Spark 1.3?
- Muse Spark 1.3 has an overall index of 156.9 in Epoch AI’s independent tests, ranking #14 of 136 models we track.
- Can Muse Spark 1.3 read images?
- Yes. Besides text, it accepts images, video and files such as PDFs as input.
- What are the alternatives to Muse Spark 1.3?
- Models with a similar price from other companies include Grok 4.3, GPT-5.1-Codex-Max and Gemini 2.5 Pro. You can compare them side by side on this page.