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Meta: Muse Spark 1.2: AI model

Muse Spark 1.2 is Meta's reasoning model for complex agent tasks from Meta with a 1M-token context window. Reachable from inside Iran through Hormouz.

Context window:
1,048,576 tokens
Input:
$1.25/1M tokens
Output:
$4.25/1M tokens
Type:
text, image, video
  • Vision
  • Tools
  • Streaming
  • Long context

Thinking levels: Always thinks · xhigh · high · medium · low · minimal

Muse Spark 1.2 is Meta's reasoning model for complex agent tasks. It reads text, images, video and PDFs over a 1M-token context and works as a main agent that plans and delegates or as a sub-agent running in parallel. In Meta's testing it does well on multi-file refactors, long debugging sessions, generating whole repositories and tasks that go far beyond one prompt.

It accepts text, image, file (PDF) and video input and returns text, and supports tool calling, structured JSON output and streaming. It always reasons before answering, and you choose how hard it thinks with the reasoning effort setting. Muse Spark 1.2 is commonly used for multi-file refactors, long debugging sessions, multi-agent systems and repository-scale code generation. Hormouz serves it behind an OpenAI-compatible API: point your base URL at Hormouz, drop in a Hormouz key, and existing OpenAI SDK code runs without changes.

Pricing is usage-based: $1.25 per million input tokens and $4.25 per million output tokens. There is no fixed monthly fee, and you pay only for the tokens you use. Hormouz provides stable access to the model from inside Iran, with no foreign credit card or circumvention tooling required.

Muse Spark 1.2 is a reasoning model from Meta, designed for complex agentic tasks. It accepts text, images, video, and PDF documents, returns text, and offers a 1M-token context window....

Quickstart

curl https://api.hormouz.net/v1/chat/completions \
  -H "Authorization: Bearer ng-YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "meta/muse-spark-1.2",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Specs

VendorMeta
TypeText, Image, Video
Context window1,048,576 tokens
Pricing$1.25/M in · $4.25/M out
APIChat Completions
CapabilitiesStreaming · Vision · Tools

Benchmarks

39.6
Intelligence Index
Better than 79% of models we compared
72.2
Coding Index
Better than 88% of models we compared
43.2
Agentic Index
Better than 84% of models we compared

Reasoning

GPQA Diamond
Graduate-level scientific reasoning
90.4%
HLE
Humanity's Last Exam
45.5%
AA-LCR
Long-context reasoning
79%
CritPt
Research-level physics reasoning
17.7%
AA Omniscience
Broad factual knowledge accuracy
45.4%
Non-Hallucination
Rate of avoiding fabricated answers
66.7%

Coding

SciCode
Python for scientific computing
57.4%

Agentic

GDPval
Economically valuable tasks
48.9%

Source: Artificial Analysis

Agentic Game Dev
Top 62%
1,179Elo
Win rate: 42.7%
Android Native
Top 27%
1,236Elo
Win rate: 53.2%
Full-Stack
Top 36%
1,208Elo
Win rate: 48%
HTML Slides
Top 87%
1,134Elo
Win rate: 40%
Mobile Apps
Top 52%
1,169Elo
Win rate: 46.8%
Python Slides
Top 48%
1,198Elo
Win rate: 48.6%
Web Apps
Top 36%
1,215Elo
Win rate: 50.6%
3D
Top 10%
1,314Elo
Win rate: 52.7%Avg time: 198s
ASCII Art
Top 5%
1,310Elo
Win rate: 58.6%Avg time: 208s
Code
Top 5%
1,319Elo
Win rate: 52.3%Avg time: 180s
Data Viz
Top 3%
1,352Elo
Win rate: 60.4%Avg time: 188s
Game Dev
Top 9%
1,314Elo
Win rate: 50.4%Avg time: 214s
SVG
Top 9%
1,289Elo
Win rate: 55.7%Avg time: 158s
UI Component
Top 10%
1,307Elo
Win rate: 52.2%Avg time: 176s
Website
Top 4%
1,320Elo
Win rate: 52.2%Avg time: 165s

Metrics sourced from Design Arena

Code example

cURL
curl https://api.hormouz.net/v1/chat/completions \
  -H "Authorization: Bearer ng-YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "meta/muse-spark-1.2",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'
Python
from openai import OpenAI
client = OpenAI(api_key="ng-YOUR_API_KEY", base_url="https://api.hormouz.net/v1")
response = client.chat.completions.create(
    model="meta/muse-spark-1.2",
    messages=[{"role": "user", "content": "Hello!"}],
)
print(response.choices[0].message.content)
JavaScript
import OpenAI from "openai";
const client = new OpenAI({ apiKey: "ng-YOUR_API_KEY", baseURL: "https://api.hormouz.net/v1" });
const response = await client.chat.completions.create({
  model: "meta/muse-spark-1.2",
  messages: [{ role: "user", content: "Hello!" }],
});
console.log(response.choices[0].message.content);

Buy the Meta: Muse Spark 1.2 API, paid in rial

  • Buy credit with an Iranian bank card; no foreign card or account needed.
  • One Hormouz key reaches Meta: Muse Spark 1.2 and 600+ other models, and you pay only for what you use.
  • No VPN and no risk of a banned account; just change the base URL to api.hormouz.net/v1.
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FAQ

How much does Muse Spark 1.2 cost?
Pricing is usage-based: $1.25 per million input tokens and $4.25 per million output tokens. There is no fixed monthly fee, and you pay only for the tokens you use.
How do I access Muse Spark 1.2 from inside Iran?
Create an account on Hormouz and generate an API key. Hormouz provides a stable path to the model from inside Iran, with no foreign credit card or circumvention tooling required.
Is Muse Spark 1.2 compatible with OpenAI code?
Yes. Hormouz exposes an OpenAI-compatible API. Point your base URL at Hormouz and swap in your Hormouz key. Your existing SDKs and code run without a rewrite.
What context window and capabilities does Muse Spark 1.2 have?
It has a 1M-token context window, accepts text, image, file (PDF) and video input, and supports tool calling, structured JSON output and streaming. It always reasons before answering, and you choose how hard it thinks with the reasoning effort setting.
What is Muse Spark 1.2 good for?
Typical uses are multi-file refactors, long debugging sessions, multi-agent systems and repository-scale code generation.

Updated 2026-10-13