Muse Spark 1.2 is a reasoning model from Meta, designed for complex agentic tasks. It accepts text, images, video, audio, and PDF documents, returns text, and offers a 1M-token context...
At a glance
- Context window
- 1Mtokens
- Max output
- 944Ktokens
- Knowledge to
- —
- Released
- 2026
Capabilities
Benchmarks
- Intelligence index
- 40
- Coding index
- 72
- Agentic index
- 44
Design Arena
| Category | Elo | Win rate |
|---|---|---|
| models · dataviz | 1,365 | 61.7 |
| models · 3d | 1,331 | 54.2 |
| models · codecategories | 1,327 | 53.9 |
| models · uicomponent | 1,326 | 53.3 |
| models · gamedev | 1,325 | 52 |
| models · website | 1,322 | 53.8 |
| models · asciiart | 1,319 | 58.6 |
| models · svg | 1,314 | 56.3 |
Source: Artificial Analysis, Design Arena · as of Sep 16, 2026
Performance
Reference uptime
100%
Median latency
4,158 ms
Throughput
93 tok/s
IranRouter uptime comes from our own automated probes; the reference figures are daily measurements of this model's upstream routes. Each card shows a 30-day average, and a day without data stays empty.
Popularity
- Current rank
- —
- Rank change, 7 days
- —
Daily tokens · 90 days
45B
Ranked by daily token volume across the global model market; the figure above the chart is the daily average.
Supported parameters
Parameters this model accepts; anything else is ignored.
Quick start
from openai import OpenAI
client = OpenAI(
api_key="ir-...",
base_url="https://iranrouter.com/v1",
)
resp = client.chat.completions.create(
model="meta/muse-spark-1.2",
messages=[{"role": "user", "content": "سلام!"}],
)
print(resp.choices[0].message.content)Only base_url and the key change; the rest of your code stays as it is.