Meta · Efficient
Muse Spark 1.3 Contributor
Meta's Muse Spark 1.3 Contributor is a frontier multimodal reasoning model for long-horizon coding and agentic workflows, with strong gains in computer use, browsing, professional tool use, codebase understanding, and million-token retrieval. It accepts text, images, audio, video, and files, supports tool calling and structured output, and always reasons before answering. Prompts and outputs may be used by Meta for training and to improve its products.
- Reasoning
- Tools
- Vision
- Structured output
- PDF input
- Audio input
- Video input
- Input
- Text, Images, Video, Audio
- Output
- Text
- Reasoning effort
- minimal · low · medium · high · xhigh
- Discovery tier
- Efficient
Pricing
USD per 1M tokens- Input
- $0.10
- Output
- $0.20
- Cache read
- $0.002
Reference prices as published by the model provider. API example
Specifications
- Context window
- 1M
- Max output
- —
- Average output (7 days)
- 1.2K tokens
- Longer than 77% of 473 models
Side by side
Muse Spark 1.3 Contributor compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| Muse Spark 1.3 ContributorMetaThis model | Mercury 3InceptionRemove | |
|---|---|---|
| Provider | Meta | Inception |
| Discovery tier | Efficient | Efficient |
| Added | Sep 2, 2026 | Oct 19, 2026 |
| Limits | ||
| Context window | 1.05MBest | 1M |
| Max output | — | 131.07K |
| Average output | 1.2K tokens | 1.9K tokens |
| Pricing, USD per 1M tokens | ||
| Input | $0.10 | $0.10 |
| Output | $0.20Best | $0.35 |
| Cache read | $0.002Best | $0.01 |
| Performance | ||
| Throughput | 193.8 tok/s | 883.5 tok/sBest |
| Time to first token | 3.6 sBest | 4.5 s |
| Request success (24h) | 99.4% | 100.0%Best |
| Capabilities | ||
| Reasoning | Yes | Yes |
| Tools | Yes | Yes |
| Vision | Yes | No |
| Structured output | Yes | Yes |
| PDF input | Yes | No |
| Audio input | Yes | No |
| Video input | Yes | No |
| Parallel tools | No | Yes |
| Reasoning effort | minimal, low, medium, high, xhigh | none, low, medium, high |
Public evaluations
Benchmarks
There are no public benchmark results for these models yet.
Live routing data
Performance and reliability
Recent averages across requests routed for this model. Your own speed depends on prompt length, reasoning effort and load.
- Throughput
- 193.8 tok/s
- Faster than 84% of 260 models
- Time to first token
- 3.6 s
- Quicker than 44% of 260 models
- Prompt cache hits
- 63.7%
- About $0.0376 per 1M input tokens with caching
- Request success (24h)
- 99.4%
- Reliable
Cache hits are the share of input tokens recently served from a prompt cache across all requests. They are not a forecast of your own hit rate.
- Healthy (98% or more)
- Degraded (90–98%)
- Down (under 90%)
- No requests
Developers
Use it through the API
Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.
curl https://www.noumen.xyz/api/v1/chat/completions \
-H "Authorization: Bearer $NOUMEN_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "meta/muse-spark-1.3-contributor",
"reasoning_effort": "medium",
"messages": [{ "role": "user", "content": "Explain this stack trace." }]
}'import os
from openai import OpenAI
client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
model="meta/muse-spark-1.3-contributor",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)Meta
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