Muse Spark 1.3 vs Muse Spark 1.3 Contributor
The same model on two sets of terms. The Contributor version is far cheaper because Meta may use your prompts and its answers to train future models; the standard version is not used that way. Choose by what you are sending.
Choose Muse Spark 1.3 if
- Customer data, personal data or anything confidential.
- Products your own customers use.
- Higher rate limits.
Choose Muse Spark 1.3 Contributor if
- Prototypes and experiments on data that is not sensitive.
- Public or open-source code.
- Large test runs where cost matters more than privacy.
Side by side
| Muse Spark 1.3 | Muse Spark 1.3 Contributor | |
|---|---|---|
| Made by | Meta | Meta |
| Released | September 2026 | September 2026 |
| Input price, per 1M tokens | $1.625 | $0.13 |
| Output price, per 1M tokens | $5.525 | $0.26 |
| Cached input, per 1M tokens | $0.195 | $0.0026 |
| Batch (about half price) | No | No |
| Context window | 1.05M tokens | 1.05M tokens |
| Longest answer | — | — |
| Reads | Text, Images, Video | Text, Images, Video |
| Thinks before answering | Yes, adjustable | Yes, adjustable |
| Open weights | No | No |
| Runs in Sri Lanka | No | No |
Prices are Roar AI’s published rates, live from our price list. Specs are each lab’s own published figures.
What a real job costs
Take 1,000 requests, each about 3,000 tokens in and 1,000 out — a long prompt and a page of answer.
Muse Spark 1.3 Contributor does the same job for 16× less. Models that think before answering spend extra output tokens doing it, so on hard prompts the real gap can be wider than the rates suggest.
Use both, switch any time
On Roar AI both are on the same key and the same monthly invoice, billed in rupees. Trying the other one is a one-word change:
client.chat.completions.create(model="muse-spark-1.3", …) client.chat.completions.create(model="muse-spark-1.3-contributor", …)
Send the same prompts to both for a day and compare the answers on your own work — that settles it faster than any benchmark. Read the docs.