Meta: Muse Spark 1.3 Contributor API Pricing
Meta: Muse Spark 1.3 Contributor costs $0.100 per 1M input tokens and $0.200 per 1M output tokens (cache reads: $0.0020). Context window: 1.0M. Prices verified 2026-10-21 · source
Rebuilt daily from our snapshot archive — the chart appears once a model has 5+ snapshots of history.
From our own daily snapshot archive — independent of provider announcements.
Token economics
| Token type | Price | vs base input |
|---|---|---|
| Standard input | $0.100 | — |
| Cache read | $0.0020 | −98% |
| Output | $0.200 | — |
| Web search tool | $2.5/1k searches | — |
Prompt caching stores repeated context server-side: reads cost far less, but writes carry a one-time premium.
Higher effort = deeper thinking = more reasoning tokens billed as output.
What would Meta: Muse Spark 1.3 Contributor cost you per month?
| Workload | Requests/mo | Avg tokens (in/out) | Est. monthly cost |
|---|---|---|---|
| Light chatbot | 10,000 | 800 / 400 | $1.60 |
| Coding agent | 5,000 | 8,000 / 2,000 | $6.00 |
| RAG pipeline | 30,000 | 4,000 / 500 | $15.00 |
| Doc summarizer | 2,000 | 20,000 / 1,000 | $4.40 |
Estimates use list prices without prompt caching. Caching can cut input cost by up to 90% on repeated context.
About Meta: Muse Spark 1.3 Contributor
Muse Spark 1.3 Contributor is the cost-efficient contributor tier of Meta’s multimodal reasoning model for experimentation, learning, and early-stage agentic, multi-agent, and coding workflows. It is designed to track information...
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Frequently asked questions
How much does Meta: Muse Spark 1.3 Contributor cost?
Meta: Muse Spark 1.3 Contributor costs $0.100 per 1M input tokens and $0.200 per 1M output tokens; cached input tokens cost $0.0020 per 1M. Verified 2026-10-21 — provider source.
What is the context window?
1.0M tokens, with up to 944K output tokens per response. That's roughly 1311 pages of text in a single request.
Does it support prompt caching?
Yes — cached input is $0.0020/1M, about 98% cheaper than standard input. Agents and RAG workloads with repeated context benefit most.
What's a cheaper alternative?
ScaleDown: Summarize saves about 78% on a typical workload with comparable quality.
Official resources
- Meta: Muse Spark 1.3 Contributor on OpenRouter — live endpoint, pricing source of record.
- Artificial Analysis leaderboard → — independent intelligence and performance rankings.
- Shred your current bill — paste a CSV and see if switching saves money.