As of September 2, 2026, Muse Spark 1.3 Contributor API pricing is $0.10 per million input tokens and $0.20 per million output tokens. A typical 100K-in / 20K-out request costs $0.01. Source: https://dev.meta.ai/docs/pricing-rate-limits/
Blended / 1M
$0.30
Input
$0.10
Output
$0.20
100K / 20K
$0.01
Specs
1M
131.1K
Sep 2, 2026
Proprietary
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As of September 2, 2026, Muse Spark 1.3 Contributor Meta API pricing is $0.10 per million input tokens and $0.20 per million output tokens. Input tokens are the prompt you send; output tokens are the completion. Long answers therefore cost more than short ones even when the prompt stays the same. Source: https://dev.meta.ai/docs/pricing-rate-limits/
On this page the blended Muse Spark 1.3 Contributor API cost is $0.30 for 1 million input tokens plus 1 million output tokens. That 1:1 mix is the comparison scale used across the LLM pricing table. A 3:1 mix (three million input tokens per one million output tokens), which some calculators use, would be about $0.50.
A typical Muse Spark 1.3 Contributor API request with 100K input tokens and 20K output tokens costs about $0.01 at current rates as of September 2, 2026. Multiply that by daily or monthly volume to estimate spend. Caching, batch APIs, and volume discounts from Meta can bring the real invoice lower than the public list rate at https://dev.meta.ai/docs/pricing-rate-limits/.
Muse Spark 1.3 Contributor supports a 1M token context window and can generate up to 131K output tokens per request. The context window is the total prompt plus conversation history the model can see in one call. Larger windows cost more when you fill them, because every input token is billed per million tokens.
No. Muse Spark 1.3 Contributor is a proprietary model by Meta. The only public way to call it is Meta's API, billed per million input and output tokens. There is no self-host option for the weights.
Benchmark data for Muse Spark 1.3 Contributor is not yet available. Check back as evaluation results are published. Use those scores with the token prices above when you are choosing between a cheaper LLM and a frontier model. GPQA, SWE-bench, and HLE are the evals people usually compare first.
Use the Compare picker on this page to start an LLM comparison. Search by model or provider, pick a second model, and AnotherWrapper opens a dedicated Muse Spark 1.3 Contributor vs page with per-million-token prices, blended 1M-in / 1M-out cost, context window, throughput, and benchmarks. You can also open any model from the sidebar, or go back to the LLM pricing table to sort the full index.
The cheapest LLM alternative depends on whether you optimize for blended token cost, coding evals, or context window. Start with the popular matchups on this page, then sort the LLM pricing table by blended cost to see which hosted APIs undercut Muse Spark 1.3 Contributor. Open-weight models can be cheaper still if you self-host, but that is not the same as Meta API pricing on this page.
Muse Spark 1.3 Contributor is called through Meta's API with an API key. Bill against input and output tokens separately; cache or shorten prompts if spend is high. If you are shipping a full product, AnotherWrapper includes pre-built API routes and templates for Meta and 5+ other providers with auth, payments, and deployment already configured.
This Muse Spark 1.3 Contributor page tracks the latest published Meta API pricing from Meta, quoted per million tokens. List rates can differ from invoices because of prompt caching, batch discounts, committed-use tiers, and private contracts. Official rate sheet: https://dev.meta.ai/docs/pricing-rate-limits/. Benchmark scores come from official publications and independent evals, not from a private lab run by AnotherWrapper.
Muse Spark 1.3 Contributor is a proprietary model from Meta. Current API pricing is $0.10 per million input tokens and $0.20 per million output tokens, with a 1M token context window. A blended 1M-in / 1M-out workload costs $0.30.
Source: Meta pricing (https://dev.meta.ai/docs/pricing-rate-limits/)
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