Muse Spark 1.3 API Pricing
Muse Spark 1.3 is the newest checkpoint on Meta's Model API, described by Meta as tuned for agentic workflows — multi-step tool, browser and long-horizon tasks — with improved coding over 1.2, and marked recommended for new work. It is priced identically to 1.2 and 1.1: Meta groups all three and states they share the same standard pricing — $1.25/M input, $0.15/M cached input, $4.25/M output. One thing to read before switching: Meta says audio understanding here is not fully supported and points audio work back to 1.2.
Run the numbers.
Live calculator on Meta's standard rate. The lever that actually moves this bill is not the workload mix but the tier: the Contributor rate below is a different order of magnitude, and it is paid for with training rights rather than dollars.
Real-world presets.
Codebase-scale migration
Reading 100-page contracts
Ticket triage
Research planning turn
Paste text. See tokens. See cost.
This is a chars-per-token approximation, not a real tokenizer. Actual tokens vary by language, code density, and tool-call overhead — counts are typically ±10–20% off for English prose, more for code or non-Latin scripts. For exact billing, use the vendor's official tokenizer.
| Model | Input /M | Output /M | Effective blended | Context | Best for |
|---|---|---|---|---|---|
| Muse Spark 1.3 Current | $1.25 cache $0.15 | $4.25 | $0.66 agentic 92/8 | 1M | Agentic workflows and coding - recommended for new work |
| Muse Spark 1.2 | $1.25 cache $0.15 | $4.25 | $0.66 identical card, previous checkpoint | 1M | Audio work, where 1.3 is degraded |
| Muse Spark 1.1 | $1.25 cache $0.15 | $4.25 | $0.66 identical card, original checkpoint | 1M | No Contributor tier on this one |
| Gemini 3.5 Flash-Lite | $0.30 cache $0.03 | $2.50 | $0.272 budget 1M peer | 1M | High-volume 1M-context work on a budget |
| Grok 4.3 | $1.25 cache $0.20 | $2.50 | $0.558 same input, cheaper output | 1M | Output-heavy 1M-context agents |
| GPT-5.6 Luna | $0.20 cache $0.02 | $1.20 | $0.152 OpenAI 1M peer | 1.05M | OpenAI-native agent stacks |
| Gemini 3.6 Flash | $0.75 cache $0.075 | $3.75 | $0.481 Google agentic peer | 1M | Multimodal agents with computer use |
| Kimi K3 | $3.00 cache $0.30 | $15.00 | $1.92 frontier agentic peer | 1M | Long-horizon agentic coding |
Frequently asked.
What the Contributor tier really costs you, why three checkpoints share one price, and the audio footnote worth reading before you switch.
Q · 01 How much does Muse Spark 1.3 cost? +
$1.25/M input, $0.15/M cached input and $4.25/M output on the Standard tier. Under this site's 92/8 agentic blend at an 82% cache-hit rate that is $0.66/M effective. There is no long-context premium — Meta states the rate is the same whether the window is nearly empty or nearly full.Q · 02 Is it more expensive than 1.2 or 1.1? +
Q · 03 What is the Contributor tier, and what does it actually cost? +
$0.10/M input, $0.002/M cached input and $0.20/M output — about 19x cheaper on our blend, $0.034/M against $0.66/M. The price is not money: Meta describes it as "heavily discounted token pricing in exchange for permission to use your prompts and completions to train future Meta models". Throughput differs too — Contributor is capped at 100 requests per minute against Standard's 3,000, though token throughput is close (3M vs 4M per minute). It suits prototyping and load testing; anything touching customer or proprietary data is a legal question, not a pricing one. Only 1.3 and 1.2 offer it — 1.1 does not.Q · 04 Can I send it audio? +
Q · 05 What does it cost to add web search? +
$2.50 per 1,000 queries, on top of the token cost of whatever the search returns into your context. Muse Image's built-in search is different — that is included in its flat per-image price.