Data verified: Aug 15, 2026, 11:13 AM · Prices sourced from official provider pages. Verify current rates before production use.
Data verified: Aug 15, 2026, 11:13 AM · Prices sourced from official provider pages. Verify current rates before production use.
Price, context and performance head to head. Data synced from the provider catalog.
Cheaper
Muse Spark 1.2
Larger context
Tied
Faster
Gemini 3.5 Flash
Higher quality
Gemini 3.5 Flash
| Feature | Gemini 3.5 Flash | Muse Spark 1.2 |
|---|---|---|
| Provider | Meta | |
| Tier | Budget | Mid-tier |
| Input per 1M tokens | $1.5 | $1.25 |
| Output per 1M tokens | $9 | $4.25 |
| Cached input per 1M | $0.15 | $0.15 |
| Context window | 1.0M | 1.0M |
| Intelligence index | 52/100 | — |
| Coding index | 70/100 | — |
| Agentic index | 40/100 | — |
| GPQA Diamond | 1 | — |
| Tau-bench (airline) | 1 | — |
| Speed | Fast | Standard |
| Vision (image input) | Yes | Yes |
| Function calling | Yes | Yes |
| Batch API | No | No |
Enter how many requests per day you send with an average prompt (1K input + 1K output) and compare the monthly cost of both models.
Muse Spark 1.2 saves $15/mo vs Gemini 3.5 Flash
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We integrate Gemini 3.5 Flash or Muse Spark 1.2 into your product with caching, observability and continuous evaluation — typically 40-80% cheaper than the obvious first pick.
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What people ask us when comparing GPT, Claude, Gemini and the rest.
A token is the unit an AI model processes: usually between half a word and a full word. Rule of thumb: 1,000 tokens ≈ 750 English words. A 20-word sentence is about 26 tokens; a 300-word email is around 400. Models charge for input tokens (your prompt) and output tokens (their answer) separately.