$ diff gemini-3-6-flash muse-spark
Gemini 3.6 Flash vs Muse Spark
Google DeepMind and Meta AI, side by side. Every value below is the one recorded on the model’s own wiki page, with its citation — nothing is estimated.
Google DeepMindGemini 3.6 Flash
- context
- 1.0M
- weights
- closed
- $/M in
- $1.5
- $/M out
- $7.5
- context
- 1M
- weights
- open
- $/M in
- $1.25
- $/M out
- $4.25
What actually differs
- Context window
- Gemini 3.6 Flash takes 1.0M against 1M — modestly more room in a single request.
- Input price
- Muse Spark at $1.25/M against $1.5/M — 1.2× cheaper to feed.
- Output price
- Muse Spark at $4.25/M against $7.5/M — 1.8× cheaper to generate. Output dominates the bill on most agentic workloads, where the model writes far more than it reads.
- Weights
- Muse Spark publishes weights (proprietary (closed / API-only, not open-weights)); Gemini 3.6 Flash is API-only. That decides self-hosting, air-gapped deployment and fine-tuning before any capability question does.
- Recency
- Gemini 3.6 Flash shipped 104 days after Muse Spark (2026-07-21 vs 2026-04-08).
Full spec
| Attribute | Gemini 3.6 Flash | Muse Spark |
|---|---|---|
| Developer | Google DeepMind | Meta AI |
| Released | 2026-07-21 | 2026-04-08 |
| Context window | 1,048,576 tokens (1M) | 1,000,000 tokens (1.1) |
| Pricing | $1.50/M input · $7.50/M output | $1.25/M input · $4.25/M output (Meta Model API, public preview) |
| License | proprietary | proprietary (closed / API-only, not open-weights) |
| Availability | Gemini API, Google AI Studio, Android Studio, Vertex AI, consumer Gemini app, Google Search, GitHub Copilot | Meta Model API (public preview, US-based developers only) |
Values come from Gemini 3.6 Flash and Muse Spark, where each is cited to its source. This page states no benchmark result and ranks neither model — it puts two published specifications next to each other. Where a lab has not published a figure, the row says so rather than guessing. How these pages are produced.