$ diff gemini-4-argon muse-spark-1-3
Gemini 4 Argon vs Muse Spark 1.3
Values come from Gemini 4 Argon and Muse Spark 1.3, 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.
Google DeepMindGemini 4 Argon
- context
- 2M
- weights
- closed
- $/M in
- $2
- $/M out
- $10
- context
- 1M
- weights
- closed
- $/M in
- $1.25
- $/M out
- $4.25
What actually differs
- Context window
- Gemini 4 Argon takes 2M against 1M — 2× more room in a single request.
- Input price
- Muse Spark 1.3 at $1.25/M against $2/M — 1.6× cheaper to feed. Standard rates: one of these labs also quotes a lower cached-input tier, which applies only when a prefix is reused — see the full spec below.
- Output price
- Muse Spark 1.3 at $4.25/M against $10/M — 2.4× cheaper to generate. Output dominates the bill on most agentic workloads, where the model writes far more than it reads.
- Recency
- Gemini 4 Argon shipped 28 days after Muse Spark 1.3 (2026-09-30 vs 2026-09-02).
Full spec
| Attribute | Gemini 4 Argon | Muse Spark 1.3 |
|---|---|---|
| Developer | Google DeepMind | Meta AI |
| Released | 2026-09-30 | 2026-09-02 |
| Context window | 2M tokens | 1,000,000 |
| Pricing | $2/M input · $10/M output · cached input $0.10/M (introductory; stated to double to $4/$20) | Standard $1.25/M input · $4.25/M output · Contributor ≈$0.10/M input · ≈$0.20/M output |
| License | proprietary | proprietary |
| Availability | Fairwind Program (trusted cyber defenders) only; paid API and Google AI Ultra stated as next, no date | Muse Code, Meta Model API |