$ diff muse-spark-1-3 deepseek-v4-pro-0813
Muse Spark 1.3 vs DeepSeek V4-Pro-0813
Values come from Muse Spark 1.3 and DeepSeek V4-Pro-0813, 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.
Meta AIMuse Spark 1.3
- context
- 1M
- weights
- closed
- $/M in
- $1.25
- $/M out
- $4.25
- context
- 1.0M
- weights
- open
- $/M in
- $0.66
- $/M out
- $1.98
What actually differs
- Context window
- DeepSeek V4-Pro-0813 takes 1.0M against 1M — modestly more room in a single request.
- Input price
- DeepSeek V4-Pro-0813 at $0.66/M against $1.25/M — 1.9× 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
- DeepSeek V4-Pro-0813 at $1.98/M against $4.25/M — 2.1× cheaper to generate. Output dominates the bill on most agentic workloads, where the model writes far more than it reads.
- Weights
- DeepSeek V4-Pro-0813 publishes weights (MIT (open-weight, as reported)); Muse Spark 1.3 is API-only. That decides self-hosting, air-gapped deployment and fine-tuning before any capability question does.
- Recency
- Muse Spark 1.3 shipped 20 days after DeepSeek V4-Pro-0813 (2026-09-02 vs 2026-08-13).
Full spec
| Attribute | Muse Spark 1.3 | DeepSeek V4-Pro-0813 |
|---|---|---|
| Developer | Meta AI | DeepSeek |
| Released | 2026-09-02 | 2026-08-13 |
| Context window | 1,000,000 | 1,048,576 (1M) — 384K max output |
| Pricing | Standard $1.25/M input · $4.25/M output · Contributor ≈$0.10/M input · ≈$0.20/M output | $0.66/M input (cache miss) · $1.98/M output off-peak; $1.32 · $3.96 at peak — see Pricing |
| License | proprietary | MIT (open-weight, as reported) |
| Availability | Muse Code, Meta Model API | DeepSeek API (Responses format, Codex-adapted), Hugging Face (`deepseek-ai/DeepSeek-V4-Pro-0813`) |