Comparison
DeepSeek V4 Pro vs Muse Spark 1.2
How DeepSeek V4 Pro and Muse Spark 1.2 compare on the numbers that decide the call - and how to switch between them without touching your code.
| Spec | DeepSeek V4 Pro | Muse Spark 1.2 |
|---|---|---|
| Input price / 1Mlower is cheaper | $0.66 | $1.25 |
| Output price / 1Mlower is cheaper | $1.98 | $4.25 |
| Context windowbigger fits more | 1M | 1.048576M |
| Typical speedfaster median | 1.6s | 1.8s |
| Quality score | 90/100 | 88/100 |
| Provider | DeepSeek | Meta |
Which should you pick?
- DeepSeek V4 Pro is cheaper on input tokens ($0.66 vs $1.25).
- Muse Spark 1.2 takes a larger context window (1.048576M tokens).
- DeepSeek V4 Pro is usually the faster to answer.
- DeepSeek V4 Pro scores higher on the composite quality benchmark.
You do not have to choose permanently. Name one as your first choice and let Final Router fall back to the other when a provider fails - the request still gets answered, and the log shows which model replied.
Common questions
- Is DeepSeek V4 Pro or Muse Spark 1.2 cheaper?
- DeepSeek V4 Pro is cheaper on input tokens - $0.66 vs $1.25 per 1M. Neither is marked up: Final Router bills provider list price.
- Can I switch between DeepSeek V4 Pro and Muse Spark 1.2 without changing my code?
- Yes. Both are called through the same OpenAI-compatible endpoint - change only the model id ("deepseek/deepseek-v4-pro" or "meta/muse-spark-1.2"), or let a routing policy fall back from one to the other automatically.