Muse Spark 1.2 vs DeepSeek-R1
Meta vs DeepSeek · Prices checked 12 August 2026
On blended cost DeepSeek-R1 undercuts Muse Spark 1.2 by about 2.1×: $1.04 per million tokens versus $2.15. A single 100K-input, 10K-output job costs $0.077 on DeepSeek-R1 against $0.168 on Muse Spark 1.2.
On context, Muse Spark 1.2 is the larger at 1,049,000 tokens versus 64,000.
Pricing and capacity
| Metric | Muse Spark 1.2 | DeepSeek-R1 | Difference |
|---|---|---|---|
| Input / 1M tokens | $1.25 | $0.550 | 2.3× |
| Output / 1M tokens | $4.25 | $2.19 | 48% |
| Blended · 70/30calculated | $2.15 | $1.04 | 2.1× |
| Blended · 50/50calculated | $2.75 | $1.37 | 2.0× |
| Blended · 80/20calculated | $1.85 | $0.878 | 2.1× |
| Blended · 20/80calculated | $3.65 | $1.86 | 49% |
| Job cost · 100K + 10Kcalculated | $0.168 | $0.077 | 2.2× |
| Job cost · 1M + 100Kcalculated | $1.68 | $0.769 | 2.2× |
| Context window | 1,049,000 | 64,000 | 16.4× |
Input and output rates are as published by each provider. Blended and job-cost rows are calculated comparison metrics, not published prices — how they are derived.
Benchmarks
These two models do not currently report scores on any of the same benchmark suites, so there is no like-for-like capability comparison to show. Rather than pad the page with one-sided numbers, the benchmark leaderboards list every score we do hold.
What each model is for
Muse Spark 1.2
Meta · Frontier
Meta Superintelligence Labs' flagship line, and Meta's entry into the agentic coding market via the Meta Model API rather than open weights. Muse Spark plans work, delegates to subagents, writes scripts or drives UIs directly, and debugs from screenshots. It pairs a 1M-token context window with full multimodal input (images, video and PDFs) plus built-in search with citations, structured output and parallel tool calling.
- Agentic execution with subagent delegation
- Coding, with particular strength on frontend and design work
- 1M-token context
- Images, video and PDF input
DeepSeek-R1
DeepSeek · Reasoning
Open-weights reasoning model with chain-of-thought trained via RL. Comparable to o1 on math benchmarks at a fraction of the price.
- Open-weights reasoning
- Visible chain-of-thought
- Math & code
- Cheap
Frequently asked questions
Which is cheaper, Muse Spark 1.2 or DeepSeek-R1?
On blended cost DeepSeek-R1 undercuts Muse Spark 1.2 by about 2.1×: $1.04 per million tokens versus $2.15. A single 100K-input, 10K-output job costs $0.077 on DeepSeek-R1 against $0.168 on Muse Spark 1.2. Blended cost weights input at 70% and output at 30%; price your own token split for an exact answer, since the cheaper model on a blended basis is not always cheaper for your workload.
Which has the larger context window, Muse Spark 1.2 or DeepSeek-R1?
On context, Muse Spark 1.2 is the larger at 1,049,000 tokens versus 64,000. The context window caps everything in a single request: prompt, retrieved documents, conversation history and the model’s own output all share it.
Can I compare Muse Spark 1.2 and DeepSeek-R1 on my own numbers?
Yes. Open both in the side-by-side comparison tool to see every field at once, or use the token calculator to price your actual prompt and monthly request volume against each model. Both are free and need no sign-up.
Price it for your own workload
Related matchups
Terms used on this page
Prices and scores are recomputed on every deploy from the catalogue. Prices checked 12 August 2026.