davinci-002 vs Muse Spark 1.2
Detailed pricing comparison and cost analysis.
Updated September 2026
Cost Simulator
| Feature | davinci-002 | Muse Spark 1.2 |
|---|---|---|
| Provider | OpenAI | Meta |
| Input Price (1M) | $2.00 | $1.25 |
| Output Price (1M) | $2.00 | $4.25 |
| Context Window | 16,384 | 1,048,576 |
Verdict
davinci-002 costs $2.00 per 1M input tokens and $2.00 per 1M output tokens. Muse Spark 1.2 costs $1.25 per 1M input tokens and $4.25 per 1M output tokens. Muse Spark 1.2 is 38% cheaper on input tokens than davinci-002. For output tokens, davinci-002 is the more affordable option at $2.00/1M vs $4.25.
On context window, Muse Spark 1.2 supports 1,048,576 tokens — meaning it can fit more conversation history, documents, or code in a single request. This matters for RAG pipelines, long document analysis, and agentic workflows where context builds up over many turns.
When to choose davinci-002
- ✓ Your workload is output-heavy — davinci-002 generates text cheaper
- ✓ You are already integrated with OpenAI
When to choose Muse Spark 1.2
- ✓ You need the lowest input token cost ($ 1.25/1M)
- ✓ You need a larger context window (1,048,576 tokens)
- ✓ You are already integrated with Meta
Use the calculator above to simulate your specific workload and find the exact break-even point. For most applications, the cheapest model is the one that minimises your total monthly bill given your input-to-output token ratio.
Frequently Asked Questions
Is davinci-002 cheaper than Muse Spark 1.2? ▼
Muse Spark 1.2 is cheaper on input tokens at $1.25/1M vs $2.00/1M for davinci-002 — a 38% saving.
What is the context window of davinci-002 vs Muse Spark 1.2? ▼
davinci-002 has a 16,384-token context window. Muse Spark 1.2 has a 1,048,576-token context window. Muse Spark 1.2 supports the larger context, suitable for longer documents and agentic workflows.
Which model is better: davinci-002 or Muse Spark 1.2? ▼
The best choice depends on your use case. For cost efficiency on input tokens, Muse Spark 1.2 is the cheaper option. For maximum context length, Muse Spark 1.2 supports 1,048,576 tokens. Use the comparison table above to find the right fit for your workload.