Data verified: Aug 15, 2026, 11:13 AM · Prices sourced from official provider pages. Verify current rates before production use.
Data verified: Aug 15, 2026, 11:13 AM · Prices sourced from official provider pages. Verify current rates before production use.
Price, context and performance head to head. Data synced from the provider catalog.
Cheaper
GPT-5.6 Luna Pro
Larger context
GPT-5.6 Luna Pro
Faster
MiniMax M2
Higher quality
GPT-5.6 Luna Pro
| Feature | GPT-5.6 Luna Pro | MiniMax M2 |
|---|---|---|
| Provider | OpenAI | MiniMax |
| Tier | Flagship | Budget |
| Input per 1M tokens | $0.1 | $0.255 |
| Output per 1M tokens | $0.6 | $1.02 |
| Cached input per 1M | $0.01 | $0.255 |
| Context window | 1.1M | 204.8K |
| Intelligence index | — | — |
| Coding index | — | — |
| Agentic index | — | — |
| GPQA Diamond | 1 | — |
| Tau-bench (airline) | 1 | — |
| Speed | Slow | Fast |
| Vision (image input) | Yes | No |
| Function calling | Yes | Yes |
| Batch API | No | No |
Enter how many requests per day you send with an average prompt (1K input + 1K output) and compare the monthly cost of both models.
GPT-5.6 Luna Pro saves $1.73/mo vs MiniMax M2
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We integrate GPT-5.6 Luna Pro or MiniMax M2 into your product with caching, observability and continuous evaluation — typically 40-80% cheaper than the obvious first pick.
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A token is the unit an AI model processes: usually between half a word and a full word. Rule of thumb: 1,000 tokens ≈ 750 English words. A 20-word sentence is about 26 tokens; a 300-word email is around 400. Models charge for input tokens (your prompt) and output tokens (their answer) separately.