GPT-5.6 Luna vs MiniMax-M3: utility LLM pricing showdown
By TechCompare · Updated · How we check
Luna is the cheaper of the two per token for utility work. MiniMax-M3 is the pick when MiniMax's specific reasoning profile suits the task better than OpenAI's.
OpenAI: GPT-5.6 Luna
OpenAI's own price
- Input
- $0.20
- Output
- $1.20
- Cached
- $0.02
per 1M tokens
Price checked 2026-11-12
MiniMax: MiniMax M3
Cheapest host: GMICloud (fp8)
- Input
- $0.30
- Output
- $1.20
- Cached
- $0.06
per 1M tokens
Price checked 2026-11-12
Cost Comparison
Based on 100,000 input tokens (50% cached), 5,000 output tokens, and 100 requests.Prices come live from OpenRouter at each maker's own price where it's listed. Temporary deals are left out.
GPT-5.6 Luna and MiniMax-M3 are both in the ultra-cheap utility tier, designed for high-volume classification, routing, and formatting work where per-token cost dominates. Luna is the cheaper of the two per token. MiniMax-M3 has a context window of up to 1M tokens (512K guaranteed).
Two utility tier models for high volume work. Compare token rates and caching.
Side-by-side specs
| Spec | GPT-5.6 Luna | MiniMax-M3 |
|---|---|---|
| Input Cost (per M) | $0.20 (better on this spec) | $0.30 |
| Output Cost (per M) | $1.20 | $1.20 |
| Cached Input (per M)Cached input is text the provider has already processed. It costs less than fresh input. | $0.02 (better on this spec) | $0.06 |
| Batch input / output (per M) | $0.10 / $0.60 | None |
| Context Window | 1.05M | Up to 1M |
How they differ
GPT-5.6 Luna is priced at $0.20 per million input tokens and $1.20 per million output tokens at OpenAI's list price, with a 90% caching discount ($0.02 per million), a 50% batch discount and a 1.05M context. MiniMax-M3 is priced at $0.30 per million input tokens and $1.20 per million output tokens, with an 80% caching discount ($0.06 per million) and up to 1M of context.
For a 30K input + 3K output request, Luna costs $0.0096 vs MiniMax's $0.0126, so Luna is cheaper at this volume.
Verdict
Live one-shot loads go to Luna. Luna wins the rows that decide utility pricing: $0.20/M input against $0.30 (33.3% less) and $0.02/M cached input against $0.06 (66.7% less). Output ties at $1.20/M and context is near-tied (1.05M versus up to 1M). The batch row goes to Luna, with batch prices of $0.10/M input and $0.60/M output against MiniMax's none.
Which should you pick?
Choose GPT-5.6 Luna
Maximum-volume utility work: classification, formatting, routing. Luna's $0.20/$1.20 rates make it the cheaper per-token option of the two.
Choose MiniMax-M3
Workloads where MiniMax's reasoning profile specifically outperforms Luna at the task.