tokevenGPTvsMiniMax
GPT 5.6 Luna vs MiniMax M2
Side-by-side comparison of pricing, task quality, and projected cost at higher scale.
Pricing
Side-by-side pricing
GPT 5.6 Luna
Fast / BudgetMiniMax M2
Mid-tierInput $/MTok
$0.20
$0.26
Output $/MTok
$1.20
$1.00
Cache discount
90% off
0% off
Context
922K
200K
Quality
Task confidence comparison
Confidence score from zero to one hundred by task type, where higher is better.
Code Generation
62
vs
0
Code Review
68
vs
0
Summarization
57
vs
0
Q&A
85
vs
0
Extraction
74
vs
0
Reasoning
86
vs
0
Classification
91
vs
0
Creative Writing
69
vs
0
GPT 5.6 Luna
MiniMax M2
Guidance
When to use GPT 5.6 Luna vs MiniMax M2
Choose GPT 5.6 Luna when...
- -Cost matters: 23% cheaper on input tokens
- -You need a larger context window (922K vs 200K)
Choose MiniMax M2 when...
- Similar performance; consider provider preference or ecosystem fit.
At scale
Cost at scale
Estimated cost assuming a seventy percent input and thirty percent output token split.
GPT 5.6 Luna
MiniMax M2
100K tokens
$0.05
$0.05Cheaper
1M tokens
$0.82
$0.48Cheaper
10M tokens
$8.20
$4.82Cheaper
FAQ
When should I use GPT 5.6 Luna instead of MiniMax M2?
GPT 5.6 Luna and MiniMax M2 perform similarly across all tracked tasks. Pick based on pricing and provider preference.
Is MiniMax M2 cheaper than GPT 5.6 Luna?
MiniMax M2 input costs $0.26/MTok, which is 30% more than GPT 5.6 Luna at $0.20/MTok.
What are the context window sizes for GPT 5.6 Luna and MiniMax M2?
GPT 5.6 Luna has a 922K token context window. MiniMax M2 has a 200K token context window.
Go deeper on either model
Per-call cost calculators, provider lineups, and price history for both models on this page.
Other comparisons
How GPT 5.6 Luna and MiniMax M2 stack up against the rest of the field.
Track your real costs
Comparisons show estimated costs at list price. The dashboard reveals your real spend and savings.