MiniMax M1
by MiniMax · minimax/minimax-m1 · #220 cheapest of 422 paid models
Prices updated Sep 19, 2026, 6:22 PM UTC · refreshed hourly
MiniMax-M1 is a large-scale, open-weight reasoning model designed for extended context and high-efficiency inference. It leverages a hybrid Mixture-of-Experts (MoE) architecture paired with a custom "lightning attention" mechanism, allowing it...
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Pricing
Input
$0.40
per 1M tokens
Output
$2.20
per 1M tokens
Blended (3:1)
$0.85
3 input : 1 output
Cache read
—
per 1M cached tokens
Cache write
—
per 1M tokens
Cache & batch economics
Effective prices for MiniMax M1 (no cache-read rate published — hits billed as normal input).
| Cache hit rate | Effective blended $/1M | Example request* | vs no cache |
|---|---|---|---|
| 0% | $0.85 | $0.043 | — |
| 50% | $0.85 | $0.043 | −0% |
| 90% | $0.85 | $0.043 | −0% |
*Example: 100K sticky context + 2K new input + 1K output. Batch discount is an approximate 50% off list rates (available for OpenAI / Anthropic / Google — not flagged for this creator). Confirm on the vendor’s pricing page.
What a request costs
| Workload | Input tokens | Output tokens | Cost / request | Cost / 1K requests |
|---|---|---|---|---|
| Short chat message | 500 | 300 | $0.00086 | $0.86 |
| Document summary | 8,000 | 1,000 | $0.0054 | $5.40 |
| Codebase question (RAG) | 30,000 | 2,000 | $0.0164 | $16.40 |
| Long-context analysis | 150,000 | 5,000 | $0.071 | $71.00 |
Specs
Context window
1M
tokens
Max output
40K
tokens
Input modalities
text
Tokenizer
Other