MiniMax M2.7
Pricing as of October 2026$0.300/1M input · $1.20/1M output · 205K context · MiniMax
MiniMax M2.7 costs $0.300 per 1M input tokens and $1.20 per 1M output tokens from MiniMax, with a 205K-token context window. A typical chat reply (1,500 tokens in, 400 out) costs $0.0009, or $9.30 per 10,000 requests. On that workload it is cheaper than 122 of the 172 other buyable models tracked here.
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What MiniMax M2.7 Costs Per Request
At $0.300 per 1M input and $1.20 per 1M output tokens, before caching or batch discounts.
| Workload | Input / output tokens | Per request | Per 10,000 requests |
|---|---|---|---|
| Chat reply | 1,500 / 400 | $0.0009 | $9.30 |
| RAG answer over retrieved docs | 8,000 / 600 | $0.0031 | $31.20 |
| Coding-agent step | 30,000 / 2,000 | $0.011 | $114.00 |
MiniMax M2.7 vs Similarly Priced Models
Nearest buyable models by price, with the RAG answer above (8,000 in / 600 out) priced on each.
| Model | Input /1M | Output /1M | Context | RAG answer |
|---|---|---|---|---|
| MiniMax M2.7 MiniMax | $0.300 | $1.20 | 205K | $0.0031 |
| MiniMax M3 MiniMax | $0.300 | $1.20 | 1.0M | $0.0031 |
| GPT-5.4 Nano OpenAI | $0.200 | $1.25 | 400K | $0.0024 |
| Qwen3-Next-80B-A3B-Thinking Alibaba | $0.150 | $1.20 | 262K | $0.0019 |
Alternatives to MiniMax M2.7
Pricing Details
MiniMax230B total / 10B active MoE, 256 experts. OpenRouter: $0.279/$1.20. Cached input ~$0.06/1M (semi-confirmed). Highest open-weight GDPval-AA ELO at 1495. SWE-Bench Pro 56.22, SWE-Bench Multilingual 76.5, MLE-Bench Lite medal 66.6%. SWE-Bench Verified not officially published.
Input / 1M tokens
$0.3
Output / 1M tokens
$1.2
Context Window
205K
Max Output
131K
Price History
No price change recorded since 2026-08-11, when this site started tracking this model; it launched on 2026-03-18.
Frequently Asked Questions
Common questions about MiniMax M2.7 pricing and usage
How much does MiniMax M2.7 cost?
MiniMax M2.7 costs $0.3 per 1 million input tokens and $1.2 per 1 million output tokens. This pricing is set by MiniMax.
What tokenizer does MiniMax M2.7 use?
MiniMax M2.7 uses the cl100k_base tokenizer. This tokenizer has a vocabulary of ~100,000 tokens and is widely used across many models.
What is MiniMax M2.7's context window?
MiniMax M2.7 supports a context window of 205K tokens (204,800 tokens). The maximum output length is 131K tokens.
How does MiniMax M2.7 compare to other models?
On an 8,000-token-in, 600-token-out RAG answer, MiniMax M2.7 costs $0.0031 per request. The nearest-priced alternatives cost: MiniMax M3 (MiniMax) $0.0031, GPT-5.4 Nano (OpenAI) $0.0024, Qwen3-Next-80B-A3B-Thinking (Alibaba) $0.0019. The table above lists their full rates and context windows.
How do I count tokens for MiniMax M2.7?
Use the token counter at the top of this page or visit the homepage calculator. Paste your text and it will show the exact token count and cost for MiniMax M2.7 using the cl100k_base tokenizer.