AllocateMiniMax M2.7 FP4
Open weightsMiniMax M2.7 FP4 is a language model from MiniMaxAI with a 192K-token context window. Provider list price is $0.30 per million input tokens and $1.20 per million output; on Allocate you pay $0.32 and $1.28 with the 7% transaction fee. The weights are open, so you can fine-tune it and own the result.
Pricing
Token usage bills at the provider list price plus the 7% transaction fee. Prices checked 2026-07-08.
Price against its peers
Provider list prices per M tokens, MiniMax M2.7 FP4 against its nearest language peers by price.
What a real workload costs
Take 1,000,000 requests a month at 1,200 input and 350 output tokens each: 1,200M input and 350M output tokens. At list prices that is 1,200 × $0.30 + 350 × $1.20 = $780 a month. Billed on Allocate it is $834.60 with the 7% transaction fee.
MiniMax M2.7 FP4 is an open-weights model; the catalog does not list its license, so check the lab’s model card before commercial fine-tuning.
Example usage
Point a route at minimaxai/minimax-m2.7 and the endpoint never changes; swap the model behind it whenever you want.
curl https://api.allocate.network/v1/chat/completions \ -H "Authorization: Bearer $ALLOCATE_KEY" \ -d '{ "model": "minimaxai/minimax-m2.7", "messages": [{"role": "user", "content": "Summarise the attached contract."}] }'
Common questions
How much does MiniMax M2.7 FP4 cost per million tokens?
Provider list price is $0.30 per million input tokens and $1.20 per million output tokens. On Allocate you pay list plus the 7% transaction fee: $0.32 in and $1.28 out.
What context window does MiniMax M2.7 FP4 have?
196,608 tokens (192K). At roughly 0.75 words per token, that is about 147k words of English text per request.
What does cached input cost on MiniMax M2.7 FP4?
$0.06 per million tokens at list ($0.064 billed). Repeated prompt prefixes, such as a stable system prompt or tool definitions, bill at this rate instead of the full input price.
Can I fine-tune MiniMax M2.7 FP4?
Yes. MiniMax M2.7 FP4 is an open-weights model; check the lab’s model card for the exact license terms. Read the license terms before fine-tuning for commercial use. On Allocate the trained weights stay inside your boundary and belong to you.
How do I call MiniMax M2.7 FP4 on Allocate?
Send minimaxai/minimax-m2.7 in the model field of the OpenAI-compatible endpoint at api.allocate.network/v1, or point a route name (like prod/support-agent) at it so you can swap the model later without a deploy.