MiniMax M2.7 Turbo API Pricing
As of October 10, 2026, MiniMax M2.7 Turbo costs $0.38 per 1M input tokens and $1.70 per 1M output tokens on DeepInfra, with cache reads at $0.07 per 1M tokens. It has a 196,608-token context window.
- Input
- $0.38 / 1M tokens
- Output
- $1.70 / 1M tokens
- Cache read
- $0.07 / 1M tokens
- Context window
- 196,608 tokens
- Providers
- 1
- Added to LiteLLM
- August 27, 2026
MiniMax M2.7 Turbo pricing by provider
1 listing across 1 provider. Token prices are in US dollars per 1M tokens. The highlighted row is the price quoted above.
| Provider | Model name in LiteLLM | Input | Output | Cache read | Context |
|---|---|---|---|---|---|
| DeepInfra | deepinfra/MiniMaxAI/MiniMax-M2.7-Turbo | $0.38 | $1.70 | $0.07 | 192K |
What MiniMax M2.7 Turbo costs in practice
1,000 requests with 2,000 input and 500 output tokens each
| DeepInfra | $1.61 |
100 long-document requests with 100,000 input and 2,000 output tokens each
| DeepInfra | $4.14 |
MiniMax M2.7 Turbo features
- Function calling
- Structured output
- Image input
- Reasoning
- Prompt caching
Use MiniMax M2.7 Turbo with LiteLLM
Call MiniMax M2.7 Turbo through the LiteLLM Python SDK, or put it behind the LiteLLM proxy and send OpenAI-format requests to /v1/chat/completions. LiteLLM tracks the cost of every request at these prices.
from litellm import completion
response = completion(
model="deepinfra/MiniMaxAI/MiniMax-M2.7-Turbo",
messages=[{"role": "user", "content": "Hello!"}],
)model_list:
- model_name: minimax-m2.7-turbo
litellm_params:
model: deepinfra/MiniMaxAI/MiniMax-M2.7-Turbo
api_key: os.environ/DEEPINFRA_API_KEYcurl http://0.0.0.0:4000/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer sk-1234" \
-d '{
"model": "minimax-m2.7-turbo",
"messages": [{"role": "user", "content": "Hello!"}]
}'MiniMax M2.7 Turbo FAQ
How much does MiniMax M2.7 Turbo cost?
MiniMax M2.7 Turbo costs $0.38 per 1M input tokens and $1.70 per 1M output tokens on DeepInfra, with cache reads at $0.07 per 1M tokens.
What is the context window of MiniMax M2.7 Turbo?
MiniMax M2.7 Turbo has a 196,608-token context window.
Which providers offer MiniMax M2.7 Turbo?
MiniMax M2.7 Turbo is available from DeepInfra through LiteLLM, using the model name deepinfra/MiniMaxAI/MiniMax-M2.7-Turbo.
How do I call MiniMax M2.7 Turbo with an OpenAI-compatible API?
Use the LiteLLM Python SDK with model="deepinfra/MiniMaxAI/MiniMax-M2.7-Turbo", or add the model to the LiteLLM proxy's config.yaml and send requests to /v1/chat/completions from any OpenAI client. LiteLLM tracks the cost of every request at the prices on this page.
What features does MiniMax M2.7 Turbo support?
MiniMax M2.7 Turbo supports function calling, structured output, reasoning and prompt caching. It does not support image input.
When did LiteLLM add MiniMax M2.7 Turbo?
MiniMax M2.7 Turbo was added to LiteLLM's model price file on August 27, 2026.
Sources
Prices come from LiteLLM's open-source model_prices_and_context_window.json, which LiteLLM uses to calculate the cost of every request. Provider pricing pages:
LiteLLM docs: DeepInfra.
Provider pages: DeepInfra.
