LiteLLMModels

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.

By MiniMaxModel ID deepinfra/MiniMaxAI/MiniMax-M2.7-TurboPrices updated Checked
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.

ProviderModel name in LiteLLMInputOutputCache readContext
DeepInfradeepinfra/MiniMaxAI/MiniMax-M2.7-Turbo$0.38$1.70$0.07192K

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

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.

Python SDK
from litellm import completion

response = completion(
    model="deepinfra/MiniMaxAI/MiniMax-M2.7-Turbo",
    messages=[{"role": "user", "content": "Hello!"}],
)
Proxy config.yaml
model_list:
  - model_name: minimax-m2.7-turbo
    litellm_params:
      model: deepinfra/MiniMaxAI/MiniMax-M2.7-Turbo
      api_key: os.environ/DEEPINFRA_API_KEY
Call the proxy
curl 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.