MiniMax M2.7 vs MiniMax M3

As of October 21, 2026, MiniMax M3 costs 20% more per input token than MiniMax M2.7 ($0.30 vs $0.25 per 1M) and has a 1M-token context window versus 192K.

Prices from LiteLLM's price fileChecked October 21, 2026

MiniMax M2.7 vs MiniMax M3 side by side

Headline prices in US dollars per 1M tokens: each model's own lab where it sells it, otherwise its cheapest provider. Source: LiteLLM model price file, as of October 21, 2026.
	MiniMax M2.7	MiniMax M3
Input, per 1M tokens	$0.25	$0.30
Output, per 1M tokens	$1.00	$1.20
Cache read, per 1M tokens	$0.05	$0.06
Cache write, per 1M tokens	–	–
Context window	196,608 tokens	1,000,000 tokens
Max output	204,800 tokens	128,000 tokens
Image input	No	Yes
Tool calling	Yes	Yes
Structured output (JSON)	Yes	Yes
Prompt caching	Yes	Yes
Reasoning	Yes	Yes
Providers on LiteLLM	7	10
Price shown is from	DeepInfra	MiniMax
Added to LiteLLM	May 2026	June 2026

Cheapest provider for each

MiniMax M2.7: DeepInfra at $0.25 input and $1.00 output per 1M tokens (deepinfra/MiniMaxAI/MiniMax-M2.7)
MiniMax M3: Weights & Biases at $0.23 input and $0.96 output per 1M tokens (wandb/MiniMaxAI/MiniMax-M3)

When to pick which

Pick MiniMax M2.7 for

Costs 17% less per input token: $0.25 vs $0.30 per 1M.
Returns up to 204,800 tokens per response, vs 128,000.

Pick MiniMax M3 for

Larger context window: 1,000,000 vs 196,608 tokens.
Supports image input, which MiniMax M2.7 doesn't list.

From differences in the data above only; where the data is equal, no reason is given.

Call MiniMax M2.7 or MiniMax M3 with LiteLLM

Both use the OpenAI format through LiteLLM, so switching is a model name change. Set each provider's API key in the environment first.

Python SDK

from litellm import completion

messages = [{"role": "user", "content": "Hello!"}]

# MiniMax M2.7
response = completion(model="deepinfra/MiniMaxAI/MiniMax-M2.7", messages=messages)

# MiniMax M3
response = completion(model="minimax/MiniMax-M3", messages=messages)

# MiniMax M2.7, falling back to MiniMax M3 if the call fails
response = completion(model="deepinfra/MiniMaxAI/MiniMax-M2.7", messages=messages, fallbacks=["minimax/MiniMax-M3"])

FAQ

Which is cheaper, MiniMax M2.7 or MiniMax M3?

MiniMax M2.7 is cheaper at 3 input tokens per output token: $0.4375 per 1M tokens blended ($0.25 input, $1.00 output), versus $0.525 ($0.30 and $1.20) for MiniMax M3, as of October 21, 2026.

Which has the larger context window, MiniMax M2.7 or MiniMax M3?

MiniMax M3 has the larger context window: 1,000,000 tokens, versus 196,608 for MiniMax M2.7.

Can I switch from MiniMax M2.7 to MiniMax M3 without changing my code?

Yes. Through LiteLLM both use the OpenAI format, so switching means changing the model name from "deepinfra/MiniMaxAI/MiniMax-M2.7" to "minimax/MiniMax-M3", or pointing a LiteLLM gateway model alias at the other model. You can also use one as a fallback for the other.