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MiniMax M2.1

invited beta chatCodeReasoningTool calling

MiniMax M2.1 agentic/coding model.

Input
$0.3/M
Output
$1.2/M
Cache read
$0.06/M
Context
205K
vs GPT-4o
~94% cheaper

Benchmarks

Above average0 / 6
MiniMax M2.1 other models measured peer average ★ no peer scored higher
SciCode
41%
GPQA Diamond
83%

Vendor-published: Alibaba (Qwen) Anthropic ByteDance DeepSeek Google MiniMax Moonshot OpenAI Tencent Z.ai

Price in context

Where the price sits among 68 comparable models

Input$0.3/M
$0.1 · Dola Seed 2.0 Mini GPT-5.4 Pro · $30
Output$1.2/M
$0.275 · DeepSeek V4 Flash GPT-5.4 Pro · $180
Cache read$0.06/M
$0.01 · Claude Haiku 5.5 GPT-5.4 Pro · $15

The bar shows how this model’s price compares with every other model of the same kind on Synthorai. The cheapest and the most expensive are named at each end. These are base rates; batch, region and cache-write discounts are on the pricing page.

Specs & limits

Prompt caching

How it caches automatic
Min prefix 512

Use MiniMax M2.1 in 30 seconds

OpenAI-compatible: swap the base_url, keep your SDK. POST /v1/chat/completions

from openai import OpenAI

client = OpenAI(
    base_url="https://synthorai.io/v1",
    api_key="sk-syn-...",
)

resp = client.chat.completions.create(
    model="minimax-m2.1",
    messages=[{"role": "user", "content": "Summarize this diff"}],
    reasoning_effort="medium",
)
print(resp.choices[0].message.content)

FAQ

Is the MiniMax M2.1 API free to try?

MiniMax M2.1 is currently in invited beta: access is application-based rather than open signup. Apply from the Synthorai console; once approved, standard pay-as-you-go pricing applies with no subscription.

How much does MiniMax M2.1 cost?

MiniMax M2.1 costs $0.3 per million input tokens and $1.2 per million output tokens on Synthorai. That is the provider's list price, with no platform markup. Cached input tokens bill at $0.06/M.

What is MiniMax M2.1's context window?

MiniMax M2.1 has a context window of 205K tokens on Synthorai.

Does MiniMax M2.1 support prompt caching?

Yes, automatically: MiniMax-served prompts cache with no code changes. Cached input tokens bill at $0.06/M vs $0.3/M uncached; prompts need a 512-token stable prefix to cache. Prompt caching guide →

How do I get access to MiniMax M2.1?

MiniMax M2.1 is in invited beta: request access from the Synthorai console. Once approved it works like every other model: point your OpenAI SDK at base_url="https://synthorai.io/v1" and set model="minimax-m2.1".

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Every value on this page is transcribed from the vendor's own documentation, linked above, and carries the date it was checked. Prices are compared across the catalogue; specification values that vendors define differently are shown with the difference stated rather than charted. Nothing here is measured by us, and nothing is scored.

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