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MiniMax

minimax-m3

MiniMax M3 is a frontier multimodal model with a 1M-token context window built on MiniMax Sparse Attention (MSA). It reaches frontier-level performance on coding and agentic tasks, surpassing GPT-5.5 and Gemini 3.1 Pro on SWE-Bench Pro and approaching Claude Opus 4.7. It natively supports image and video input and is the first open-weight model to combine frontier coding, ultra-long context, and native multimodality.

👁Vision🧠Reasoning🔧Tool calling⚡Caching
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Specifications

Context window1M tokens
Max output128K tokens
API typechat
AddedJun 1, 2026
Model IDminimaxi/minimax-m3
Data retentionYes
Used for trainingUnknown
Provider location🇸🇬 Singapore
Privacy policyMiniMax Privacy Policy→

Benchmarks

Benchmarks haven't been published yet for this exact variant.

Some variants (region-specific deployments, highspeed tiers) share benchmarks with their base model — check the base model page or the MiniMax models overview.

Pricing

Input / 1M
$0.60
Output / 1M
$2.40
Cache write
—
Cache read / 1M
$0.12
Estimated cost
100K input + 10K output$0.0840
1M input + 100K output$0.84
10M input + 1M output$8.40

Requesty charges exactly what the upstream provider charges — no markup, no per-request fees. Prompt caching and smart routing can reduce effective cost by 30-80%.

Quickstart

Drop-in compatible with the OpenAI SDK. Change the base URL, swap in your Requesty API key, and set the model to minimaxi/minimax-m3.

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from openai import OpenAI

client = OpenAI(
    api_key="YOUR_REQUESTY_API_KEY",
    base_url="https://router.requesty.ai/v1",
)

response = client.chat.completions.create(
    model="minimaxi/minimax-m3",
    messages=[
        {"role": "user", "content": "Explain quantum computing in one paragraph."},
    ],
)

print(response.choices[0].message.content)

Other MiniMax models

MiniMax-M2.7
200K ctx$0.30/1M
MiniMax-M2.7-highspeed
200K ctx$0.60/1M
MiniMax-M2.5-highspeed
200K ctx$0.60/1M
MiniMax-M2.5
200K ctx$0.30/1M
MiniMax-M2
200K ctx$0.30/1M
SWE-Bench 69%

Frequently asked questions

How much does minimax-m3 cost?
minimax-m3 is priced at $0.60 per million input tokens and $2.40 per million output tokens when accessed via Requesty. Prompt caching is supported, which can cut effective input cost by up to 90% on repeated context. Requesty charges exactly what the upstream provider charges — we don't add markup.
What is the context window of minimax-m3?
minimax-m3 has a context window of 1M tokens, with a maximum output of 128K tokens per response. That's roughly 1,333 words of input you can fit in a single prompt.
What can minimax-m3 do?
minimax-m3 supports vision input, tool calling, extended reasoning, prompt caching. You can call it through any OpenAI-compatible client by pointing base_url to Requesty.
How do I use minimax-m3 with the OpenAI SDK?
Install the OpenAI SDK, set base_url to "https://router.requesty.ai/v1", set your API key to your Requesty key, and set the model to "minimaxi/minimax-m3". The Quickstart above shows Python, JavaScript and cURL snippets.

Access minimax-m3 through Requesty

One API key, 400+ models, OpenAI-compatible. No markup on provider prices, automatic failover, and smart caching built-in.

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