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minimax-m2.5

MiniMax M2.5 is MiniMax's latest large language model, delivering strong performance across reasoning, coding, and tool use with improved efficiency for production workloads.

ReasoningTool callingJSON schema
CompareDocs

Specifications

Context window128K tokens
Max output16K tokens
API typechat
AddedMay 31, 2026
Model IDbedrock/minimax-m2.5@us-west-2
Data retentionNo
Used for trainingNo
Provider location🇺🇸 US / 🇪🇺 EU
Privacy policyAWS Privacy Notice→

Benchmarks

Released 2026-02-12
GPQA Diamondreasoning
84.8%

Graduate-level physics, chemistry & biology questions designed to resist Googling.

Intelligence Indexreasoning
33.7%

Artificial Analysis Intelligence Index — a composite of multiple evaluations measuring overall model capability.

Scores are sourced from official model cards, Artificial Analysis, and public leaderboards. Benchmarks measure specific skills and do not capture every aspect of model quality. Always test on your own workload.

Pricing

Input / 1M
$0.30
Output / 1M
$1.20
Cache write
N/A
Cache read
N/A
Estimated cost
100K input + 10K output$0.0420
1M input + 100K output$0.42
10M input + 1M output$4.20

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 bedrock/minimax-m2.5@us-west-2.

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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="bedrock/minimax-m2.5@us-west-2",
    messages=[
        {"role": "user", "content": "Explain quantum computing in one paragraph."},
    ],
)

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

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Frequently asked questions

How much does minimax-m2.5 cost?
minimax-m2.5 is priced at $0.30 per million input tokens and $1.20 per million output tokens when accessed via Requesty. Requesty charges exactly what the upstream provider charges, we don't add markup.
What is the context window of minimax-m2.5?
minimax-m2.5 has a context window of 128K tokens, with a maximum output of 16K tokens per response. That's roughly 171 words of input you can fit in a single prompt.
How does minimax-m2.5 perform on benchmarks?
minimax-m2.5 scores 95.3% on τ²-Bench, 84.8% on GPQA Diamond, 42.6% on SciCode. See the full benchmark chart above for results across MMLU Pro, GPQA Diamond, SWE-Bench Verified, HumanEval, MATH, AIME, MMMU, and LiveBench.
What can minimax-m2.5 do?
minimax-m2.5 supports tool calling, extended reasoning, structured outputs (JSON schema). You can call it through any OpenAI-compatible client by pointing base_url to Requesty.
How do I use minimax-m2.5 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 "bedrock/minimax-m2.5@us-west-2". The Quickstart above shows Python, JavaScript and cURL snippets.
Can I run minimax-m2.5 through Requesty?
Yes. minimax-m2.5 runs through Requesty's OpenAI-compatible API, served from AWS Bedrock in us-west-2. You do not host the model yourself: point base_url at Requesty, set the model to "bedrock/minimax-m2.5@us-west-2", and requests are routed to the upstream provider with automatic failover. The same key gives you 400+ other models too.
What region is this deployment?
This variant of minimax-m2.5 is deployed in us-west-2. Region-specific endpoints matter for data residency, latency to your users, and compliance requirements (GDPR, HIPAA). Other regions for the same model may be listed on the AWS Bedrock provider page.

Access minimax-m2.5 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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