MiniMax M2.5

适合文本、图像与智能体推理的多模态旗舰模型，编码表现也很强。

SWE-Bench 80.2%公开模型详情MoE Transformer

参数规模

229B MoE

上下文

192K

最大输出

64K

许可证

Modified MIT

TTFT

160ms

吞吐

120 tok/s

为什么选它

默认多模态
适合产品 Copilot 与顾问式应用

价格与差价

层级标准缓存SiliconFlow节省

在线调用$0.10 / $0.40$0.035$0.30 / $1.2067%

批处理$0.05 / $0.20$0.035$0.30 / $1.2067%

快速开始

OpenAI 兼容接口，切换 base_url 即可。

在 Playground 中试用查看价格页

Python

from openai import OpenAI

client = OpenAI(
    base_url="https://api.luminapath.tech/v1",
    api_key="BATCHIN_API_KEY"
)

resp = client.chat.completions.create(
    model="minimax-m2.5",
    messages=[{"role": "user", "content": "Summarize why this model is a fit for my workload."}]
)

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

JavaScript

import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://api.luminapath.tech/v1",
  apiKey: process.env.BATCHIN_API_KEY,
});

const resp = await client.chat.completions.create({
  model: "minimax-m2.5",
  messages: [{ role: "user", content: "Summarize why this model is a fit for my workload." }],
});

console.log(resp.choices[0]?.message?.content);

cURL

curl https://api.luminapath.tech/v1/chat/completions \
  -H "Authorization: Bearer $BATCHIN_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "minimax-m2.5",
    "messages": [{"role":"user","content":"Summarize why this model is a fit for my workload."}]
  }'

规格与行为

架构

MoE Transformer

厂商家族

MiniMax

上下文

192K

最大输出

64K

适用场景

multimodal

vision