text·image·video
Minimax M3
silvamux/
minimax-m3Minimax M3面向文档分析、信息抽取与复杂语义理解提供稳定的模型能力,优势集中在文本理解和长文本处理,并支持图像、视频信息输入。适合需要兼顾任务理解与结果质量的产品和研发团队。
Pricing
Tiers are determined by the input context length of each request; Tune and Pro share the same tiered prices.
| Input context | Input | Output | Cache read | Cache write |
|---|---|---|---|---|
| ≤ 512K tokens | ¥2.1 | ¥8.4 | ¥0.21 | ¥2.1 |
| > 512K tokens | ¥4.2 | ¥16.8 | ¥0.84 | ¥4.2 |
Capabilities
MiniMax M3 综合得分 62,整体能力中等,是一款多语言处理见长的通用模型。多语言能力(77%)为其最强项,跨语言内容理解与生成稳定,在多语言翻译、内容审核与风控等文本理解分析场景中可用性尚可。相对而言,代码理解与调试(35%)明显不足,在复杂代码任务上能力有限。对语言类任务它仍是务实之选,代码类任务则需搭配其他模型。
62/ 100
专项进阶能力
8 items数学与科学推理63%
14 questions · 主/客观混合
代码生成33%
12 questions · 客观
代码理解与调试35%
6 questions · 主观
长文本处理70%
16 questions · 主观
智能体协同69%
18 questions · 主/客观混合
创意写作63%
22 questions · 主观
多语言能力77%
11 questions · 主观
信息检索 / RAG58%
9 questions · 主/客观混合
通用基础能力
3 items通识知识63%
10 questions · 主/客观混合
文本理解72%
23 questions · 主观
逻辑推理67%
16 questions · 主/客观混合
安全与合规能力
2 items幻觉控制73%
15 questions · 主观
指令遵循59%
18 questions · 主观
Performance
Minimax M3
minimax-m3Last 24 hours · 112,895 requests
- First token · TTFT · P50
- 1365ms P95 2256 ms
- Output speed · TPS · P50
- 95tok/s P95 99 tok/s
- Full response · E2E · P50
- 8.86s P95 9.19 s
- Request success rate
- 99.55% 112,392 completed requests
24-hour availability
24 hours ago12 hours agoNow
Minimax M3 example code and API
Pro
minimax-m3/api/v0/chat/completions/api/v1/responses/api/anthropic/v1/messagescurl https://www.silvamux.com/api/v1/chat/completions \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "minimax-m3",
"messages": [{"role": "user", "content": "Hello, please introduce yourself"}]
}'# pip install openai
from openai import OpenAI
client = OpenAI(
base_url="https://www.silvamux.com/api/v1",
api_key="YOUR_API_KEY",
)
response = client.chat.completions.create(
model="minimax-m3",
messages=[
{"role": "user", "content": "Hello, please introduce yourself"}
],
)
print(response.choices[0].message.content)// Gradle: implementation(__HL_SLOT_0__)
import okhttp3.*;
OkHttpClient client = new OkHttpClient();
MediaType json = MediaType.get("application/json");
String payload = "{\"model\":\"minimax-m3\",\"messages\":[{\"role\":\"user\",\"content\":\"Hello, please introduce yourself\"}]}";
Request request = new Request.Builder()
.url("https://www.silvamux.com/api/v1/chat/completions")
.header("Authorization", "Bearer YOUR_API_KEY")
.post(RequestBody.create(payload, json))
.build();
try (Response response = client.newCall(request).execute()) {
System.out.println(response.body().string());
}// npm install openai
import OpenAI from 'openai'
const client = new OpenAI({
baseURL: 'https://www.silvamux.com/api/v1',
apiKey: 'YOUR_API_KEY',
})
const response = await client.chat.completions.create({
model: 'minimax-m3',
messages: [{ role: 'user', content: 'Hello, please introduce yourself' }],
})
console.log(response.choices[0].message.content)