xiaomi/mimo-v2.5-pro
Date de publication: 2026-04-23
1,048,576 context · $1.00/M input tokens · $3.00/M output tokens
MiMo-V2.5-Pro is Xiaomi’s flagship open model for advanced agentic workflows, complex software engineering, and long-horizon task execution. Built on a sparse Mixture-of-Experts architecture with 1.02T total parameters and 42B active parameters, it supports a 1M-token context window and is optimized for autonomous coding agents, large codebase reasoning, tool-use workflows, and multi-step problem solving. It delivers strong performance on agentic and software engineering benchmarks such as ClawEval, GDPVal, and SWE-bench Pro, with an emphasis on token-efficient long-context execution.
Paiement à l'usage
Aucun coût initial, payez uniquement ce que vous utilisez
Utilisez les exemples de code suivants pour intégrer notre API :
import OpenAI from 'openai';
if (!process.env.WAVESPEED_API_KEY) throw new Error('Set WAVESPEED_API_KEY');
const client = new OpenAI({
apiKey: process.env.WAVESPEED_API_KEY,
baseURL: 'https://llm.wavespeed.ai/v1',
timeout: 120_000,
maxRetries: 2,
});
try {
const response = await client.chat.completions.create({
model: 'xiaomi/mimo-v2.5-pro',
messages: [{ role: 'user', content: 'Hello!' }],
});
console.log(response.choices[0]?.message?.content ?? '');
} catch (error) {
console.error('LLM request failed:', error);
process.exitCode = 1;
}import OpenAI from 'openai';
if (!process.env.WAVESPEED_API_KEY) throw new Error('Set WAVESPEED_API_KEY');
const client = new OpenAI({
apiKey: process.env.WAVESPEED_API_KEY,
baseURL: 'https://llm.wavespeed.ai/v1',
timeout: 120_000,
maxRetries: 2,
});
try {
const response = await client.chat.completions.create({
model: 'xiaomi/mimo-v2.5-pro',
messages: [{ role: 'user', content: 'Hello!' }],
});
console.log(response.choices[0]?.message?.content ?? '');
} catch (error) {
console.error('LLM request failed:', error);
process.exitCode = 1;
}MiMo-V2.5-Pro is Xiaomi’s flagship open model for advanced agentic workflows, complex software engineering, and long-horizon task execution. Built on a sparse Mixture-of-Experts architecture with 1.02T total parameters and 42B active parameters, it is optimized for autonomous coding agents, large codebase reasoning, tool use, and multi-step problem solving.
| Specification | Value |
|---|---|
| Provider | xiaomi |
| Model Type | Chat Completions model |
| Architecture | Sparse Mixture-of-Experts |
| Parameters | 1.02T total / 42B active |
| Context Window | 1,048,576 tokens |
| Max Input | 1,032,192 tokens |
| Max Output | 16,384 tokens |
| Input | Text |
| Output | Text |
| Vision | Not listed |
| Function Calling | Supported |
| Structured Outputs | Supported |
| Primary Use Cases | Agentic coding, complex software engineering, long-horizon tasks, tool use |
| Token Type | Cost |
|---|---|
| Input | $1.00 per million tokens |
| Output | $3.00 per million tokens |
| Cached Input | $0.20 per million tokens |
Base URL: https://llm.wavespeed.ai/v1
API Endpoint: chat/completions
Model ID: xiaomi/mimo-v2.5-pro
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://llm.wavespeed.ai/v1"
)
response = client.chat.completions.create(
model="xiaomi/mimo-v2.5-pro",
messages=[{"role": "user", "content": "Hello!"}]
)
print(response.choices[0].message.content)curl https://llm.wavespeed.ai/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '{
"model": "xiaomi/mimo-v2.5-pro",
"messages": [{"role": "user", "content": "Hello!"}]
}'xiaomi/mimo-v2.5-pro
MiMo-V2.5-Pro is Xiaomi’s flagship open model for advanced agentic workflows, complex software engineering, and long-horizon task execution. Built on a sparse Mixture-of-Experts architecture with 1.02T total parameters and 42B active parameters, it supports a 1M-token context window and is optimized for autonomous coding agents, large codebase reasoning, tool-use workflows, and multi-step problem solving. It delivers strong performance on agentic and software engineering benchmarks such as ClawEval, GDPVal, and SWE-bench Pro, with an emphasis on token-efficient long-context execution.
Entrée
$1 /M
Sortie
$3 /M
Contexte
1049K
Sortie max.
16K
Utilisation d'outils
Pris en charge
Accédez à Mimo V2.5 Pro via notre API unifiée — compatible OpenAI, sans démarrages à froid, prix transparents.
Tarification sur WaveSpeedAI : $1.00 par million de tokens d'entrée et $3.00 par million de tokens de sortie. Le prompt caching et le traitement par batch sont facturés séparément et réduisent le coût effectif sur les charges longues et répétitives.
Mimo V2.5 Pro prend en charge jusqu'à 1049K tokens de contexte et jusqu'à 16K tokens de sortie par requête.
WaveSpeedAI expose Mimo V2.5 Pro à https://llm.wavespeed.ai/v1 via l’interface Chat Completions compatible OpenAI. La plupart des clients du SDK OpenAI fonctionnent en changeant l’URL de base et la clé API ; les champs facultatifs dépendent du modèle.
Connectez-vous à WaveSpeedAI, créez une clé API dans Access Keys, puis envoyez une requête à https://llm.wavespeed.ai/v1/chat/completions avec l’id du modèle affiché ci-dessus. Consultez le catalogue actuel pour la disponibilité, les capacités et les tarifs.