mistralai/mistral-small-24b-instruct-2501
Data di rilascio: 2025-01-31
32,768 context · $0.05/M input tokens · $0.08/M output tokens
Mistral Small 3 is a 24B-parameter language model optimized for low-latency performance across common AI tasks. Released under the Apache 2.0 license, it features both pre-trained and instruction-tuned versions designed...
Prezzi
Pay-per-use
Nessun costo iniziale, paga solo per ciò che usi
Prova il modello
Utilizzo API
Usa i seguenti esempi di codice per integrare la nostra 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: 'mistralai/mistral-small-24b-instruct-2501',
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: 'mistralai/mistral-small-24b-instruct-2501',
messages: [{ role: 'user', content: 'Hello!' }],
});
console.log(response.choices[0]?.message?.content ?? '');
} catch (error) {
console.error('LLM request failed:', error);
process.exitCode = 1;
}Introduzione al modello
Mistralai mistral-small-24b-instruct-2501
Mistral Small 3 is a 24B-parameter language model optimized for low-latency performance across common AI tasks
Mistral Small 3 is a 24B-parameter language model optimized for low-latency performance across common AI tasks. Released under the Apache 2.0 license, it features both pre-trained and instruction-tuned versions designed for efficient local deployment.
The model achieves 81% accuracy on the MMLU benchmark and performs competitively with larger models like Llama 3.3 70B and Qwen 32B, while operating at three times the speed on equivalent hardware. Read the blog post about the model here.
Why It Looks Great
- Large Language Model architecture for efficient processing
- 32768 context window for long document handling
- Competitive pricing at $0.0/$0.1 per million tokens
Key Features
- Context Window: 32768 tokens
- Max Output: 16384 tokens
- Vision: Supported
- Function Calling: Supported
Specifications
| Specification | Value |
|---|---|
| Provider | Mistralai |
| Model Type | Large Language Model (LLM) |
| Architecture | N/A |
| Context Window | 32768 tokens |
| Max Output | 16384 tokens |
| Input | Text |
| Output | Text |
| Vision | Supported |
| Function Calling | Supported |
Pricing
| Token Type | Cost per Million Tokens |
|---|---|
| Input | $0.0 |
| Output | $0.1 |
How to Use
- Write your prompt — describe the task, provide context, and specify desired output format.
- Submit — the model processes your request and returns the response.
API Integration
Base URL: https://llm.wavespeed.ai/v1 API Endpoint: chat/completions Model ID: mistralai/mistral-small-24b-instruct-2501
API Usage
Python SDK
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://llm.wavespeed.ai/v1"
)
response = client.chat.completions.create(
model="mistralai/mistral-small-24b-instruct-2501",
messages=[
{"role": "user", "content": "Hello!"}
]
)
print(response.choices[0].message.content)cURL
curl https://llm.wavespeed.ai/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '{
"model": "mistralai/mistral-small-24b-instruct-2501",
"messages": [{"role": "user", "content": "Hello!"}]
}'Notes
- Model: mistralai/mistral-small-24b-instruct-2501
- Provider: Mistralai
Info
Funzionalità supportate
Guida all'accesso API
Mistral Small 24b Instruct 2501 API
mistralai/mistral-small-24b-instruct-2501
Mistral Small 3 is a 24B-parameter language model optimized for low-latency performance across common AI tasks. Released under the Apache 2.0 license, it features both pre-trained and instruction-tuned versions designed...
Input
$0.05 /M
Output
$0.08 /M
Contesto
33K
Output max
16K
Uso strumenti
Supportato
Prova Mistral Small 24b Instruct 2501 su WaveSpeedAI
Accedi a Mistral Small 24b Instruct 2501 tramite la nostra API unificata — compatibile con OpenAI, senza cold start, prezzi trasparenti.
Domande frequenti su Mistral Small 24b Instruct 2501
Quanto costa Mistral Small 24b Instruct 2501 via API?+
Prezzi su WaveSpeedAI: $0.05 per milione di token in input e $0.08 per milione di token in output. Prompt caching e batch processing sono fatturati separatamente e riducono il costo effettivo su carichi lunghi e ripetitivi.
Qual è la context window di Mistral Small 24b Instruct 2501?+
Mistral Small 24b Instruct 2501 supporta fino a 33K token di contesto e fino a 16K token di output per richiesta.
Mistral Small 24b Instruct 2501 è compatibile con OpenAI?+
WaveSpeedAI espone Mistral Small 24b Instruct 2501 su https://llm.wavespeed.ai/v1 tramite l’interfaccia Chat Completions compatibile con OpenAI. Per la maggior parte dei client OpenAI SDK basta cambiare base URL e API key; i campi opzionali dipendono dal modello.
Come si inizia con Mistral Small 24b Instruct 2501?+
Accedi a WaveSpeedAI, crea una API key in Access Keys e invia una richiesta a https://llm.wavespeed.ai/v1/chat/completions con il model id mostrato sopra. Consulta il catalogo attuale per disponibilità, funzionalità e prezzi.