Devstral Small | Mistral AI Lightweight Coding API

Name: Devstral Small API
Brand: mistralai
Price: 0.1 USD
Availability: InStock

Utilizzo API

Usa i seguenti esempi di codice per integrare la nostra API:

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/devstral-small",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)

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

Introduzione al modello

Mistralai devstral-small

Devstral Small 1

Devstral Small 1.1 is a 24B parameter open-weight language model for software engineering agents, developed by Mistral AI in collaboration with All Hands AI. Finetuned from Mistral Small 3.1 and released under the Apache 2.0 license, it features a 128k token context window and supports both Mistral-style function calling and XML output formats.

Designed for agentic coding workflows, Devstral Small 1.1 is optimized for tasks such as codebase exploration, multi-file edits, and integration into autonomous development agents like OpenHands and Cline. It achieves 53.6% on SWE-Bench Verified, surpassing all other open models on this benchmark, while remaining lightweight enough to run on a single 4090 GPU or Apple silicon machine. The model uses a Tekken tokenizer with a 131k vocabulary and is deployable via vLLM, Transformers, Ollama, LM Studio, and other OpenAI-compatible runtimes.

Why It Looks Great

Large Language Model architecture for efficient processing
131072 context window for long document handling
Competitive pricing at $0.1/$0.3 per million tokens

Key Features

Context Window: 131072 tokens
Max Output: N/A tokens
Vision: Supported
Function Calling: Supported

Specifications

Specification	Value
Provider	Mistralai
Model Type	Large Language Model (LLM)
Architecture	N/A
Context Window	131072 tokens
Max Output	tokens
Input	Text
Output	Text
Vision	Supported
Function Calling	Supported

Pricing

Token Type	Cost per Million Tokens
Input	$0.1
Output	$0.3

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/devstral-small

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/devstral-small",
    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/devstral-small",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Notes

Model: mistralai/devstral-small
Provider: Mistralai

Domande frequenti su Devstral Small

Quanto costa Devstral Small via API?+

Prezzi su WaveSpeedAI: $0.10 per milione di token in input e $0.30 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 Devstral Small?+

Devstral Small supporta fino a 131K token di contesto e fino a — token di output per richiesta.

Devstral Small è compatibile con OpenAI?+

Sì. WaveSpeedAI espone Devstral Small tramite un endpoint compatibile con OpenAI all'indirizzo https://llm.wavespeed.ai/v1. Punta l'SDK ufficiale di OpenAI a questa base URL con la tua API key WaveSpeedAI — senza altre modifiche al codice.

Come si inizia con Devstral Small?+

Accedi a WaveSpeedAI, crea una API key in Access Keys, poi invia una richiesta a https://llm.wavespeed.ai/v1/chat/completions con il model id mostrato sopra. I nuovi account ricevono crediti gratuiti per testare Devstral Small.

Prezzi

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