mistralai/mistral-small-24b-instruct-2501
Release date: 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...
Pricing
Pay-per-use
No upfront costs, pay only for what you use
Try the model
API Usage
Use the following code examples to integrate with our 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: 0,
});
try {
const response = await client.chat.completions.create({
model: 'mistralai/mistral-small-24b-instruct-2501',
messages: [{ role: 'user', content: 'Hello!' }],
});
const body = response as typeof response & { error?: { message?: string } };
if (body.error) throw new Error(body.error.message || 'LLM generation failed');
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: 0,
});
try {
const response = await client.chat.completions.create({
model: 'mistralai/mistral-small-24b-instruct-2501',
messages: [{ role: 'user', content: 'Hello!' }],
});
const body = response as typeof response & { error?: { message?: string } };
if (body.error) throw new Error(body.error.message || 'LLM generation failed');
console.log(response.choices[0]?.message?.content ?? '');
} catch (error) {
console.error('LLM request failed:', error);
process.exitCode = 1;
}Model Introduction
Mistral: Mistral Small 3
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...
This model is available through the WaveSpeed AI OpenAI-compatible API for chat completions and compatible application workflows.
Why It Looks Great
- text->text architecture for Text to Text workloads
- 32768 context window for long prompts, document analysis, and multi-turn workflows
- Structured output support for JSON responses and schema-constrained generation
Key Features
- Context Window: 32768 tokens
- Max Input: 16384 tokens
- Max Output: 16384 tokens
- Vision: Not listed
- Function Calling: Not listed
- Structured Outputs: Supported
- Image Generation: Not listed
- Audio Input: Not listed
- Supported Parameters: frequency_penalty, logit_bias, max_tokens, min_p, presence_penalty, repetition_penalty, response_format, seed, stop, structured_outputs, temperature, top_k, top_p
Specifications
| Specification | Value |
|---|---|
| Provider | mistral |
| Model Type | Chat Completions model |
| Architecture | text->text |
| Context Window | 32768 tokens |
| Max Input | 16384 tokens |
| Max Output | 16384 tokens |
| Input | Text |
| Output | Text |
| Vision | Not listed |
| Function Calling | Not listed |
| Structured Outputs | Supported |
| Release Date | January 31, 2025 |
How to Use
- Write your prompt - describe the task, provide context, and specify the 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: mistral
Info
Supported Functionality
API Access Guide
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
Context
33K
Max Output
16K
Tool Use
Supported
Try Mistral Small 24b Instruct 2501 on WaveSpeedAI
Access Mistral Small 24b Instruct 2501 through our unified API — OpenAI-compatible, no cold starts, transparent pricing.
Frequently Asked Questions about Mistral Small 24b Instruct 2501
How much does Mistral Small 24b Instruct 2501 cost via the API?+
Pricing on WaveSpeedAI: $0.05 per million input tokens and $0.08 per million output tokens. Prompt caching and batch processing are billed separately and reduce effective cost on long, repetitive workloads.
What is the context window of Mistral Small 24b Instruct 2501?+
Mistral Small 24b Instruct 2501 supports up to 33K tokens of context with up to 16K tokens of output per request.
Is Mistral Small 24b Instruct 2501 OpenAI-compatible?+
WaveSpeedAI exposes Mistral Small 24b Instruct 2501 at https://llm.wavespeed.ai/v1 through the OpenAI-compatible Chat Completions interface. Most OpenAI SDK clients work by changing the base URL and API key; optional fields depend on the selected model.
How do I get started with Mistral Small 24b Instruct 2501?+
Sign in to WaveSpeedAI, create an API key in Access Keys, then send a request to https://llm.wavespeed.ai/v1/chat/completions with the model id shown above. Check the current model catalog for availability, capabilities, and pricing.