mistral-small-24b-instruct-2501
Mistral Small 3 is a 24B-parameter model optimized for low-latency performance on common AI tasks, released under the Apache 2.0 license in both pre-trained and instruction-tuned versions.
Precio: Entrada: 12 créditos / 1 M de tokens (≈ $0.06); salida: 19.2 créditos / 1 M de tokens (≈ $0.10).
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Mistral Small 3 API on ModelFold
Mistral Small 3 is a 24B-parameter model optimized for low-latency performance on common AI tasks, released under the Apache 2.0 license in both pre-trained and instruction-tuned versions. Try Mistral Small 3 in the ModelFold Playground, then call it from your own code through an OpenAI-compatible chat completions API.
What Is the Mistral Small 3 API
Mistral Small 3 at a glance
Mistral Small 3 is a chat model from Mistral AI. It accepts text as input and returns text, with a context window of up to 33K tokens.
Use it without hosting anything
On ModelFold you call Mistral Small 3 with a single API key — no model weights to download and no inference servers to run. The same key also works for the other chat, image, video and audio models on ModelFold.
Core Capabilities of Mistral Small 3
Up to 33K tokens of context
Keep long conversations, large documents and sizeable code in a single request, so the model can reason over the full material instead of fragments.
Structured outputs
Ask for JSON that follows a schema (response_format), which makes extraction, classification and system integrations more reliable.
How to Use Mistral Small 3 on ModelFold
- 1
Step 1: Try it in the Playground
Open the Playground at the top of this page, type a prompt and see how Mistral Small 3 responds before writing any code.
- 2
Step 2: Create an API key
Sign in to ModelFold and create an API key in the console. Keep it secret and send it as a Bearer token.
- 3
Step 3: Send a request
Call POST https://modelfold.ai/v1/chat/completions with "model": "mistral-small-24b-instruct-2501" and your messages. Existing OpenAI-compatible SDKs work by changing the base URL and key.
- ✓
Step 4: Ship and monitor
Integrate the response into your product and check token usage and spend for every call in the console logs.
What You Can Build with Mistral Small 3
Low-latency experiences
Power chat interfaces, autocomplete and interactive tools where users expect fast responses.
High-volume pipelines
Run classification, extraction, rewriting and batch jobs at scale where cost per request matters.
Writing and content
Draft, edit and translate articles, emails, product copy and documentation in a consistent tone.
Frequently Asked Questions
What is Mistral Small 3?⌄
Mistral Small 3 is a 24B-parameter model optimized for low-latency performance on common AI tasks, released under the Apache 2.0 license in both pre-trained and instruction-tuned versions.
Which inputs does Mistral Small 3 support?⌄
Mistral Small 3 accepts text and returns text. Through ModelFold you send text messages; documents attached in the Playground are converted to text.
How long is the context window of Mistral Small 3?⌄
Up to 33K tokens, shared between your input and the model’s output.
Does Mistral Small 3 support function calling?⌄
Function calling is not listed for Mistral Small 3; requests that include tools will be rejected. Use plain prompts or JSON output instead.
How is Mistral Small 3 billed on ModelFold?⌄
Pay as you go by tokens: input and output tokens are charged at the per-million-token prices shown on this page. There is no monthly fee, and failed requests are not charged.
How do I call Mistral Small 3 through the API?⌄
Send a POST request to https://modelfold.ai/v1/chat/completions with "model": "mistral-small-24b-instruct-2501", using your ModelFold API key as the Bearer token.
| Entrada | 12 créditos 1M tokens≈ $0.06 |
| Salida | 19.2 créditos 1M tokens≈ $0.10 |
Se cobra por token, con tarifas separadas para entrada y salida. Los tokens de razonamiento cuentan como salida. El entorno de pruebas aplica exactamente el mismo cálculo.
Leer la documentación de la API →AI Agents · Claude Code / Cursor / Trae →curl https://modelfold.ai/v1/chat/completions \
-H "Authorization: Bearer $MODELFOLD_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"mistral-small-24b-instruct-2501","messages":[{"role":"user","content":"Hello"}]}'