Name: Devstral 2 2512 API
Brand: Mistral AI

Overview

What is Devstral 2 2512 API?

Devstral 2 2512 is available through AIMLAPI.

Technical Specifications
- Supported inputs: Text
- Output: Text
- Context window: 262,144 tokens / Max output: —
- Endpoint: /chat/completions

Performance Benchmarks
[embed]

Devstral 2 2512 API Pricing
- Input: $0.572 / 1M tokens
- Output: $2.86 / 1M tokens

Where to Use Devstral 2 2512

Coding and code review
Generate, debug, and review code across languages, reading whole files or repos in a single prompt.

Agentic and multi-step workflows
Reliable tool-calling and instruction-following suit agent loops that plan, call tools, and iterate.

Complex reasoning
Extended reasoning improves reliability on multi-step math, logic, and technical analysis.

Long-document analysis
Summarize and extract from contracts, papers, and reports without aggressive chunking.

Code Sample
[embed]

Uptime and performance

Uptime (7d): 100%

Measured on the AI/ML API gateway across live traffic. Figures are medians unless stated. Last updated 2026-10-12.

Use cases

Software engineering tasks: the model is documented as a frontier code agents model for solving software engineering tasks, with emphasis on using tools to explore codebases, edit multiple files, and power software engineering agents.

Document question answering: the documentation lists Document QnA as a stated use case for the model.

AI code assistants: the model is described as suitable for AI code assistants, alongside agentic coding and software engineering tasks.

Agentic coding and tool-calling workflows: it is documented as excelling at using tools to explore codebases and as supporting agentic, instruction-based SWE tasks.

How to use Devstral 2 2512 API

Install any OpenAI-compatible SDK, point it at api.aimlapi.com/v1, and set the model to mistralai/devstral-2512.

import requests

r = requests.post(
    "https://api.aimlapi.com/v1/chat/completions",
    headers={"Authorization": "Bearer " + AIMLAPI_KEY},
    json={
      "model": "mistralai/devstral-2512",
      "messages": [
        {
          "role": "user",
          "content": "Hello!"
        }
      ]
    },
)
print(r.json())

const r = await fetch("https://api.aimlapi.com/v1/chat/completions", {
  method: "POST",
  headers: {
    Authorization: `Bearer ${process.env.AIMLAPI_KEY}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    "model": "mistralai/devstral-2512",
    "messages": [
      {
        "role": "user",
        "content": "Hello!"
      }
    ]
  }),
});
console.log(await r.json());

curl -X POST https://api.aimlapi.com/v1/chat/completions \
  -H "Authorization: Bearer $AIMLAPI_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"mistralai/devstral-2512","messages":[{"role":"user","content":"Hello!"}]}'

OpenAI-compatible — swap the base URL and it works with your existing SDK.