import requests r = requests.post( "https://api.aimlapi.com/v1/chat/completions", headers={"Authorization": "Bearer " + AIMLAPI_KEY}, json={ "model": "mistralai/mistral-medium-3.1", "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/mistral-medium-3.1", "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/mistral-medium-3.1","messages":[{"role":"user","content":"Hello!"}]}'
OpenAI-compatible — swap the base URL and it works with your existing SDK.
| Type | Price |
|---|---|
| Input | |
| Output | |
| Cached input |
| Benchmark | Score | What it measures | Source | Retrieved |
|---|---|---|---|---|
| MMLU-Pro | 74.4% | Multi-discipline knowledge + reasoning (harder MMLU) | Source | July 12, 2026 |
| Intelligence | 9.9 | Composite score across standardised reasoning, knowledge and problem-solving evaluations, measured independently by Artificial Analysis | Source | September 12, 2026 |
| Coding | 20.5 | Composite score across standardised coding evaluations, measured independently by Artificial Analysis | Source | September 12, 2026 |
| Math | 38.3 | Composite score across standardised mathematics evaluations, measured independently by Artificial Analysis | Source | September 12, 2026 |
| Model | Input | Output | Context | Best for |
|---|---|---|---|---|
Medium 3.1 This page | Reasoning + agents | |||
| Reasoning + agents | ||||
| Balanced coding + agents | ||||
| Long-context, multimodal & agentic workflows | ||||
| Reasoning + agents |
Medium 3.1 has a 131,072 tokens context window.
Medium 3.1 takes image, text as input and returns text.
Use mistralai/mistral-medium-3.1 as the model id. Requests go to https://api.aimlapi.com/v1/chat/completions.
Medium 3.1 is priced at input $0.55016 / 1M tokens, output $2.7508 / 1M tokens, cached input $0.055016 / 1M tokens.
Yes, Medium 3.1 can stream responses as they are generated.
Yes, Medium 3.1 accepts image input alongside text.
Medium 3.1 was built by Mistral AI.
Yes, it includes reasoning as one of its listed capabilities.
Yes, it supports function calling and parallel tool calls.