import requests r = requests.post( "https://api.aimlapi.com/v1/chat/completions", headers={"Authorization": "Bearer " + AIMLAPI_KEY}, json={ "model": "sao10k/l3.1-euryale-70b", "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": "sao10k/l3.1-euryale-70b", "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":"sao10k/l3.1-euryale-70b","messages":[{"role":"user","content":"Hello!"}]}'
OpenAI-compatible — swap the base URL and it works with your existing SDK.
| Type | Price |
|---|---|
| Input | |
| Output | |
| Model | Input | Output | Context | Best for |
|---|---|---|---|---|
Llama 3.1 Euryale 70B v2.2 This page | Reasoning + agents | |||
| Reasoning + agents | ||||
| Balanced coding + agents | ||||
| Long-context, multimodal & agentic workflows | ||||
| Reasoning + agents |
Llama 3.1 Euryale 70B v2.2 has a 131,072 tokens context window and can return up to 16,384 tokens.
Llama 3.1 Euryale 70B v2.2 takes image, text as input and returns text.
Use sao10k/l3.1-euryale-70b as the model id. Requests go to https://api.aimlapi.com/v1/chat/completions.
Llama 3.1 Euryale 70B v2.2 is priced at input $1.9948802 / 1M tokens, output $1.9948802 / 1M tokens.
Yes, Llama 3.1 Euryale 70B v2.2 can stream responses as they are generated.
Yes, Llama 3.1 Euryale 70B v2.2 accepts image input alongside text.
Yes, it supports function calling, tool use, parallel tool calls, and structured outputs.
Yes, web search is listed as one of its supported features.