PrêtGPU TEE

Meta: Llama 3.3 70B Instruct

ID du modèlemeta-llama/llama-3.3-70b-instruct

The Meta Llama 3.3 multilingual large language model (LLM) is a pretrained and instruction tuned generative model in 70B (text in/text out). The Llama 3.3 instruction tuned text only model is optimized for multilingual dialogue use cases and outperforms many of the available open source and closed chat models on common industry benchmarks.

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entrée

$2.00/M

sortie

$2.00/M

contexte

131K

créé

28 nov. 2025

Forme d’API prise en charge

entrée

text

sortie

text

outils

Pris en charge

mode JSON

Pris en charge

Vérification

signature

ID de réponse

attestation

GPU TEE

fournisseur

Phala

Provider

Phala

GPU TEE

entrée

$2.00/M

sortie

$2.00/M

contexte

131K

$ pip install openai

1from openai import OpenAI
2import os
3
4MODEL = "meta-llama/llama-3.3-70b-instruct"
5
6client = OpenAI(
7    base_url="https://api.redpill.ai/v1",
8    api_key=os.environ["REDPILL_API_KEY"],
9)
10
11response = client.chat.completions.create(
12    model=MODEL,
13    messages=[{"role": "user", "content": "Run this privately."}],
14)
15
16print(response.id)
17print(response.choices[0].message.content)

$ npm install openai

1import OpenAI from "openai"
2
3const MODEL = "meta-llama/llama-3.3-70b-instruct"
4
5const openai = new OpenAI({
6  baseURL: "https://api.redpill.ai/v1",
7  apiKey: process.env.REDPILL_API_KEY,
8})
9
10const response = await openai.chat.completions.create({
11  model: MODEL,
12  messages: [{ role: "user", content: "Run this privately." }],
13})
14
15console.log(response.id)
16console.log(response.choices[0].message.content)

1curl https://api.redpill.ai/v1/chat/completions \
2  -H "Authorization: Bearer $REDPILL_API_KEY" \
3  -H "Content-Type: application/json" \
4  -d '{
5    "model": "meta-llama/llama-3.3-70b-instruct",
6    "messages": [
7      { "role": "user", "content": "Run this privately." }
8    ]
9  }'

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