Inference APIs
Models/Chat/Llama 3.3 70B Instruct
ChatTool callingJSON modeMultilingual
Context window
131K tokens
Modality
Text → Text
Input
$1.35 / 1M tokens
Output
$1.35 / 1M tokens
Time to first token
1.29 s
Output speed
67.5 tok/s
Model ID
meta-llama/Llama-3.3-70B-Instruct-Turbo

Quickstart

You need an API key to call this model. Create a free account or log in.

Set INFERENCE_API_KEY to your key from the API Keys page, then run:

curl https://api.inferenceapis.com/v1/chat/completions \
  -H "Authorization: Bearer $INFERENCE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "meta-llama/Llama-3.3-70B-Instruct-Turbo",
    "messages": [
      {"role": "system", "content": "You are a helpful assistant."},
      {"role": "user", "content": "Hello! What can you do?"}
    ]
  }'
import os
from openai import OpenAI

client = OpenAI(
    base_url="https://api.inferenceapis.com/v1",
    api_key=os.environ["INFERENCE_API_KEY"],
)
response = client.chat.completions.create(
    model="meta-llama/Llama-3.3-70B-Instruct-Turbo",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Hello! What can you do?"},
    ],
)
print(response.choices[0].message.content)
import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://api.inferenceapis.com/v1",
  apiKey: process.env.INFERENCE_API_KEY,
});
const response = await client.chat.completions.create({
  model: "meta-llama/Llama-3.3-70B-Instruct-Turbo",
  messages: [
    { role: "system", content: "You are a helpful assistant." },
    { role: "user", content: "Hello! What can you do?" },
  ],
});
console.log(response.choices[0].message.content);

Endpoint

POST https://api.inferenceapis.com/v1/chat/completions
Headers Authorization: Bearer $INFERENCE_API_KEY
Content-Type: application/json
Compatible OpenAI wire format. /openai/v1/… is accepted too, so Groq-style base URLs work with only the host changed.

Model IDs and aliases

Send any of these as model; they all resolve to this model.

IDNote
meta-llama/Llama-3.3-70B-Instruct-TurboCanonical
llama-3.3-70bAlias
llama-3.3-70b-instructAlias
llama-3.3-70b-versatileSame id as on Groq — switch by changing the base URL only
llama-3.1-8b-instantAlias
meta-llama/Llama-3.3-70B-InstructAlias

Request body

ParameterTypeDescription
model required string Model ID: meta-llama/Llama-3.3-70B-Instruct-Turbo — also accepted: llama-3.3-70b, llama-3.3-70b-instruct, llama-3.3-70b-versatile, llama-3.1-8b-instant
messages required array Conversation so far. Each item has a role (system, user or assistant) and content.
max_tokens integer Maximum number of tokens to generate.
temperature number Sampling temperature. Higher values give more varied output.
top_p number Nucleus sampling cutoff.
stream boolean Stream the response as server-sent events. The final chunk includes usage.
tools array Tool definitions for function calling (OpenAI format).
response_format object {"type": "json_object"} for JSON mode.
stop string | array Sequences where the model stops generating.
seed integer Seed for more reproducible sampling.

Response

200 OK · application/json
{
  "id": "chatcmpl-abc123",
  "object": "chat.completion",
  "model": "meta-llama/Llama-3.3-70B-Instruct-Turbo",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "Hi! I can answer questions, write and edit text, help with code and more."
      },
      "finish_reason": "stop"
    }
  ],
  "usage": { "prompt_tokens": 28, "completion_tokens": 17, "total_tokens": 45 }
}

Pricing

Input$1.35 / 1M tokens
Output$1.35 / 1M tokens
BillingPay as you go from prepaid credits. No subscription, no daily request or token cap. See all pricing.

Notes

  • Served as the Turbo (FP8) variant. Output is very close to the full-precision model; if you compare against Groq's former endpoint you may see minor wording differences.

Compare Llama 3.3 70B Instruct with…

Errors

Errors use the OpenAI envelope: {"error": {"message", "type", "code"}}. 401 missing or invalid key · 402 insufficient_balance · 404 model_not_found · 503 model_unavailable. See the error reference and provider error guides.