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Llama 3.3 70B Instruct: free via FreeLLMAPI

Llama 3.3 70B Instruct: served free by 1 provider, up to 8K context. Provider limits, quotas and setup examples on FreeLLMAPI.

Inferbase

meta-llama-3-3-70b-instruct
Context window8K tokens
Free budget5,000 requests/month; 100 requests and $0.50 usage/day shared tokens/mo
Rate limitsnot published
Shared monthly and daily free allowance info
Inferbase Free needs no card. The shared account allowance is 5,000 requests/month, also capped at 100 managed requests and $0.50 of model usage/day. Free managed chat permits 8,192 input and 1,024 output tokens per request. Counts are shared, not per-model grants. Model IDs including FP8 and Turbo variants are explicit; a changed response identity fails rather than silently substituting another model. Update FreeLLMAPI to a build with the Inferbase adapter. See https://inferbase.ai/pricing.

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Use it

FreeLLMAPI is a self-hosted router you run yourself. Install it, paste in your free Inferbase key, and meta-llama-3-3-70b-instruct answers on an OpenAI-compatible endpoint at http://localhost:3001/v1. No credit card, no hosted middleman: your prompts and your provider keys never leave your machine.

Install the router (macOS, Linux, WSL)
curl -fsSL https://freellmapi.co/install.sh | bash
Install the router (Windows PowerShell)
iwr -useb https://freellmapi.co/install.ps1 | iex
Call meta-llama-3-3-70b-instruct with curl
curl http://localhost:3001/v1/chat/completions \
  -H "Authorization: Bearer freellmapi-your-unified-key" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "meta-llama-3-3-70b-instruct",
    "messages": [{"role": "user", "content": "Say hi in five words."}]
  }'
The same request in Python (openai)
from openai import OpenAI

client = OpenAI(
    base_url="http://localhost:3001/v1",
    api_key="freellmapi-your-unified-key",
)

resp = client.chat.completions.create(
    model="meta-llama-3-3-70b-instruct",
    messages=[{"role": "user", "content": "Say hi in five words."}],
)
print(resp.choices[0].message.content)

The router answers on /v1/chat/completions and every other OpenAI surface, plus the Anthropic Messages API, so existing clients need only a new base_url. Swap the model id for auto and the router picks the best free model that is still under its limits. Full reference: docs/api.md.