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Llama 3.1 70B — free API, OpenAI-compatible, through InferAll

How to call Meta Llama 3.1 70B through InferAll's OpenAI-compatible endpoint. Hosted on NVIDIA NIM, $0 within the free tier. New accounts get 25 free calls before any payment; the $5 activation pack unlocks ongoing use.

InferAll Team

4 min read
Llama 3.1Meta AIfree LLM APINVIDIA NIMOpenAI APIopen sourcedeveloper tools

Meta's Llama 3.1 70B (meta/llama-3.1-70b-instruct) is the open-weight workhorse most developers reach for first — strong general reasoning, instruction-following, and coding, at a size you can actually run in production. Through InferAll it's $0 within the free tier via NVIDIA NIM, and it works with the OpenAI SDK you already have.

from openai import OpenAI

client = OpenAI(
    base_url="https://api.inferall.ai/v1",
    api_key="ifu_your_key_here",  # get one at inferall.ai/keys (no card needed to start)
)

response = client.chat.completions.create(
    model="meta/llama-3.1-70b-instruct",
    messages=[{"role": "user", "content": "Explain the CAP theorem to a backend engineer."}],
    max_tokens=512,
)

print(response.choices[0].message.content)

That's the whole integration. The only change from calling OpenAI directly is the base_url — your existing code, LangChain chains, and LlamaIndex retrievers all work unchanged.


TypeScript

import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://api.inferall.ai/v1",
  apiKey: process.env.INFERALL_API_KEY,
});

const response = await client.chat.completions.create({
  model: "meta/llama-3.1-70b-instruct",
  messages: [{ role: "user", content: "Write a TypeScript debounce function." }],
  max_tokens: 400,
});

console.log(response.choices[0].message.content);

Why Llama 3.1 70B

It's the dependable default. 70B parameters is the sweet spot where a model is genuinely capable across reasoning, summarization, classification, and code — without the latency and cost of frontier models. For the majority of prototyping and production tasks, Llama 3.1 70B is enough.

It's $0 within the free allowance on NVIDIA NIM. NVIDIA hosts it on their DGX Cloud infrastructure via NIM (NVIDIA Inference Microservices), which InferAll exposes at $0. There's no inference cost to pass through, so it stays free within the free-plan daily request caps (50 chat / 100 text per day). New accounts get 25 free NIM calls before any payment, so no card is needed to try it. The $5 Activation pack unlocks ongoing use and becomes spendable balance for paid providers if you ever call one.

It's OpenAI-compatible. You get standard chat.completion responses, streaming, tool use, and JSON mode — all working with whatever OpenAI client you already have. Switching from gpt-4o-mini to meta/llama-3.1-70b-instruct is a one-line model-string change.


Already on 3.1? Llama 3.3 70B is the newer drop-in

If you want the most refined model in the line, Meta Llama 3.3 70B (meta/llama-3.3-70b-instruct) is the newer iteration — more instruction-following polish and stronger benchmarks at the same 70B size, and it's free on the same NVIDIA NIM tier. It's a drop-in: change meta/llama-3.1-70b-instruct to meta/llama-3.3-70b-instruct and nothing else. Many teams start on 3.1 (the widely-known release) and move to 3.3 once they realize it's the same price for a better model.

Both are free. Pick whichever you like — or compare them side by side on the same prompt.


Compare against other free models

Llama 3.1 70B isn't the only free model on the tier. The same ifu_ key also calls Llama 3.1 8B (faster), Mixtral 8x7B (mixture-of-experts), and NVIDIA Nemotron 120B (larger, for harder prompts) — all $0. Run one prompt across all of them to pick the right model for your task:

for model in [
    "meta/llama-3.1-70b-instruct",
    "meta/llama-3.3-70b-instruct",
    "mistralai/mistral-medium-3.5-128b",
    "nvidia/nemotron-3-super-120b-a12b",
]:
    resp = client.chat.completions.create(
        model=model,
        messages=[{"role": "user", "content": "Summarize REST vs gRPC in two sentences."}],
        max_tokens=200,
    )
    print(f"\n=== {model} ===\n{resp.choices[0].message.content}")

The full, current free roster is always one call away — curl https://api.inferall.ai/ai/v1/models — so you never hardcode a list that goes stale.


One key, every model

The same ifu_... key that calls free Llama 3.1 70B also routes to GPT-4.1, Claude Opus 4, and Gemini 2.5 — so when a task needs a frontier model, you switch the model string instead of juggling provider credentials. Free open models for the bulk of the work, premium providers when you need them, one bill.

Trial: a free run to evaluate before activation. Get your key at inferall.ai/keys; the $5 activation pack (more on /billing) unlocks ongoing free-NIM access at $0 input / $0 output.