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

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. ```python 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 (card on file required to activate) ) 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 ```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 100k-token monthly allowance. A verified card on file is required to activate — the $5 [Activation pack](/billing) 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](/blog/llama-3-3-70b-free-api) (`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](/docs) 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: ```python for model in [ "meta/llama-3.1-70b-instruct", "meta/llama-3.3-70b-instruct", "mistralai/mixtral-8x7b-instruct-v0.1", "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: 200 requests to evaluate before activation. Get your key at [inferall.ai/keys](https://inferall.ai/keys); the $5 activation pack ([more on /billing](/billing)) unlocks the full 100k-token monthly free-NIM allowance.