Start Building With LLMs for Free: 100,000 Tokens/Month on Open Models via One API

The fastest way to kill a side project is to hit a paywall on line one. You want to prototype a feature, test a prompt, or wire up an agent — and before you can print a single token you are staring at a billing page. The friction is real enough that a lot of good ideas never get past "I'll try it this weekend." So here is a concrete on-ramp: **100,000 tokens per month, at $0, on 110+ open-source models** — using the same OpenAI or Anthropic SDK you already have installed. This post is a practical, code-forward walkthrough of how to get building today, what the free tier actually covers, and where the honest line is. ### What the free tier actually is InferAll's free tier gives you **100,000 tokens/month** on **110+ open-source models** hosted on **NVIDIA NIM**. That includes well-known families like **Llama 3.1 (70B / 8B), Mixtral, Nemotron, and CodeLlama** — the workhorses most developers reach for when prototyping chat, classification, summarization, and code tasks. One honest detail up front, because it matters: **you can start with no credit card.** Create a key and call free open models right away — you are charged **$0** within the free tier. A card is needed only if you later choose a paid provider or want to continue past the free trial, so there is a payment method already attached when you do. No card wall just to try it. Everything runs through a single key (it starts with `ifu_`) and two drop-in endpoints: - An **OpenAI-compatible** endpoint at `https://api.inferall.ai/v1` - An **Anthropic-compatible** endpoint at `https://api.inferall.ai/v1/messages` You do not learn a new client library. You take the SDK you already use, point it at the gateway, and pass a free model ID. ### Free model IDs you can use right now These three route to NVIDIA NIM open models and are good defaults to start with: - `meta/llama-3.1-70b-instruct` — strong general-purpose instruct model - `meta/llama-3.1-8b-instruct` — smaller and snappier for high-volume, simple turns - `mistralai/mixtral-8x7b-instruct-v0.1` — a solid mixture-of-experts option The full, current list is available from the API itself — no need to trust a hardcoded table in a blog post that may drift: ```bash curl https://api.inferall.ai/ai/v1/models \ -H "Authorization: Bearer ifu_..." ``` ### (a) The OpenAI Python SDK, pointed at the gateway, on a free model Here is a complete, runnable call. You keep `openai`, keep `client.chat.completions.create`, and change exactly two arguments — the key and the base URL — plus a free model string: ```python from openai import OpenAI client = OpenAI( api_key="ifu_...", # your InferAll key base_url="https://api.inferall.ai/v1", # the gateway, not api.openai.com ) resp = client.chat.completions.create( model="meta/llama-3.1-70b-instruct", # a free open model on NVIDIA NIM messages=[ {"role": "user", "content": "Explain backpropagation to a new grad in three sentences."} ], ) print(resp.choices[0].message.content) ``` That is a working call to an open model, counted against your free 100,000 tokens, using the exact request and response shapes the OpenAI SDK already expects. No new dependency, no provider-specific client. ### (b) The same thing with curl If you are not in Python — or you just want to confirm your key works before writing any code — hit the OpenAI-compatible endpoint directly: ```bash curl https://api.inferall.ai/v1/chat/completions \ -H "Authorization: Bearer ifu_..." \ -H "Content-Type: application/json" \ -d '{ "model": "meta/llama-3.1-8b-instruct", "messages": [ { "role": "user", "content": "Write a haiku about cold start latency." } ] }' ``` Same endpoint, same JSON shape you would send to OpenAI — the only differences are the host and the key. Swap `meta/llama-3.1-8b-instruct` for `mistralai/mixtral-8x7b-instruct-v0.1` and you are testing a different model with a one-word change. ### (c) When you outgrow free: change one string The point of starting on the free tier is that nothing is throwaway. The moment you need more capability than an open model offers — a genuinely hard task, a long-context job, a quality bar a prototype model misses — you reach for a premium provider by changing the **model string**. Same client, same key, same code: ```python resp = client.chat.completions.create( model="gpt-4o", # premium provider — this is paid usage messages=[ {"role": "user", "content": "Explain backpropagation to a new grad in three sentences."} ], ) ``` Be clear-eyed about what that line does: it crosses from the free open-model tier into **paid** premium usage. The trade is straightforward and worth stating plainly — premium providers (OpenAI, Anthropic, Google) are **pay-as-you-go at their published token price with zero markup**, on the same `ifu_` key and a single invoice. The gateway is a convenience layer, not a tax. You pay the provider's price; you just do not manage four sets of credentials to do it. (Grab the exact premium model IDs from `GET /ai/v1/models`.) ### The pattern that makes free go further Because every model — free or premium — lives behind the same interface, you can route by task instead of by vendor. Send the chatty, high-volume, low-stakes turns to a free open model: classification, retries, first-pass summarization, draft generation, the inner loop of an agent. Reserve a premium model only for the requests that actually need the extra capability. In practice that looks like a single function with a model string chosen per call: ```python def complete(prompt, hard=False): model = "gpt-4o" if hard else "meta/llama-3.1-70b-instruct" resp = client.chat.completions.create( model=model, messages=[{"role": "user", "content": prompt}], ) return resp.choices[0].message.content ``` The cheap path stays free as long as it fits your 100,000-token allowance. The expensive path is one boolean away when you need it. No second SDK, no second key, no architectural commitment to either side. ### Get started You can have a free key and a working call in a couple of minutes: 1. Create an InferAll key (prefix `ifu_`) — no card needed to start. You're charged $0 within the free tier; add a card only for paid providers or to continue past the free trial. 2. Point your existing OpenAI SDK at `https://api.inferall.ai/v1`, or Anthropic-format requests at `https://api.inferall.ai/v1/messages`. 3. Pass a free model ID like `meta/llama-3.1-70b-instruct` and ship your prototype against your real 100,000-token allowance. Start free on open models, and switch to premium with a single string only when your project earns it. Create a free key at [api.inferall.ai](https://api.inferall.ai) and run the example above.