How to Use AI for Free

Everyone wants to use AI without paying for it, and there are three ways to get there: run the model yourself, use someone’s free tier, or use a tool someone is subsidising. All of them are real options, and every one has a catch worth understanding before you commit to it.

Local LLMs (llama.cpp/ollama)

This is where your own hardware becomes the datacenter.

Usually your client makes an API request to a server which runs the AI model and sends you back the response. They run it on powerful machines to process it and generate the output, and they do it fast - at the small fee you pay (in subscriptions/tokens) them for the electricity used, so they can break even the cost of the hardware, and for their profit margin.

(I use “power” a lot here. I mean how good your hardware is, not electricity.)

Local LLMs let you run that whole process by yourself, for yourself. You already do pay for your electricity and the device you’re running the model on, and don’t need to make a profit off yourself, so it’s completely free (excluding those costs said before).

“So it’s not actually free…?” The details aren’t relevant. 😊

It’s also more private. When you use someone else’s AI, your prompts go to their servers, where they may be stored. And if your conversations end up in a training set, the personal details you mentioned can resurface later in a response someone else gets from that same model.

Problem 1 (Your hardware is trash - maybe)

TLDR: Average PC a consumer has, cannot run good models.

Most of us are running consumer hardware 🤯 - budget-friendly machines designed for average use. The average person will never run an AI model on their own machine. That hardware is ok for office work, like editing a Word doc, or for gaming. Hardware with enough power for whatever the task happens to be, which is how they can keep it cheap for you. And running AI is very intensive as it’s a complex task, which isn’t feasible on our simple machines.

AI servers have to be crazy powerful. They require “enterprise hardware”, which is very expensive for the companies that need that kind of power. With sufficient power AI models run well, but don’t on less powerful hardware, like your laptop or computer.

This isn’t quite as absolute as that sounds. An average GPU can’t run AI models to any useful degree, but a genuinely good one can. Some pricier consumer cards have the raw specs for it - a gamer might have a NVIDIA RTX 5090, a worker might have a NVIDIA RTX PRO 6000 Blackwell Workstation Edition. Still not enterprise hardware, but good enough to run AI.

You can definitely run AI models on your consumer hardware, it will just be very slow, or you’d have to pick a less advanced, not as good model, which will be fast. It won’t just refuse because your specs are too bad.

Problem 2 (Expensive)

TLDR: It is expensive to buy a good PC to feasibly run good models.

This is Problem 1 again from the other direction. To buy hardware that can run AI models anywhere close to what the big companies use will be expensive, since you need so much power for big, complex models. And more power costs you more money. With less powerful hardware, you can run less good models.

It’s cheaper to buy a $20 sub or pay a few cents per ___ tokens than buy an expensive GPU + deal with the many other problems as listed.

Problem 3 (Open-source VS Big Corp Models)

TLDR: People say O-S models are not as good as cloud AI providers. (AKA You cannot run Claude locally)

Open-source models you can download and run for free; commercial models are trained by that company for millions/billions of dollars = a very good model, but to make their money back + profit, they make this model only accessible on their servers, which you have to pay per token/subscription.

There are very good open-source models, and the labs behind most of them are funded companies rather than hobbyists - DeepSeek, Alibaba’s Qwen, Moonshot’s Kimi, Zhipu’s GLM, MiniMax, and Meta’s Llama. The gap isn’t passion versus money. It’s that the labs with the most compute keep their best weights closed and release the smaller ones, so “open source” here usually means the previous generation or a model cut down to fit your hardware.

Problem 4 (You can’t run them on your phone)

TLDR: You cannot run models on your phone.

Unless you do some crazy port forwarding or tailscale/netbird/cf tunnels, or have a godly phone that can run good models, you can’t run good models on your average phone. It will be very slow.

This is inconvenient as you can’t run them on the go or when you can’t access your server running the model.

You can make API requests, no matter your hardware, so online AI companies win here.

Non-Local AI, But Local Models?

A few underground/unpopular platforms such as many-models-in-one run open source models on their servers for free - somehow. They either have very strict limits/cooldowns, or are just bleeding money.

One example that isn’t so underground is “HuggingChat”, developed by HuggingFace - the holy grail of Local AI. It hosts hundreds of open-source models you can chat with in a familiar interface. You get $0.10 worth of credits, which burns fast depending on your tasks, but it’s fun to play with without actually downloading the model and running it yourself.

Free Tiers/Trials

Many AI Cloud Providers have a free tier, that only requires you to sign up and you can use their AI, but after a set amount of tokens/messages, you must wait a day/week/month. This is inconvenient.

The shape of it is always the same. You sign up, you get a small daily or weekly quota, and when you burn through it you’re put on a cooldown until it resets. The quota is usually generous enough to be genuinely useful for an afternoon and small enough that you won’t build a habit around it. Some give you a one-off credit grant instead of a recurring allowance, which is arguably worse, because you either rush or you lose it.

Free tiers are not charity. They’re customer acquisition. You’re getting the model at a loss because the hope is that you like it enough to pay later, so the quota exists mainly to give you a taste rather than to be useful long-term. The usual catches are rate limits while you’re inside your quota, which get worse the more you lean on it, and the quiet possibility that a free tier can shrink or disappear without much warning, since it costs the provider money and nobody is obliged to keep it.

You could always make new accounts to bypass these cooldowns, but that is heavily discouraged, tedious and against most TOS.

There’s also the privacy question, which is the same one from earlier in this post. A free tier is usually the worst case, because prompts sent on a trial are the easiest kind of data to repurpose. If you’re pasting anything you’d mind seeing in a response to someone else, that applies more here than anywhere else in the article.

OpenCode (Somehow Free)

I am not sponsored nor am I developer for OpenCode. The things I say are genuinely just true and it’s somehow free and highly effective.

TLDR: OpenCode is kinda like free Claude Code, I don’t know why, but it’s amazing. Try it out.

This is the exception to everything above, and the reason I actually wrote this post. (OpenCode is a TUI like Claude Code. OpenCode Zen is a gateway like OpenRouter; it fronts many models, and a rotating handful of them are currently $0. OpenCode Go is a separate $10/month subscription to the open models. The free part you care about lives in Zen, not Go.)

OpenCode is an open source AI coding agent that is somehow entirely free.

You can BYOK and use any cloud provider, use local AI models (ollama) or use OpenCode’s own free tier, which gives you very, very generous limits. For the record, in my ~2 months of usage, I have only hit it once. I use OpenCode every day for hours at a time for coding, system management, and creating study materials.

Again, OpenCode is like Claude Code or Codex, with support for skills, plugins, AGENTS.md, subagents, etc., except it’s completely free. I have not had to open my wallet once for tokens, or to pay for a subscription.

Why I think it’s free

TLDR: Model trains off your chats.

OpenCode regularly has promotional periods where model developers and researchers need more reinforcement learning/feedback/usage of the model so they can improve it, and the costs to run the model are absorbed as testing and training costs.

They make a model -> We get to use it for free -> We give feedback & conversation history that may be shared and trained on -> They improve model -> Model is taken off OpenCode -> Model usage is commercially sold per token/sub as usual

The models are often released as “Stealth models” which means their developer and name when commercially available are hidden and given placeholders or not publicly said.

New models get on this pipeline very often, so users will always have a model to use, for free.

Conclusion

Running AI models locally is the most private, freedom-est, and ethical way to use AI, and for most people it just isn’t going to happen. Free tiers are better than nothing and worse than they look, because the limits are the point.

Which leaves the third option, the one I didn’t expect when I started writing this. Not free hardware, and not a trial that runs out, but a tool someone is subsidising on purpose, where the free part is the whole product rather than a sample of it.

None of this is stable. Providers change their terms, free tiers shrink, models get pulled off the shelf. So don’t build a plan on any of it. Build a habit instead - because the model you’ll be using next month will be different, and knowing how to tell when it’s wrong is the part that stays.

Which was always the actual point of running the model yourself. Not that it’s free. That nobody can take it away from you.