Precision over scale
Every model we ship is purpose-built for a specific task — not a general-purpose blob that tries to do everything mediocrely. Specialization wins.
open source · community built · free forever
Big intelligence. Tinyfootprint.
We build small, fast, production-ready models that punch above their weight.
No bloat. No nonsense. Runs on your laptop — not just someone's A100 cluster.
// what we do
Machine learning
for everyone.
Most AI labs race to make models bigger. We race to make them smaller without losing what matters.
Free-tier first
Everything is trained and tested on Google Colab T4 GPUs. If it doesn't run there, it doesn't ship. Your hardware shouldn't be a barrier to good AI.
Truly open
No paywalls. No gated weights. No "available upon request." Every model, dataset, and training notebook is public, forkable, and yours to build on.
Low carbon, high impact
Smaller models mean less compute, less energy, less waste. Good ML shouldn't require a power plant. We take that seriously.
// efficiency over parameters
The AI industry measures
progress in billions.
We measure it in milliseconds.
Big models
Cost per inference$$$ expensive
Latency500ms – 2s
DeploymentNeeds A100 / H100
Accessible toWell-funded labs
Carbon footprintVery high
VS
TinyModels ⚡
Cost per inferenceFree / near-free
Latency20 – 80ms
DeploymentT4, CPU, phone
Accessible toEveryone
Carbon footprintLow
// philosophy
Three rules.
No exceptions.
Every model we release must clear all three bars. No partial credit.
Fits on a free GPU
If it doesn't run on a Colab T4, it doesn't ship. Deployable by anyone means deployable by everyone — students, indie devs, researchers with no budget.
Beats models twice its size
Size is not an excuse for quality. Every TinyModel must outperform or match models with significantly higher parameter counts on its target benchmark. Efficiency is the craft.
Ships with clean docs
A model nobody can use is worthless. Every release comes with a complete model card, working code examples, and honest evaluation numbers — no cherry-picked benchmarks.
// a word (or two)
Jokes and a
serious note.
// joke #1
GPT-4 walks into a bar. The bartender says: "We don't serve models with 1.8 trillion parameters here." GPT-4 says: "That's fine, I'll just hallucinate a better bar."
// joke #2
A researcher asks a 70B model and a 141M model the same question. The 70B takes 4 seconds. The 141M answers in 22ms and says: "Same thing, shorter."
The democratization of AI is not a marketing phrase — it is an obligation. When the tools to build intelligent systems are locked behind compute budgets that only large organizations can afford, the people who could benefit most from this technology are exactly the ones who cannot access it.
TinyModels exists because we believe that making something smaller and faster is not a compromise — it is a discipline. Every parameter saved, every millisecond cut, every megabyte reduced is a deliberate act of engineering that makes this technology more portable, more sustainable, and more inclusive.
We will keep building that way.
Open to everyone.
Forever.
Follow the org, contribute models, datasets, or ideas — all are welcome.