QuarterBit AXIOM
Train 70B AI models on 1 GPU instead of 11
What it does
QuarterBit AXIOM makes large AI model training accessible to everyone. THE PROBLEM: Training a 70B parameter model needs 840GB of GPU memory — that's 11 A100 GPUs at $30+/hour. Only big tech can afford this. THE SOLUTION: AXIOM compresses training memory 15x, allowing: • 70B models on 1 GPU (was 11) • 13B models FREE on Kaggle T4 • 90% cost reduction • 91% energy reduction NOT LoRA OR ADAPTERS: 100% of parameters are trainable. Full fine-tuning, not parameter-efficient tricks.
Does the same job
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Hey folks! We're Alex and Evan, and we're working on putting together a 512 H100 compute cluster for startups and researchers to train large generative models on. - it runs at the lowest possible margins (<$2.00/hr per H100) - designed for bursty training runs, so you can take say 128 H100s for a week - you don’t need to commit to multiple years of compute or pay for a year upfront Big labs like OpenAI and Deepmind have big clusters that support this kind of bursty allocation for their researchers, but startups so far have had to get very small clusters on very long term contracts, wait…
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