AINewsnow

I developed my own quantized LLM from scratch, trained on 30B tokens, deploys in 60 MB [R]

This story is from 2026-08-22. It is preserved in the archive; the latest stories are on the live feed.

I trained a 250M parameter model from scratch on 30B tokens of fineweb. It’s quantized to under 2 bits so the whole deployment is 60 MB and it needs about 80 MB of RAM to run. Runs around 400 tok/s on a normal laptop CPU, no GPU needed. How the long context works: the most recent 2048 tokens stay i…

Read the full story at r/MachineLearning ↗

Timeline · 1 report

  1. 2026-08-22 04:39 · r/MachineLearning
    I developed my own quantized LLM from scratch, trained on 30B tokens, deploys in 60 MB [R]

More stories

  1. Introducing Kimi K3 on Amazon Bedrock — AWS Machine Learning Blog
  2. Introducing Amazon SageMaker HyperPod Inference Gateway — AWS Machine Learning Blog
  3. Anthropic, OpenAI, SpaceXAI, Google sued over call to ‘pace’ AI development — Politico Technology
  4. Gemini Hacked Three Companies in First Known Breakout by Google’s AI — Wall Street Journal Technology
  5. NVIDIA CEO Jensen Huang rejects ‘AI will end the world’ claim, yet cautions ‘we should go as fast as we can but...’ — Mint AI
  6. Alibaba's Qwen3.8-Omni-Flash Cuts Video AI Costs by 89% With Agent Tool Use — AlphaSignal
  7. AI hallucination of Chinese nuclear components almost led to US military attack — Ars Technica AI
  8. The new AgentCore runtime: Elastic, optimized, and consistently fast starts — AWS Machine Learning Blog

Get the daily brief of stories like this at 6:30 every morning →