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Alternatives

Products that do what Z80-μLM, a 'Conversational AI' That Fits in 40KB does

How small can a language model be while still doing something useful? I wanted to find out, and had some spare time over the holidays. Z80-μLM is a character-level language model with 2-bit quantized weights ({-2,-1,0,+1}) that runs on a Z80 with 64KB RAM. The entire thing: inference, weights, chat UI, it all fits in a 40KB .COM file that you can run in a CP/M emulator and hopefully even real hardware! It won't write your emails, but it can be trained to play a stripped down version of 20 Questions, and is sometimes able to maintain the illusion of having simple but terse conversations…

  1. 1IB

    Built a ~9M param LLM from scratch to understand how they actually work. Vanilla transformer, 60K synthetic conversations, ~130 lines of PyTorch. Trains in 5 min on a free Colab T4. The fish thinks the meaning of life is food. Fork it and swap the personality for your own character.

    Apr 2026 · github.com

  2. 2EL
  3. 3GG

    A few days ago I found myself trying out GLM 5.2 and was really positively impressed. The capabilities and security I was getting from this LLM are similar to those I've gotten from models like Claude or GPT, and this really surprised me. But then I thought, "I wonder how it would work on a normal computer like mine," and above all, "I wonder if it would work without going into OOM on a computer like mine." So I started working with the help of agents to test this possibility. I started converting the model to int4, understanding MTP usage, and if possible implementing DSA for long context.…

    Jul 2026 · github.com

  4. 4
    GLM-5.3254

    Coding leap from scaled post-training on the same base

    22d ago · z.ai

  5. 5
    Ztalk.ai450

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  6. 6RA
  7. 7

    Powering the next-gen of smart, trusted voice agents

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  8. 8

    Multilingual speech AI model trained on 12.5M hours of data

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  9. 9

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    Mar 2026

  10. 10
    GLM-4.5298

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    2025

  11. 11KT

    Kitten TTS is an open-source series of tiny and expressive text-to-speech models for on-device applications. We are excited to launch a preview of our smallest model, which is less than 25 MB. This model has 15M parameters. This release supports English text-to-speech applications in eight voices: four male and four female. The model is quantized to int8 + fp16, and it uses onnx for runtime. The model is designed to run literally anywhere eg. raspberry pi, low-end smartphones, wearables, browsers etc. No GPU required! We're releasing this to give early users a sense of the latency and voices…

    2025 · github.com

  12. 12

    Building the next generation of conversational AI

    2023

  13. 13
    Grok 4.1367

    A new standard in conversational AI

    Nov 2025

  14. 14TN

    Kitten TTS (https:&#x2F;&#x2F;github.com&#x2F;KittenML&#x2F;KittenTTS) is an open-source series of tiny and expressive text-to-speech models for on-device applications. We had a thread last year here: https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=44807868. Today we're releasing three new models with 80M, 40M and 14M parameters. The largest model (80M) has the highest quality. The 14M variant reaches new SOTA in expressivity among similar sized models, despite being <25MB in size. This release is a major upgrade from the previous one and supports English text-to-speech applications in…

    Mar 2026 · github.com

  15. 15

    First TTS model to support all 22 Indic languages + English

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  16. 16DA
  17. 17
    Qwen3.5307

    The 397B native multimodal agent with 17B active params

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  18. 18IR

    The Emotion Engine has 32 MB of RAM total, so the trick is streaming weights from CD-ROM one matrix at a time during the forward pass — only activations, KV cache and embeddings live in RAM. This means models bigger than the RAM can still run, they just read more from disc. Had to build a custom quantized format (PSNT), hack endianness, write a tokenizer pipeline, and most of the PS2 SDK from scratch (releasing that separately). The model itself is also custom — a 10M param Llama-style architecture I trained specifically for this. And it works. On real hardware.

    Mar 2026 · github.com

  19. 19WM

    Try it out! https:&#x2F;&#x2F;glhf.chat&#x2F; Hey HN! We’ve been working for the past few months on a website to let you easily run (almost) any open-source LLM on autoscaling GPU clusters. It’s free for now while we figure out how to price it, but we expect to be cheaper than most GPU offerings since we can run the models multi-tenant. Unlike Together AI, Fireworks, etc, we’ll run any model that the open-source vLLM project supports: we don’t have a hardcoded list. If you want a specific model or finetune, you don’t have to ask us for it: you can just paste the Hugging Face link in and…

    2024 · glhf.chat

  20. 20
    GLM-5154

    Open-weights model for long-horizon agentic engineering

    Feb 2026

  21. 21

    Al conversations on demand on any topic

    2025

  22. 22

    Vision-to-code foundation model for real GUI automation

    Apr 2026 · docs.z.ai

  23. 23

    High-speed agentic model built specifically for OpenClaw

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  24. 24
    GPT-4.5511

    The largest and best model for chat yet in GPT family

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