A New 34B Open Source LLM, Astonishing 78 Score in MMLU (GPT-4 MMLU:83)
In plain words
This open source large language model contains 34 billion parameters and achieves a score of 78 on the MMLU benchmark. It is designed for developers and researchers who need access to a capable language model without proprietary restrictions. The model is available on GitHub for those looking to work with or fine-tune a mid-sized open alternative to larger commercial systems.
written from the facts on this page · September 2026
Does the same job
all alternatives →- IBI built a tiny LLM to demystify how language models workApr 2026 · github.com · ▲915
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.

- WMWe made glhf.chat – run almost any open-source LLM, including 405B2024 · glhf.chat · ▲161
Try it out! https://glhf.chat/ 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…



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