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GPU Poor LLM Arena
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Compact LLM Battle Arena: Frugal AI Face-Off!
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OpenAI has released BrowseComp an open source benchmark designed to evaluate the web browsing capabilities of AI agents. This dataset comprising 1,266 questions challenges AI models to navigate the web and uncover complex and obscure information. Crafted by human trainers, the questions are intentionally difficult. (unsolvable by another person in under ten minutes and beyond the reach of existing models like ChatGPT with and without browsing and an early version of OpenAI's Deep Research tool.)
Blog Post: https://openai.com/index/browsecomp/
Paper: https://cdn.openai.com/pdf/5e10f4ab-d6f7-442e-9508-59515c65e35d/browsecomp.pdf
Code in simple eval repo: https://github.com/openai/simple-evals
Blog Post: https://openai.com/index/browsecomp/
Paper: https://cdn.openai.com/pdf/5e10f4ab-d6f7-442e-9508-59515c65e35d/browsecomp.pdf
Code in simple eval repo: https://github.com/openai/simple-evals
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qwen3-30b-a3b Research
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qwen3-30b-a3b-research + Real Time Deep Research
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Qwen 3 Fine tuning >> MoE. Update the experiment thread to include config and script for fine-tuning the Qwen3-30B-A3B model.
The goal is to make a low latency non-thinking model for a daily driver coding, so 3 billion parameters active should be perfect.
βοΈ training running
βοΈ evals running
βοΈ improve dataset
The moe isn't going to fit into colab's A100 even with quantization (π @UnslothAI ). So I've been working on HF spaces' H100s for this. Everything is available in the tread and I'll share more tomorrow.
burtenshaw/Qwen3-Code-Lite#1
The goal is to make a low latency non-thinking model for a daily driver coding, so 3 billion parameters active should be perfect.
βοΈ training running
βοΈ evals running
βοΈ improve dataset
The moe isn't going to fit into colab's A100 even with quantization (π @UnslothAI ). So I've been working on HF spaces' H100s for this. Everything is available in the tread and I'll share more tomorrow.
burtenshaw/Qwen3-Code-Lite#1
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