753B-parameter open-weights scientific-discovery model from DeepPrinciple, post-trained from GLM 5.3.
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Hydrogen 1.0 is a scientific-discovery language model from DeepPrinciple. According to YouTube creator coverage, it has about 753B parameters and is built on GLM 5.3, then further trained on scientific literature, lab records and full research trajectories, including failed attempts.
Creators report that it scores 38.33% on the Frontier Science benchmark at roughly $0.25 per problem, compared with $0.88 for GPT-6 Astra, and that it sometimes beats Astra on science benchmarks. A demo reportedly had it write code to simulate a polyethylene melt in 3D. These figures come from creator statements and have not been verified against official pages.
Weights are reported to be on Hugging Face in full-precision, FP4 (about 464 GB) and MX variants, and an API is also said to be available. A 753B-parameter model needs substantial multi-GPU hardware for self-hosting. The license, official URLs and exact release date could not be confirmed.
Watch the moment: the exact second top creators show it. Videos load only when you press play, via youtube-nocookie.com.
753B-parameter open scientific model based on GLM 5.3, further trained on literature, lab records and full research trajectories including failures. Released in full, FP4 (~464 GB) and MX versions; sometimes beats GPT-6 Astra on science benchmarks.
A scientific-discovery model post-trained from GLM 5.3. It scores 38.33% on Frontier Science at $0.25 per problem versus $0.88 for Astra, and the demo wrote code to simulate a polyethylene melt in 3D. Weights are on Hugging Face and an API is available.
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