{"schema_version":"onlylabs.public_signal.v1","title":"Cerebras Model: cerebras/Cerebras-GPT-590M","description":"Cerebras model signal with public source context, captured evidence pages, related signals, and category-scoped analysis context.","url":"https://onlylabs.fyi/signals/5a567908-45a7-402d-bd31-919efc5ca956","json_url":"https://onlylabs.fyi/signals/5a567908-45a7-402d-bd31-919efc5ca956/signal.json","generated_at":"2026-07-26T20:40:37.715Z","evidence_latest_fetched_at":"2026-07-18T07:20:20.78904+00:00","signal_first_seen_at":"2026-07-18T07:20:07.762789+00:00","org":{"slug":"cerebras","name":"Cerebras","category":"neocloud","category_label":"Neocloud","dossier_url":"https://onlylabs.fyi/labs/cerebras","dossier_json_url":"https://onlylabs.fyi/labs/cerebras/dossier.json"},"related_urls":{"signal":"https://onlylabs.fyi/signals/5a567908-45a7-402d-bd31-919efc5ca956","signal_json":"https://onlylabs.fyi/signals/5a567908-45a7-402d-bd31-919efc5ca956/signal.json","source":"https://huggingface.co/cerebras/Cerebras-GPT-590M","lab_dossier":"https://onlylabs.fyi/labs/cerebras","lab_dossier_json":"https://onlylabs.fyi/labs/cerebras/dossier.json","analysis":"https://onlylabs.fyi/analysis/cerebras","analysis_json":"https://onlylabs.fyi/analysis/cerebras/analysis.json","analysis_evidence_json":"https://onlylabs.fyi/analysis/cerebras/evidence.json","category":"https://onlylabs.fyi/neoclouds","category_json":"https://onlylabs.fyi/neoclouds.json","category_feed":"https://onlylabs.fyi/neoclouds/feed.xml","category_signals_json":"https://onlylabs.fyi/signals.json?category=neocloud","topic":"https://onlylabs.fyi/topics/releases","topic_signals_json":"https://onlylabs.fyi/topics/releases/signals.json?category=neocloud","topic_feed":"https://onlylabs.fyi/topics/releases/feed.xml?category=neocloud","data_business":null},"answer_pack":{"answer":"Cerebras published cerebras/Cerebras-GPT-590M. 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Model Description The Cerebras-GPT family is released to facilitate research into LLM scaling laws using open architectures and data sets and demonstrate the simplicity of and scalability of training LLMs on the Cerebras software and hardware stack. All Cerebras-GPT models are available on Hugging Face. The family includes 111M, 256M, 590M, 1.3B, 2.7B, 6.7B, and 13B models. All models in the Cerebras-GPT family have been trained in accordance with [Chinchilla scaling laws](https://arxiv.org/abs/2203.15556) (20 tokens per model parameter) which is compute-optimal. These models were trained on the [Andromeda](https://www.cerebras.net/andromeda/) AI supercomputer comprised of 16 CS-2 wafer scale systems. Cerebras' [weight streaming technology](https://www.cerebras.net/blog/linear-scaling-made-possible-with-weight-streaming) simplifies the training of LLMs by disaggregating compute from model storage. 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