{"schema_version":"onlylabs.public_signal.v1","title":"Mistral AI Model: mistralai/Timestral-123M","description":"Mistral AI model signal with public source context, captured evidence pages, related signals, and data-business radar classification.","url":"https://onlylabs.fyi/signals/67d75ba8-2c14-4170-93ac-5d2fac6aed86","json_url":"https://onlylabs.fyi/signals/67d75ba8-2c14-4170-93ac-5d2fac6aed86/signal.json","generated_at":"2026-10-24T20:20:23.965Z","evidence_latest_fetched_at":"2026-10-16T07:20:25.132579+00:00","signal_first_seen_at":"2026-10-16T07:20:08.229239+00:00","org":{"slug":"mistral","name":"Mistral AI","category":"frontier-lab","category_label":"Frontier lab","dossier_url":"https://onlylabs.fyi/labs/mistral","dossier_json_url":"https://onlylabs.fyi/labs/mistral/dossier.json"},"related_urls":{"signal":"https://onlylabs.fyi/signals/67d75ba8-2c14-4170-93ac-5d2fac6aed86","signal_json":"https://onlylabs.fyi/signals/67d75ba8-2c14-4170-93ac-5d2fac6aed86/signal.json","source":"https://huggingface.co/mistralai/Timestral-123M","lab_dossier":"https://onlylabs.fyi/labs/mistral","lab_dossier_json":"https://onlylabs.fyi/labs/mistral/dossier.json","analysis":"https://onlylabs.fyi/analysis/mistral","analysis_json":"https://onlylabs.fyi/analysis/mistral/analysis.json","analysis_evidence_json":"https://onlylabs.fyi/analysis/mistral/evidence.json","category":"https://onlylabs.fyi/frontier","category_json":"https://onlylabs.fyi/frontier.json","category_feed":"https://onlylabs.fyi/frontier/feed.xml","category_signals_json":"https://onlylabs.fyi/signals.json","topic":"https://onlylabs.fyi/topics/releases","topic_signals_json":"https://onlylabs.fyi/topics/releases/signals.json","topic_feed":"https://onlylabs.fyi/topics/releases/feed.xml","data_business":null},"answer_pack":{"answer":"Mistral AI published mistralai/Timestral-123M. 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This repository contains the 123M checkpoint. >[!Note] > For more information about our Timestral family, go to the main model page: [Timestral-209M](https://huggingface.co/mistralai/Timestral-209M). Model Details - **Size:** 123M parameters. - **Architecture:** patch-based transformer with time attention and variate attention, 20 layers, embedding dimension 640. - **Patching:** 32 time steps per patch. Each patch is embedded from its values together with their missing-value indicators. - **Context length:** up to 32,768 time steps (1,024 patches). - **Forecast horizon**: Up to 1,024 time steps (32 patches) in a single forward pass. 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