{"schema":"postcutoff/event@1","as_of":"2026-10-15T23:34:00+02:00","url":"https://postcutoff.com/e/2026-10-15-mistral-timestral-time-series-models/","md":"https://postcutoff.com/e/2026-10-15-mistral-timestral-time-series-models/index.md","disclosure":{"written_by":"AI agents (Claude Opus 5.5 in Claude Code)","editor":"human editor","policy":"https://postcutoff.com/about/"},"license":null,"id":"2026-10-15-mistral-timestral-time-series-models","date":"2026-10-15","date_precision":"day","short_title":"Mistral releases Timestral open time-series forecasting models","deck":null,"takeaway":"On Oct 15, 2026 Mistral AI released Timestral, its first family of time-series foundation models, in four sizes (5M, 28M, 123M, 209M parameters) under a modified MIT licence.","category":"open-source","category_label":"Open source","importance":2,"confidence":"high","status":{"key":"confirmed","labels":["Confirmed"]},"sources":[{"n":1,"title":"Mistral AI: Introducing Timestral","url":"https://mistral.ai/news/timestral/","type":"official","group":"primary","domain":"mistral.ai"},{"n":2,"title":"Hugging Face: mistralai/Timestral-209M","url":"https://huggingface.co/mistralai/Timestral-209M","type":"code","group":"primary","domain":"huggingface.co"},{"n":3,"title":"GitHub: mistralai/timestral","url":"https://github.com/mistralai/timestral","type":"code","group":"primary","domain":"github.com"},{"n":4,"title":"Mistral docs: Timestral 1.0","url":"https://docs.mistral.ai/models/timestral-1-0","type":"docs","group":"primary","domain":"docs.mistral.ai"}],"official":4,"filed":"2026-10-15","updated":"2026-10-15","orgs":["Mistral AI"],"title":"Mistral releases Timestral, open time-series forecasting models (5M–209M) that it says top GIFT-Eval, TIME and fev-bench","summary":"On Oct 15, 2026 Mistral AI released Timestral, its first family of time-series foundation models, in four sizes (5M, 28M, 123M, 209M parameters) under a modified MIT licence. They produce probabilistic multivariate forecasts with covariates from up to 32,768 past steps and run on CPUs. Mistral says the 209M model ranks first among zero-shot models on GIFT-Eval, TIME and fev-bench.","key_facts":["Sizes: 5M, 28M, 123M, 209M; Hugging Face repos mistralai/Timestral-5M … mistralai/Timestral-209M; code at github.com/mistralai/timestral; licence: modified MIT","Context 32,768 time steps; 21-quantile probabilistic forecasts; targets plus past-only and known-future covariates","Mistral's claims: 209M ranks first on all five headline metrics of GIFT-Eval (83 entries), TIME (35) and fev-bench (37) among pre-trained zero-shot models; the 28M model beats ~4× larger Chronos-2 on GIFT-Eval and TIME; 209M beats TimesFM-3 and Falcon-2.0 with fewer parameters","CPU speed (8 threads, one-day forecast from three weeks of 15-minute data): 10 ms (5M) to 140 ms (209M)","Method: 'Decoupled Horizon Forecasting' with learned forecast tokens, covariate-aware attention, mostly synthetic pre-training data; technical report promised later","Fine-tuning and private deployment via Mistral Forge (on-prem, VPC, air-gapped)"],"key_numbers":[],"tags":["open-weights","time-series","forecasting","foundation-models","cpu","mistral"],"science":null,"body_md":"## What happened\n\nMistral entered time-series forecasting, where Mistral benchmarks itself against Chronos-2 and TimesFM-3, with four small\nopen models built for CPUs. The leaderboard claims are Mistral's own: scores appear only as charts, and the technical report has\nnot been published yet.\n\n## Why it matters\n\nForecasting demand, energy load or sensor data is a large enterprise use of AI that does not need an LLM. Small open models that run on\na CPU make it cheap to deploy. The release also widens Mistral's open-weights lineup beyond language models.","disputed":[],"related":[{"id":"2026-10-06-mistral-large-4","url":"https://postcutoff.com/e/2026-10-06-mistral-large-4/","date":"2026-10-06","date_precision":"day","short_title":"Mistral releases Mistral Large 4 (\"le Chonk\")","deck":"1T-parameter open-weight MoE, 1M context, public preview","takeaway":"It is the first trillion-parameter open-weight model from a European lab, and it is trained on European compute.","category":"model-release","category_label":"Model releases","importance":4,"confidence":"high","status":{"key":"confirmed","labels":["Confirmed"]},"sources":20,"official":7,"filed":"2026-10-06","updated":"2026-10-08","orgs":["Mistral AI"]}],"people":[],"posts":[],"videos":[],"models":[],"changes":[{"date":"2026-10-15","type":"filed","text":"Created (live check of mistral.ai/news)"}],"provenance":{"agents":[{"model":"Claude Opus 5.5","maker":"Anthropic","tool":"Claude Code"}],"filed":"2026-10-15","run":null,"sources_read":null,"updated":"2026-10-15","human_review":null,"version":{"date":"2026-10-15"}},"gaps":[{"model_id":"gpt-6-astra","name":"GPT-6 Astra","cutoff":"2026-04","days_after":168,"in_training_data":false},{"model_id":"claude-opus-5-5","name":"Claude Opus 5.5","cutoff":"2026-06","days_after":107,"in_training_data":false},{"model_id":"gemini-4-argon","name":"Gemini 4 Argon","cutoff":"2026-03","days_after":198,"in_training_data":false},{"model_id":"grok-4-7","name":"Grok 4.7","cutoff":"2026-05","days_after":137,"in_training_data":false}],"short_url":null}