{"schema_version":"onlylabs.public_signal.v1","title":"Snowflake (Arctic) Model: Snowflake/Llama-3.1-Arctic-ExCoT-70B","description":"Snowflake (Arctic) model signal with public source context, captured evidence pages, related signals, and category-scoped analysis context.","url":"https://onlylabs.fyi/signals/f7dcf972-db5e-480a-b863-c57e7fea3fa7","json_url":"https://onlylabs.fyi/signals/f7dcf972-db5e-480a-b863-c57e7fea3fa7/signal.json","generated_at":"2026-06-11T02:50:44.706288+00:00","org":{"slug":"snowflake","name":"Snowflake (Arctic)","category":"neocloud","category_label":"Neocloud","dossier_url":"https://onlylabs.fyi/labs/snowflake","dossier_json_url":"https://onlylabs.fyi/labs/snowflake/dossier.json"},"related_urls":{"signal":"https://onlylabs.fyi/signals/f7dcf972-db5e-480a-b863-c57e7fea3fa7","signal_json":"https://onlylabs.fyi/signals/f7dcf972-db5e-480a-b863-c57e7fea3fa7/signal.json","source":"https://huggingface.co/Snowflake/Llama-3.1-Arctic-ExCoT-70B","lab_dossier":"https://onlylabs.fyi/labs/snowflake","lab_dossier_json":"https://onlylabs.fyi/labs/snowflake/dossier.json","analysis":"https://onlylabs.fyi/analysis/snowflake","analysis_json":"https://onlylabs.fyi/analysis/snowflake/analysis.json","analysis_evidence_json":"https://onlylabs.fyi/analysis/snowflake/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":"Snowflake (Arctic) published Snowflake/Llama-3.1-Arctic-ExCoT-70B. This model signal is evidence of what shipped on model infrastructure and how the release is positioned. High-signal details: license cc-by-nc-4.0 · 13 HF downloads · Notable 70B model, but very low traction (14 downloads).. onlylabs links this event to 1 captured evidence page and 6 related model signals.","signal_desk":"releases","source_context":{"source_url":"https://huggingface.co/Snowflake/Llama-3.1-Arctic-ExCoT-70B","source_host":"huggingface.co","occurred_at":"2025-03-25T00:29:06+00:00","first_seen_at":"2026-06-06T01:49:59.400935+00:00","date_source":"source","context":null},"context_markers":[{"label":"Lab","value":"Snowflake (Arctic)","source":"signal"},{"label":"Signal desk","value":"releases","source":"signal"},{"label":"Source host","value":"huggingface.co","source":"source"},{"label":"License","value":"cc-by-nc-4.0","source":"model"},{"label":"Params","value":"70.6B","source":"model"},{"label":"Downloads","value":"13","source":"traction"},{"label":"Likes","value":"10","source":"traction"},{"label":"Notability","value":"Notable 70B model, but very low traction (14 downloads).","source":"signal"},{"label":"Watch term","value":"Eval methodology","source":"evidence"},{"label":"Watch term","value":"Model card","source":"model"},{"label":"Watch term","value":"Data pipeline","source":"evidence"},{"label":"Watch term","value":"Infrastructure","source":"evidence"}],"evidence_coverage":{"target_pages":1,"captured_pages":1,"readable_pages":1,"capture_methods":["plain"],"missing_page_urls":[],"failed_page_urls":[],"blocked_page_urls":[],"page_urls":["https://huggingface.co/Snowflake/Llama-3.1-Arctic-ExCoT-70B/raw/main/README.md"],"related_signals":6,"has_source_url":true,"latest_page_fetched_at":"2026-06-11T02:50:44.706288+00:00"},"data_business":{"matches":false,"lanes":[],"matched_terms":[],"score":null,"reason":null},"agent_handoff":{"signal_json":"https://onlylabs.fyi/signals/f7dcf972-db5e-480a-b863-c57e7fea3fa7/signal.json","dossier_json":"https://onlylabs.fyi/labs/snowflake/dossier.json","analysis_json":"https://onlylabs.fyi/analysis/snowflake/analysis.json","analysis_evidence_json":"https://onlylabs.fyi/analysis/snowflake/evidence.json","topic_signals_json":"https://onlylabs.fyi/topics/releases/signals.json?category=neocloud","topic_feed":"https://onlylabs.fyi/topics/releases/feed.xml?category=neocloud","category_signals_json":"https://onlylabs.fyi/signals.json?category=neocloud","data_radar_json":null,"opportunities_json":null},"analysis_playbook":{"objective":"Turn model cards, repository releases, and launch artifacts into a current view of what shipped and what changed.","evidence_focus":["model card","release note","version or tag","pipeline tag","license","downloads, likes, stars, and linked papers"],"extraction_questions":["What actually shipped, and through which public artifact?","Which releases include inspectable model, repo, paper, or package evidence?","Which launches create new eval, data, infra, or deployment needs?","Which shipped signals are missing captured page context?"],"signal_questions":["What shipped in this model artifact, and what evidence describes its capability, license, or traction?","What actually shipped, and through which public artifact?","Which releases include inspectable model, repo, paper, or package evidence?","Do the 6 related model signals show a repeated pattern?"],"output_fields":["org","release_type","artifact","traction","evidence_url"],"data_business_relevance":"Data-business lane extraction is scoped to frontier labs; 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ExCoT is a novel framework that combines CoT prompting with SQL execution-based DPO, using execution results — not human preferences — as the feedback signal. This enables scalable, high-quality model optimization without requiring expensive human annotations. Based on our internal testing, ExCoT delivered state-of-the-art results on the [BIRD-test benchmark](https://bird-bench.github.io/), achieving best-in-class performance in the single-model, single-inference category using only public datasets (BIRD and Spider) and no additional Text2SQL data: * [Llama-3.1-Arctic-ExCoT-70B](https://huggingface.co/Snowflake/Llama-3.1-Arctic-ExCoT-70B) improved execution accuracy on the BIRD-dev set from the base model’s 57.37% to 68.51%. [Qwen-2.5-coder-Arctic-ExCoT-32B](https://huggingface.co/Snowflake/Qwen-2.5-coder-Arctic-ExCoT-32B) achieved similarly strong gains. * Both models significantly outperformed other well-known frontier general-purpose models, achieving over 10 points of improvement. For more..."},"evidence_pages":[{"url":"https://huggingface.co/Snowflake/Llama-3.1-Arctic-ExCoT-70B/raw/main/README.md","final_url":"https://huggingface.co/Snowflake/Llama-3.1-Arctic-ExCoT-70B/raw/main/README.md","title":"Snowflake/Llama-3.1-Arctic-ExCoT-70B model card","http_status":200,"content_type":"text/plain; charset=utf-8","capture_method":"plain","fetched_at":"2026-06-11T02:50:44.706288+00:00","bytes":2885,"raw_path":"0e7cfafc15302d8e76723954b51798f58d24bfd3dc34ad20c123c9b410edf3d6.md","content_hash":"15c5c065ff606633a1ef6b69d529bc715a9ad37fb3982a613e2bf710bff21a26","excerpt_chars":1200,"truncated":true,"excerpt":"--- license: cc-by-nc-4.0 base_model: - meta-llama/Llama-3.1-70B --- Arctic Text2SQL: ExCoT Snowflake’s AI research team introduces ExCoT, the first model in the Arctic Text2SQL family. ExCoT is a novel framework that combines CoT prompting with SQL execution-based DPO, using execution results — not human preferences — as the feedback signal. This enables scalable, high-quality model optimization without requiring expensive human annotations. Based on our internal testing, ExCoT delivered state-of-the-art results on the [BIRD-test benchmark](https://bird-bench.github.io/), achieving best-in-class performance in the single-model, single-inference category using only public datasets (BIRD and Spider) and no additional Text2SQL data: * [Llama-3.1-Arctic-ExCoT-70B](https://huggingface.co/Snowflake/Llama-3.1-Arctic-ExCoT-70B) improved execution accuracy on the BIRD-dev set from the base model’s 57.37% to 68.51%. [Qwen-2.5-coder-Arctic-ExCoT-32B](https://huggingface.co/Snowflake/Qwen-2.5-coder-Arctic-ExCoT-32B) achieved similarly strong gains. * Both models significantly outperformed other well-known frontier general-purpose models, achieving over 10 points of improvement. 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