{"schema_version":"onlylabs.public_signal.v1","title":"Arcee AI Repo: arcee-ai/trinity-large-tech-report","description":"Arcee AI repo signal with public source context, captured evidence pages, related signals, and category-scoped analysis context.","url":"https://onlylabs.fyi/signals/8e750f42-1a87-42cd-a42a-bcb1acb363a5","json_url":"https://onlylabs.fyi/signals/8e750f42-1a87-42cd-a42a-bcb1acb363a5/signal.json","generated_at":"2026-06-11T02:53:16.483891+00:00","org":{"slug":"arcee","name":"Arcee AI","category":"neolab","category_label":"Neolab","dossier_url":"https://onlylabs.fyi/labs/arcee","dossier_json_url":"https://onlylabs.fyi/labs/arcee/dossier.json"},"related_urls":{"signal":"https://onlylabs.fyi/signals/8e750f42-1a87-42cd-a42a-bcb1acb363a5","signal_json":"https://onlylabs.fyi/signals/8e750f42-1a87-42cd-a42a-bcb1acb363a5/signal.json","source":"https://github.com/arcee-ai/trinity-large-tech-report","lab_dossier":"https://onlylabs.fyi/labs/arcee","lab_dossier_json":"https://onlylabs.fyi/labs/arcee/dossier.json","analysis":"https://onlylabs.fyi/analysis/arcee","analysis_json":"https://onlylabs.fyi/analysis/arcee/analysis.json","analysis_evidence_json":"https://onlylabs.fyi/analysis/arcee/evidence.json","category":"https://onlylabs.fyi/neolabs","category_json":"https://onlylabs.fyi/neolabs.json","category_feed":"https://onlylabs.fyi/neolabs/feed.xml","category_signals_json":"https://onlylabs.fyi/signals.json?category=neolab","topic":null,"topic_signals_json":null,"topic_feed":null,"data_business":null},"answer_pack":{"answer":"Arcee AI published arcee-ai/trinity-large-tech-report. This repository signal exposes tooling, eval, infrastructure, or model-adjacent work before it may appear in a launch post. High-signal details: repo arcee-ai/trinity-large-tech-report · Tech report with moderate traction. onlylabs links this event to 1 captured evidence page and 6 related repo signals.","signal_desk":"repos","source_context":{"source_url":"https://github.com/arcee-ai/trinity-large-tech-report","source_host":"github.com","occurred_at":"2026-01-27T20:08:46+00:00","first_seen_at":"2026-06-05T22:32:26.032324+00:00","date_source":"source","context":null},"context_markers":[{"label":"Lab","value":"Arcee AI","source":"signal"},{"label":"Signal desk","value":"repos","source":"signal"},{"label":"Source host","value":"github.com","source":"source"},{"label":"Repository","value":"arcee-ai/trinity-large-tech-report","source":"source"},{"label":"Stars","value":"124","source":"traction"},{"label":"Notability","value":"Tech report with moderate traction","source":"signal"},{"label":"Watch term","value":"Model card","source":"model"},{"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://github.com/arcee-ai/trinity-large-tech-report"],"related_signals":6,"has_source_url":true,"latest_page_fetched_at":"2026-06-11T02:53:16.483891+00:00"},"data_business":{"matches":false,"lanes":[],"matched_terms":[],"score":null,"reason":null},"agent_handoff":{"signal_json":"https://onlylabs.fyi/signals/8e750f42-1a87-42cd-a42a-bcb1acb363a5/signal.json","dossier_json":"https://onlylabs.fyi/labs/arcee/dossier.json","analysis_json":"https://onlylabs.fyi/analysis/arcee/analysis.json","analysis_evidence_json":"https://onlylabs.fyi/analysis/arcee/evidence.json","topic_signals_json":null,"topic_feed":null,"category_signals_json":"https://onlylabs.fyi/signals.json?category=neolab","data_radar_json":null,"opportunities_json":null},"analysis_playbook":{"objective":"Turn new repository signals into early evidence of tooling, eval, infrastructure, model-adjacent, or product work before it appears in polished launch channels.","evidence_focus":["repo name","owner","description","language","stars","source URL","first seen time","data, eval, infra, safety, and product terms"],"extraction_questions":["What technical area does this repository expose?","Does the repo imply eval, data, infrastructure, agent, or deployment work?","Is the repo new evidence for a lab direction that is not yet in writing or releases?","Which related signals should an analyst inspect next?"],"signal_questions":["What does this new repository reveal before a formal announcement exists?","What technical area does this repository expose?","Does the repo imply eval, data, infrastructure, agent, or deployment work?","Do the 6 related repo signals show a repeated pattern?"],"output_fields":["org","repo","technical_theme","evidence_url"],"data_business_relevance":"Data-business lane extraction is scoped to frontier labs; for this category, interpret the repository as source-grounded category strategy evidence.","required_sources":[{"label":"signal_json","url":"https://onlylabs.fyi/signals/8e750f42-1a87-42cd-a42a-bcb1acb363a5/signal.json","required":true},{"label":"source","url":"https://github.com/arcee-ai/trinity-large-tech-report","required":true},{"label":"dossier_json","url":"https://onlylabs.fyi/labs/arcee/dossier.json","required":true},{"label":"analysis_evidence_json","url":"https://onlylabs.fyi/analysis/arcee/evidence.json","required":true},{"label":"topic_signals_json","url":null,"required":false},{"label":"data_radar_json","url":null,"required":false}],"expected_output":["one-paragraph source-grounded interpretation","category-specific implication","confidence and missing evidence","recommended next source to inspect"],"prompt_seed":"Using only the linked onlylabs JSON, captured source context, and cited evidence, analyze Arcee AI's repo signal \"arcee-ai/trinity-large-tech-report\" for neolab strategy."},"semantic_triples":[{"subject":"Arcee AI","predicate":"published repo","object":"arcee-ai/trinity-large-tech-report","text":"Arcee AI published repo arcee-ai/trinity-large-tech-report."},{"subject":"arcee-ai/trinity-large-tech-report","predicate":"is classified as","object":"repo signal","text":"arcee-ai/trinity-large-tech-report is classified as repo signal."},{"subject":"arcee-ai/trinity-large-tech-report","predicate":"belongs to","object":"repos desk","text":"arcee-ai/trinity-large-tech-report belongs to repos desk."},{"subject":"arcee-ai/trinity-large-tech-report","predicate":"has evidence coverage","object":"1 captured evidence page","text":"arcee-ai/trinity-large-tech-report has evidence coverage 1 captured evidence page."},{"subject":"arcee-ai/trinity-large-tech-report","predicate":"has captured page count","object":"1","text":"arcee-ai/trinity-large-tech-report has captured page count 1."},{"subject":"arcee-ai/trinity-large-tech-report","predicate":"has readable page count","object":"1","text":"arcee-ai/trinity-large-tech-report has readable page count 1."},{"subject":"arcee-ai/trinity-large-tech-report","predicate":"has related signal count","object":"6","text":"arcee-ai/trinity-large-tech-report has related signal count 6."},{"subject":"arcee-ai/trinity-large-tech-report","predicate":"has analysis playbook objective","object":"Turn new repository signals into early evidence of tooling, eval, infrastructure, model-adjacent, or product work before it appears in polished launch channels.","text":"arcee-ai/trinity-large-tech-report has analysis playbook objective Turn new repository signals into early evidence of tooling, eval, infrastructure, model-adjacent, or product work before it appears in polished launch channels.."},{"subject":"arcee-ai/trinity-large-tech-report","predicate":"has source host","object":"github.com","text":"arcee-ai/trinity-large-tech-report has source host github.com."},{"subject":"arcee-ai/trinity-large-tech-report","predicate":"has lab","object":"Arcee AI","text":"arcee-ai/trinity-large-tech-report has lab Arcee AI."},{"subject":"arcee-ai/trinity-large-tech-report","predicate":"has signal desk","object":"repos","text":"arcee-ai/trinity-large-tech-report has signal desk repos."},{"subject":"arcee-ai/trinity-large-tech-report","predicate":"has source host","object":"github.com","text":"arcee-ai/trinity-large-tech-report has source host github.com."},{"subject":"arcee-ai/trinity-large-tech-report","predicate":"has repository","object":"arcee-ai/trinity-large-tech-report","text":"arcee-ai/trinity-large-tech-report has repository arcee-ai/trinity-large-tech-report."},{"subject":"arcee-ai/trinity-large-tech-report","predicate":"has stars","object":"124","text":"arcee-ai/trinity-large-tech-report has stars 124."},{"subject":"arcee-ai/trinity-large-tech-report","predicate":"has notability","object":"Tech report with moderate traction","text":"arcee-ai/trinity-large-tech-report has notability Tech report with moderate traction."},{"subject":"arcee-ai/trinity-large-tech-report","predicate":"has watch term","object":"Model card","text":"arcee-ai/trinity-large-tech-report has watch term Model card."},{"subject":"arcee-ai/trinity-large-tech-report","predicate":"has watch term","object":"Infrastructure","text":"arcee-ai/trinity-large-tech-report has watch term Infrastructure."}]},"intelligence":{"signal_desk":"repos","answer":"Arcee AI published arcee-ai/trinity-large-tech-report. This repository signal exposes tooling, eval, infrastructure, or model-adjacent work before it may appear in a launch post. High-signal details: repo arcee-ai/trinity-large-tech-report · Tech report with moderate traction. onlylabs links this event to 1 captured evidence page and 6 related repo signals.","semantic_triples":[{"subject":"Arcee AI","predicate":"published repo","object":"arcee-ai/trinity-large-tech-report","text":"Arcee AI published repo arcee-ai/trinity-large-tech-report."},{"subject":"arcee-ai/trinity-large-tech-report","predicate":"is classified as","object":"repo signal","text":"arcee-ai/trinity-large-tech-report is classified as repo signal."},{"subject":"arcee-ai/trinity-large-tech-report","predicate":"belongs to","object":"repos desk","text":"arcee-ai/trinity-large-tech-report belongs to repos desk."},{"subject":"arcee-ai/trinity-large-tech-report","predicate":"has evidence coverage","object":"1 captured evidence page","text":"arcee-ai/trinity-large-tech-report has evidence coverage 1 captured evidence page."}]},"signal":{"id":"8e750f42-1a87-42cd-a42a-bcb1acb363a5","url":"https://onlylabs.fyi/signals/8e750f42-1a87-42cd-a42a-bcb1acb363a5","json_url":"https://onlylabs.fyi/signals/8e750f42-1a87-42cd-a42a-bcb1acb363a5/signal.json","source_url":"https://github.com/arcee-ai/trinity-large-tech-report","title":"arcee-ai/trinity-large-tech-report","summary":"Arcee AI published a new repository. onlylabs watches repos for tooling, eval, infra, and model-adjacent work.","context":null,"kind":{"key":"repo_new","label":"Repo"},"org":{"slug":"arcee","name":"Arcee AI","category":"neolab"},"occurred_at":"2026-01-27T20:08:46+00:00","first_seen_at":"2026-06-05T22:32:26.032324+00:00","date_source":"source","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://github.com/arcee-ai/trinity-large-tech-report"]},"facets":{"repo":"arcee-ai/trinity-large-tech-report"},"traction":{"github_stars":124,"hn_points":null,"hn_comments":null,"hn_story_id":null,"hf_downloads":null,"hf_likes":null},"data_radar":null},"primary_evidence_page":{"url":"https://github.com/arcee-ai/trinity-large-tech-report","final_url":"https://github.com/arcee-ai/trinity-large-tech-report","title":"arcee-ai/trinity-large-tech-report repository metadata","http_status":200,"content_type":"application/json","capture_method":"plain","fetched_at":"2026-06-11T02:53:16.483891+00:00","bytes":9127,"raw_path":"d2ce011aa007a8b1f286a3deb502a9203f8ed7439afcef132309240dddbc07be.json","content_hash":"d722cd3a846e8a85aee5b87076ac8fbc03488b7ec819329eba97e48e60abbc2f","excerpt_chars":1200,"truncated":true,"excerpt":"arcee-ai/trinity-large-tech-report Stars: 124 Forks: 5 Open issues: 0 Created: 2026-01-27T20:08:46Z Pushed: 2026-02-19T02:01:44Z Default branch: main Fork: no Archived: no README: Arcee Trinity Large - Technical Report <img width=\"1472\" height=\"828\" alt=\"trinity\" src=\"https://github.com/user-attachments/assets/ffca3a5f-e8cc-48a8-863d-ec2760ffaf5e\" /> <br><br> We present the technical report for Arcee Trinity Large, a sparse Mixture-of-Experts model with 400B total parameters and 13B activated per token. Additionally, we report on Trinity Nano and Trinity Mini, with Trinity Nano having 6B total parameters with 1B activated per token, Trinity Mini having 26B total parameters with 3B activated per token. The models’ modern architecture includes interleaved local and global attention, gated attention, depth-scaled sandwich norm, and sigmoid routing for Mixture-of-Experts. For Trinity Large, we also introduce a new MoE load balancing strategy titled Soft-clamped Momentum Expert Bias Updates (SMEBU). We train the models using the Muon optimizer. All three models completed training with zero loss spikes. Trinity Nano and Trinity Mini were pre-trained on 10 trillion tokens, and Trinity..."},"evidence_pages":[{"url":"https://github.com/arcee-ai/trinity-large-tech-report","final_url":"https://github.com/arcee-ai/trinity-large-tech-report","title":"arcee-ai/trinity-large-tech-report repository metadata","http_status":200,"content_type":"application/json","capture_method":"plain","fetched_at":"2026-06-11T02:53:16.483891+00:00","bytes":9127,"raw_path":"d2ce011aa007a8b1f286a3deb502a9203f8ed7439afcef132309240dddbc07be.json","content_hash":"d722cd3a846e8a85aee5b87076ac8fbc03488b7ec819329eba97e48e60abbc2f","excerpt_chars":1200,"truncated":true,"excerpt":"arcee-ai/trinity-large-tech-report Stars: 124 Forks: 5 Open issues: 0 Created: 2026-01-27T20:08:46Z Pushed: 2026-02-19T02:01:44Z Default branch: main Fork: no Archived: no README: Arcee Trinity Large - Technical Report <img width=\"1472\" height=\"828\" alt=\"trinity\" src=\"https://github.com/user-attachments/assets/ffca3a5f-e8cc-48a8-863d-ec2760ffaf5e\" /> <br><br> We present the technical report for Arcee Trinity Large, a sparse Mixture-of-Experts model with 400B total parameters and 13B activated per token. Additionally, we report on Trinity Nano and Trinity Mini, with Trinity Nano having 6B total parameters with 1B activated per token, Trinity Mini having 26B total parameters with 3B activated per token. The models’ modern architecture includes interleaved local and global attention, gated attention, depth-scaled sandwich norm, and sigmoid routing for Mixture-of-Experts. For Trinity Large, we also introduce a new MoE load balancing strategy titled Soft-clamped Momentum Expert Bias Updates (SMEBU). We train the models using the Muon optimizer. All three models completed training with zero loss spikes. Trinity Nano and Trinity Mini were pre-trained on 10 trillion tokens, and Trinity..."}],"related_signals":[{"id":"6f498857-818f-43d8-904c-d7bfd27e8812","url":"https://onlylabs.fyi/signals/6f498857-818f-43d8-904c-d7bfd27e8812","source_url":"https://github.com/arcee-ai/pybubble","title":"arcee-ai/pybubble","context":"Python","kind":{"key":"repo_new","label":"Repo"},"org":{"slug":"arcee","name":"Arcee AI","category":"neolab"},"occurred_at":"2025-11-16T04:37:22+00:00","first_seen_at":"2026-06-05T22:32:26.032324+00:00","date_source":"source"},{"id":"826f1087-1cc4-4dc9-903a-4a76f26d92ed","url":"https://onlylabs.fyi/signals/826f1087-1cc4-4dc9-903a-4a76f26d92ed","source_url":"https://github.com/arcee-ai/NeMo-RL","title":"arcee-ai/NeMo-RL","context":"Python","kind":{"key":"repo_new","label":"Repo"},"org":{"slug":"arcee","name":"Arcee AI","category":"neolab"},"occurred_at":"2025-08-14T00:08:13+00:00","first_seen_at":"2026-06-05T22:32:26.032324+00:00","date_source":"source"},{"id":"69136e4e-afb2-4e3f-8562-c6385d01b2bf","url":"https://onlylabs.fyi/signals/69136e4e-afb2-4e3f-8562-c6385d01b2bf","source_url":"https://github.com/arcee-ai/anymcp","title":"arcee-ai/anymcp","context":"Python","kind":{"key":"repo_new","label":"Repo"},"org":{"slug":"arcee","name":"Arcee AI","category":"neolab"},"occurred_at":"2025-05-06T09:20:06+00:00","first_seen_at":"2026-06-05T22:32:26.032324+00:00","date_source":"source"},{"id":"c38ed25b-17d4-44a9-88ab-c4093e1197be","url":"https://onlylabs.fyi/signals/c38ed25b-17d4-44a9-88ab-c4093e1197be","source_url":"https://github.com/arcee-ai/wipro-pump-demo","title":"arcee-ai/wipro-pump-demo","context":"Python","kind":{"key":"repo_new","label":"Repo"},"org":{"slug":"arcee","name":"Arcee AI","category":"neolab"},"occurred_at":"2025-04-24T19:05:03+00:00","first_seen_at":"2026-06-05T22:32:26.032324+00:00","date_source":"source"},{"id":"fc91b138-d32e-46c7-8054-eb93385cd631","url":"https://onlylabs.fyi/signals/fc91b138-d32e-46c7-8054-eb93385cd631","source_url":"https://github.com/arcee-ai/KidRails","title":"arcee-ai/KidRails","context":"Python","kind":{"key":"repo_new","label":"Repo"},"org":{"slug":"arcee","name":"Arcee AI","category":"neolab"},"occurred_at":"2025-02-11T16:28:50+00:00","first_seen_at":"2026-06-05T22:32:26.032324+00:00","date_source":"source"},{"id":"0a9518f7-9084-4dc3-883f-559b4d0922e8","url":"https://onlylabs.fyi/signals/0a9518f7-9084-4dc3-883f-559b4d0922e8","source_url":"https://github.com/arcee-ai/in-context-learning","title":"arcee-ai/in-context-learning","context":"Python","kind":{"key":"repo_new","label":"Repo"},"org":{"slug":"arcee","name":"Arcee AI","category":"neolab"},"occurred_at":"2024-11-25T17:27:10+00:00","first_seen_at":"2026-06-05T22:32:26.032324+00:00","date_source":"source"}]}