# Cohere c4ai-command-a-03-2025 Projects at AI Tinkerers

> Canonical HTML: https://aitinkerers.org/technologies/cohere-c4ai-command-a-03-2025
> Markdown URL: https://aitinkerers.org/technologies/cohere-c4ai-command-a-03-2025.md
> Technology record last updated: 2026-06-07T23:44:07Z
> Generated: 2026-09-21T02:40:18Z

Cohere's 111-billion-parameter open-weights model built for high-throughput enterprise tasks, advanced tool use, and multilingual operations across 23 languages.

Developed by Cohere and Cohere For AI, Command A is a 111-billion-parameter open-weights model designed to deliver maximum performance with minimal hardware overhead (deployable on just two GPUs). It features a massive 256,000-token context length and delivers a 150% throughput boost over its predecessor, Command R+ 08-2024. Optimized for business-critical workflows, the model excels at agentic tasks, multi-step tool use, and retrieval-augmented generation (RAG) with built-in document citation, making it a highly efficient, secure choice for demanding enterprise environments.

- Official technology site: https://huggingface.co/CohereForAI/c4ai-command-a-03-2025
- Public AI Tinkerers demos and talks: 1
- Result page: 1 of 1

## Recent Public Talks and Demos

### [A Guardrail for the Hardest Conversations: (Bilingual) Youth Crisis Detection](https://montreal.aitinkerers.org/talks/rsvp_noPwfE2FLcI)

A stateful, multi-turn input guardrail that screens an entire sensitive youth mental health conversation arc (not just the latest input) to catch crises that build up gradually ("slow drift"), the failure mode where each turn looks benign but the cumulative trajectory is high-risk. Live, I'll walk through the actual system: the two-stage stack (fine-tuned mmBERT classifier → Cohere c4ai chain-of-thought judge), the 5-question reasoning prompt that made the difference, and the evaluation harness output on a hidden validation set (F1 0.899, recall 0.954 at ~1.16s/sample). I'll show the architecture diagram, the prompt engineering and the red-team CSVs that trained the classifier.

- Event context: AI Tinkerers Montreal - June Demo Meetup — 2026-06-17 — Montreal
- Public talk page: https://montreal.aitinkerers.org/talks/rsvp_noPwfE2FLcI

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