Command A+ is an open source model with 25 billion active parameters and 218B total parameters model optimized for agentic, multilingual, and reasoning-heavy tasks with a focus on enterprise performance, while also providing support for vision inputs for processing image inputs. Developed by: Cohere and Cohere Labs * Point of Contact: **Cohere Labs** * License: Apache 2.0 * Model: command-a-plus-05-2026 * Model Size: 25B active parameters, 218B total parameters * Context length: 128K input
Command A+ is an open source model with 25 billion active parameters and 218B total parameters model optimized for agentic, multilingual, and reasoning-heavy tasks with a focus on enterprise performance, while also providing support for vision inputs for processing image inputs. All three quantizations show negligible differences in benchmark quality and performance. **Our recommended quantization for most uses is W4A4 which boasts superior speed and latency characteristics alongside a smaller hardware footprint.** Please install transformers from the source repository that includes the necessary changes for this model.
command-r-08-2024 is an update of the Command R with improved performance for multilingual retrieval-augmented generation (RAG) and tool use. More broadly, it is better at math, code and reasoning and...
command-r-plus-08-2024 is an update of the Command R+ with roughly 50% higher throughput and 25% lower latencies as compared to the previous Command R+ version, while keeping the hardware footprint...
Command R7B (12-2024) is a small, fast update of the Command R+ model, delivered in December 2024. It excels at RAG, tool use, agents, and similar tasks requiring complex reasoning...
North Micro Vision Instruct is a 2.4B-parameter open-weight vision-language model with native-resolution image support, released under the Apache 2.0 license. It is designed as a compact foundation for prototyping, task-specific fine-tuning, and specialized multimodal applications. > **Technical deep dive:** Read the North Micro Vision technical blog post for architecture, training, and evaluation details. - Native-resolution image processing that preserves aspect ratios and fine visual detail. - Broad image-understanding capabilities across VQA, captioning, grounding, OCR, charts, and documents. - Multilingual and multi-image support. - Compact 2.4B-parameter scale suited to customization and deployment experimentation. - Apache 2.0-licensed model weights.
North Mini Code is Cohere's first agentic coding model and the debut of its North family. A sparse mixture-of-experts model with 30B total parameters and 3B active, it is optimized...
