Cohere

Cohere and Cohere Labs released Cohere Transcribe Arabic, a 2B parameter automatic speech recognition model optimized for Arabic dialects and Arabic-English code-switching. The open-source model achieves a 25.9% average word error rate across major Arabic ASR benchmarks, outperforming models up to 30B parameters.

Cohere Labs has released North Mini Code 1.0, a 30B-parameter sparse Mixture-of-Experts model with 3B active parameters and a 256K context window. The Apache 2.0-licensed model is optimized for agentic software engineering, featuring 128 experts with 8 activated per token, and trained specifically for tool use in coding tasks.

Cohere has released Command A+ as an open source model under Apache 2.0 license. The sparse mixture-of-experts architecture features 25 billion active parameters out of 218B total parameters, supports 128K input context length, and includes vision capabilities alongside tool use and reasoning features.

Cohere has released Command A+, an open-source sparse mixture-of-experts model with 218 billion total parameters and 25 billion active parameters. The model features W4A4 quantization allowing deployment on a single Nvidia B200 GPU, supports 128K input context, and includes built-in chain-of-thought reasoning with vision capabilities.

Cohere has released Transcribe, a 2 billion parameter open-source automatic speech recognition model that the company claims tops the Hugging Face Open ASR Leaderboard with a 5.42% word error rate. The model supports 14 languages and is available under Apache 2.0 license, outperforming OpenAI's Whisper Large v3 and competing models on both accuracy and throughput metrics.

Cohere Labs has released tiny-aya-global, a lightweight text generation model trained to support conversational tasks across 100+ languages. The model is available on Hugging Face under a CC-BY-NC-4.0 license and builds on the tiny-aya-base architecture.