Cohere Launches Tiny Aya: 3.35B Open-Weight Models Supporting 70+ Languages for Offline Use
Overview
Cohere unveiled Tiny Aya at the India AI Summit on February 17, 2026 — a family of compact, open-weight multilingual models designed to run offline on standard laptops. The release targets language accessibility in regions underserved by English-centric AI tools.
Model Specifications
- Parameters: 3.35 billion
- License: Open-weight (MIT)
- Training infrastructure: Single cluster of 64 H100 GPUs
- Languages supported: 70+
Regional Variants
Cohere released region-specific fine-tuned variants:
- TinyAya-Fire: South Asian languages — Hindi, Urdu, Bengali, Punjabi, Gujarati, Tamil, Telugu, Marathi
- TinyAya-Earth: African languages
- TinyAya-Water: Asia-Pacific, Western Asian, and European languages
Availability
Models are available on HuggingFace, Kaggle, and Ollama for local deployment, as well as through the Cohere platform API. The efficient training footprint — just 64 H100 GPUs — also positions Tiny Aya as a reference point for cost-effective multilingual model development.
Source: TechCrunch
Related Articles
Ollama 0.17, released February 22, introduces a new native inference engine replacing llama.cpp server mode, delivering up to 40% faster prompt processing and 18% faster token generation on NVIDIA GPUs, plus improved multi-GPU tensor parallelism and AMD RDNA 4 support.
A popular r/LocalLLaMA thread points to karpathy/autoresearch, a small open-source setup where an agent edits one training file, runs 5-minute experiments, and iterates toward lower validation bits per byte.
A high-scoring LocalLLaMA thread surfaced Sarvam AI's release of two Apache 2.0 reasoning models, Sarvam 30B and Sarvam 105B. The company says both were trained from scratch in India, use Mixture-of-Experts designs, and target reasoning, coding, agentic workflows, and Indian-language performance.
Comments (0)
No comments yet. Be the first to comment!