Ai2 Unveils Compact AI Model Outperforming Google, Meta Rivals

Small AI models are making waves this week.

On Thursday, Ai2, a nonprofit AI research group, launched Olmo 2 1B, a 1-billion-parameter model that surpasses similarly-sized models from Google, Meta, and Alibaba across multiple benchmarks. Parameters, often called weights, are the internal elements that shape a model’s performance.

Olmo 2 1B is freely available under an Apache 2.0 license on Hugging Face, a platform for AI developers. Unlike most models, it can be fully recreated, with Ai2 sharing the code and datasets (Olmo-mix-1124, Dolmino-mix-1124) used in its development.

While smaller models may lack the power of larger ones, they don’t demand high-end hardware, making them ideal for developers and hobbyists using standard laptops or consumer devices.

Recent days have seen a surge in small model releases, from Microsoft’s Phi 4 reasoning family to Qwen’s 2.5 Omni 3B. Most, including Olmo 2 1B, can run smoothly on modern laptops or even mobile devices.

Ai2 notes that Olmo 2 1B was trained on 4 trillion tokens from public, AI-generated, and curated sources. A million tokens roughly equals 750,000 words.

In arithmetic reasoning tests like GSM8K, Olmo 2 1B outperforms Google’s Gemma 3 1B, Meta’s Llama 3.2 1B, and Alibaba’s Qwen 2.5 1.5B. It also excels in TruthfulQA, a benchmark for factual accuracy.

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This model was pretrained on 4T tokens of high-quality data, following the same standard pretraining into high-quality annealing of our 7, 13, & 32B models. We upload intermediate checkpoints from every 1000 steps in training.

Access the base model: https://t.co/xofyWJmo85 pic.twitter.com/7uSJ6sYMdL

— Ai2 (@allen_ai) May 1, 2025

Ai2 cautions that Olmo 2 1B has risks. Like all AI models, it may generate problematic outputs, including harmful or sensitive content and inaccurate information. Ai2 advises against using it in commercial applications.