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The VibeThinker-3B model achieves state-of-the-art math and coding reasoning performance, scoring 94.3 on AIME'26 and 96.1% on unseen LeetCode problems, demonstrating that small models can reach frontier-level reasoning in verifiable domains.
Cleo is a finetuned version of Qwen3.5-2B-Base designed for text-to-SQL tasks, using a unified harness for training and inference that supports live execution evidence and safety checks. All code, model, and datasets are open-source.
Microsoft launches Fara-7B, an efficient Computer Use Agent with only 7B parameters, surpassing larger models on web tasks, supporting pure local deployment, and achieving low-cost desktop automation.
Microsoft has released Fara-7B, a small 7B-parameter language model focused on pure local desktop automation. It can directly take over your mouse and keyboard to execute repetitive workflows, with low cost and no need for internet connectivity.
Supra Labs released Supra Title, a 350M parameter model specialized for generating chat conversation titles. Built on LFM2.5, it runs on any hardware in GGUF format and requires no system prompt.
VibeThinker-3B is a 3B-parameter model that achieves frontier-level reasoning performance on math, coding, and STEM benchmarks by optimizing the Spectrum-to-Signal Principle (SSP) post-training pipeline, reaching performance comparable to much larger models.
This paper introduces IAPO, a reinforcement learning algorithm that improves tool-calling capabilities in multimodal small language models by aligning input attribution with a stronger teacher. Experiments on Qwen2.5-VL-3B show an average 3% improvement in visual question answering accuracy across six test sets.
The author shares learnings from training a 160M parameter LLM from scratch, experimenting with architectures like multi-token prediction and hierarchical reasoning models. They emphasize the importance of fast iteration, simplifying ideas, and understanding why architectures work.
Microsoft announced two new on-device AI models at Build 2026: Aion 1.0 Instruct, an open-weights small language model, and Aion 1.0 Plan, a 14B parameter reasoning and tool-calling model for local agentic workflows.
Trained a 75M parameter LLM called KeyLM from scratch on 18B tokens, achieving competitive instruction-following scores against larger models while using fewer parameters and less data.
OpenBMB releases MiniCPM5-1B, a leading 1B open weights LLM that achieves the highest Artificial Analysis Intelligence Index score (17.9) in its size class, surpassing larger models like Qwen3.5 2B while using fewer parameters.
MiniCPM5-1B is a new 1B parameter AI model from OpenBMB featuring hybrid reasoning with Think/No-Think modes, 128K context, and Apache 2.0 license, running on various hardware.
MiniCPM5-1B is fully open-sourced with weights, training data, and deployment code; it achieves top scores among sub-2B models and runs on edge devices.
SupraLabs released Supra-50M, a compact 50M-parameter causal language model with base and instruct versions, trained on 20B tokens from fineweb-edu, achieving competitive benchmarks against larger models like GPT-2 and SmolLM.
Sapient Intelligence introduces HRM-Text, a 1B-parameter reasoning language model trained on only 40B tokens with a budget of $1,000, achieving competitive performance while drastically reducing data and compute requirements.
Microsoft released Fara-7B, a 7-billion parameter small language model that can autonomously control a computer to perform tasks like clicking, scrolling, and filling forms, running on-device and beating larger models like OpenAI's computer-use agent on benchmarks.
Microsoft released Fara-7B, a 7 billion parameter agentic small language model for computer use, achieving state-of-the-art performance among models of its size and competitive with larger systems.
Cactus-Compute released Needle, a 26M parameter open-source model distilled from Gemini for efficient on-device function calling using a novel Simple Attention Network architecture without MLPs.
Two new open-source small language models are being released: one matches state-of-the-art accuracy at up to 93x smaller size, and the other outperforms a recent OpenAI model. The first model drops tomorrow.
OpenBMB has released MiniCPM V4.6, a 1B-parameter multimodal large language model optimized for mobile devices under the Apache 2.0 license. It features mixed visual token compression and claims approximately 1.5x faster throughput than Qwen3.5 0.8B while running natively on iOS, Android, and HarmonyOS.