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UkisAI releases the Swift Series of efficient reasoning LLMs based on Qwen, with models offering significant token reduction and accuracy improvements, along with various quantization options for deployment.
Granite 4.2 is IBM's new family of reasoning LLMs available in 3B, 8B, and 30B sizes, featuring thinking modes, tool calling, and trained with a multi-stage reinforcement learning pipeline under the Apache 2.0 license.
MIThinker proposes a lightweight reasoning model for motivational interviewing counseling agents, trained via supervised fine-tuning and reinforcement learning to generate therapeutic thoughts, achieving MI competency comparable to state-of-the-art systems with lower computation.
This paper presents RaDaR, a 32B open-source reasoning LLM trained on public and synthetic rare disease cases, which outperforms larger models like DeepSeek-R1 in diagnosis benchmarks and improves physician accuracy by 21.44 percentage points in a randomized trial.