EpistemeAI has released Reasoning-Medical0.1-27B, a medical fine-tuned model based on the Qwen3.5-27B architecture. The model is available for download on Hugging Face and claims to surpass MedGemma in performance. No specific benchmark scores or detailed technical specifications were provided in the source text.
media
r/LocalLLaMA
·
47d ago
·
open_models
EpistemeAI releases Reasoning-Medical0.1-27B, a Qwen3.5-27B medical finetune
from English
Related articles
media
r/LocalLLaMA
·
3h ago
IBM releases Granite 4.2 family with built-in chain-of-thought reasoning
IBM has released the Granite 4.2 family of open-source reasoning models, featuring flagship 30B, mid-size 8B, and compact 3B variants. These models leverage native chain-of-thought capabilities to improve performance on math, coding, and complex multi-step problems.
media
r/LocalLLaMA
·
22d ago
·
32 views
AI9Stars releases G9v3-39A5B, an open weights model with 39B parameters and 5 active experts
AI9Stars has released G9v3-39A5B, an open weights language model designed to deliver stronger reasoning capabilities than its predecessor, ai9stars/G9v3-3B. The model features 39 billion parameters with 5 active experts and is licensed under Apache 2.0 for personal and commercial use.
media
r/LocalLLaMA
·
48d ago
·
20 views
MiniMax plans to launch 2.7-trillion parameter M3 Pro model
Chinese AI company MiniMax is preparing to release a new large language model named M3 Pro, which contains 2.7 trillion parameters. The model is expected to be released and open-sourced as early as the third quarter of this year.
media
r/LocalLLaMA
·
49d ago
·
5 views
Liquid AI releases Antidoom to remove doom loops in reasoning models
Liquid AI has released Antidoom, an open-source method designed to eliminate the "doom loop" failure mode commonly found in reasoning models. The company provided evaluation scores demonstrating significant reductions in error rates for specific model checkpoints.
arxiv
arXiv cs.AI
·
57d ago
·
4 views
RaDaR: A specialized reasoning LLM for accelerating rare disease diagnosis
Researchers present RaDaR, an open-source 32B parameter reasoning large language model designed to accelerate the diagnosis of rare diseases by addressing challenges in clinical deployability and data scarcity. The model was trained on nearly 50,000 public cases and over 100,000 synthetic cases, demonstrating superior performance across benchmarks and external validation centers.