Agnes-AI/Agnes-3.0-Qwen (QFN finetune)
Strong agentic performance: agnes-3.0-qwen scores highest in its comparison set on τ3-Banking, and is within about one point of the best model on Terminal-Bench 2.1, while being a much smaller model than most of the flagship systems it is compared against.

Proof1 community thread
Key points
- Reliable instruction following: on IFBench, agnes-3.0-qwen outperforms GPT-5.6 Sol (Max) and Claude Opus 4.8 (Max).
- Built for demanding work: a 1M-token context window, extended reasoning with selectable reasoning effort (xhigh, medium, low), tool calling, and text, image, and video understanding.
- Model type Multimodal reasoning model (hybrid attention MoE)
- Total parameters ~180B (512 experts, 10 active per token)
Sources (1)
- [1]Agnes-AI/Agnes-3.0-Qwen (QFN finetune)r/LocalLLaMA (top, daily) · Oct 20, 05:11 PM
- Strong agentic performance: agnes-3.0-qwen scores highest in its comparison set on τ3-Banking, and is within about one point of the best model on Terminal-Bench 2.1, while being a much smaller model than most of the flagship systems it is compared against.
- Reliable instruction following: on IFBench, agnes-3.0-qwen outperforms GPT-5.6 Sol (Max) and Claude Opus 4.8 (Max).
Extractive summary: sentences quoted from the sources.
Hype check
Independently evaluated4 independent looks since
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- Follow-up · Oct 20, 2026When Do LLMs Help with Feature Selection? A Systematic Empirical Study
- Follow-up · Oct 20, 2026Fine-tuning GPT-OSS-20B for multilingual reasoning on Amazon SageMaker HyperPod
Before this
- Oct 20, 2026ornith-ai/Ornith-1.5-122B (Qwen finetune)
- Oct 20, 2026[AINews] DeepSeek DeepInfer: Open Source SOTA Inference running 155T toks/day/cluster making $22m/day at ~80% margin for a 81 day payback
- Oct 20, 2026Do Diffusion LLMs Scale? Testing Mercury 3 + Decide
- Oct 20, 2026migtissera/Tess-4.5-27B (Qwen finetune)
- Oct 19, 2026MiniMax M3.1 Flash shows China's AI price race has no floor in sight
- Oct 19, 2026TorchNeuron: running HF models on AWS Trainium is easier than ever

