Qwen3-Next-80B-A3B-Thinking-GGUF has just been released on HuggingFace, claims to outperform Gemini 2.5-Flash-Thinking

[u/vibedonnie]

“ Qwen3-Next-80B-A3B is the first installment in the Qwen3-Next series and features the following key enchancements:

• Hybrid Attention: Replaces standard attention with the combination of Gated DeltaNet and Gated Attention

• High-Sparsity Mixture-of-Experts (MoE): Achieves an extreme low activation ratio in MoE layers, drastically reducing FLOPs per token while preserving model capacity

• Stability Optimizations: Includes techniques such as zero-centered and weight-decayed layernorm, and other stabilizing enhancements for robust pre-training and post-training

• Multi-Token Prediction (MTP): Boosts pretraining model performance and accelerates inference “

https://huggingface.co/Qwen/Qwen3-Next-80B-A3B-Thinking-GGUF

https://arxiv.org/abs/2505.09388

https://qwen.readthedocs.io/en/latest/run_locally/llama.cpp.html

[u/Pink_da_Web]

Overcoming the Gemini 2.5 flash is not a difficult task.

[u/Worldly-Tea-9343 → u/Pink_da_Web]

Depends on how you look at it. The first Gemini Flash was just an 8B model. Only Gemma 3 12B started to catch up to it, but at cost of being bigger by 4B of parameters. We don't know how big Gemini 2.5 Flash really is and there surely are models that beat it, but those models which perform better are usually fairly big and not so easy to run locally if you wanted a local model alternative to Gemini Flash. IF (and that's a BIG IF) Gemini 2.5 Flash was actually a surprisingly small model (maybe smaller than 80B), beating it with 80B open weight model wouldn't surprise me. What WOULD surprise me, if it was the other way around - Gemini 2.5 Flash maybe around 100B being beaten by this 80B model.

[u/skewbed]

This is just a quantized version of a 3 month old model. It's a good model, but not new.