u/JLeonsarmiento

Amazing news!!!

Sony a74
12-24 F4
Seafrogs Housing

Like when?

https://huggingface.co/microsoft/Mage-Flow-Turbo

Properly done this time.

Models as the GIFs are displayed:

1. Qwen3.6-27B - 4bit

2. Qwen3.6-MoE - 6bit

3. Ornith-35B - 6bit

4. Gemma-4-26B - 6bit

5. Qwen3.6-MoE - 4bit

6. HuiHui-Qwen3.6-MoE - 6bit

7. Agents-A1 - 6bit

Inference parameters:

Qwen3.6 & HuiHui Abliterated:

temperature 0.6 - top_p 0.95 - top_k 20 - min_p 0.01 - repeat_penalty 1.05

Ornith-1.0-35B:

temperature 1.0 - top_p 1.0 - top_k 40 - min_p 0.01 - repeat_penalty 1.05

Gemma-4:

temperature 1.0 - top_p 1.0 - top_k 64 - min_p 0.01 - repeat_penalty 1.1

Agents-A1:

temperature 0.85 - top_p 0.95 - top_k 20 - min_p 0.01 - repeat_penalty 1.05

Prompt: "Create a beautiful, relaxing flight simulator in a single html file with mountains, clouds, and endless procedural terrain"

Harnes: Pi

Served by: oMLX

Method: single prompt. If the html file doesn't work everything was deleted, Pi session was restarted, and model had to start from scratch again. maximum of 3 tries.

Models Quants used:

https://huggingface.co/collections/leonsarmiento/local-sota-for-48gb-macs

Kind of unexpected.

Happy for Gemma-4/Google, big win for us, LocalLLMers.

Yet Qwen3.6 still does better in Hermes than Gemma-4 somehow.

We need Gemma-4.1 fine-tuned on Agentic-tasks. That would be killer.