anika-ai-fast

Anika AI Fast

The fast, uncensored llama.cpp build of the strongest SuperGemma text line.

This release is for people who want three things together:

• a model that feels less censored than stock chat releases
• a model that is more capable than the raw base on practical text workloads
• a compact local GGUF that still serves quickly on Apple Silicon

Why this build

• Uncensored chat behavior without forcing every prompt into coding mode
• Tuned from the strongest fast line instead of the raw base
• Neutral chat template baked into the GGUF to reduce prompt-routing bugs
• Verified on Apple Silicon with clean general-chat and coding responses

Headline numbers

• Base model: google/gemma-4-26B-A4B-it
• Format: GGUF Q4_K_M
• General Korean prompt speed: 222.0 tok/s
• Generation speed: 89.4 tok/s
• Derived from the verified SuperGemma Fast MLX line

Why this build is appealing

• Carries the stronger Fast weights instead of the plain stock base
• Keeps general chat natural instead of routing everything into coding mode
• Preserves the uncensored release identity while staying useful on normal prompts
• Gives you a practical llama.cpp deployment target without losing the personality of the tuned line

Why it is better than stock

• Inherits the Fast line improvements over the original local baseline:
  • Quick bench overall: 95.8 vs 91.4
  • Faster average generation on the MLX reference run: 46.2 tok/s vs 42.5 tok/s
  • Higher scores in code, logic, browser workflows, and Korean
• Ships with a neutral embedded template to avoid the older routing bug where simple questions drifted into coding/tool-call behavior

Included file

• supergemma4-26b-uncensored-fast-v2-Q4_K_M.gguf

Quick local checks

Tested on Apple M4 Max with llama.cpp:

• General Korean prompt: 봄에 먹기 좋은 한식 반찬 5개 추천
  • Prompt speed: 222.0 tok/s
  • Generation speed: 89.4 tok/s
  • Output stayed in normal Korean assistant mode
• Code prompt: 파이썬으로 피보나치 함수를 짧게 작성해줘
  • Prompt speed: 704.9 tok/s
  • Generation speed: 89.4 tok/s
  • Output returned concise Python code correctly

Notes

• This GGUF is exported from the supergemma4-26b-uncensored-fast-v2 MLX line.
• Gemma 4 MoE expert tensors were converted with a patched local converter so GGUF export works correctly.
• A neutral template is embedded to avoid the old issue where general prompts were pushed into coding/tool-call behavior.