MIXdevAI-gemma3-4B-GGUF – AI Model by kirilldual0987 | AlphaNeural AI

You can deploy this model and start earning money today!

kirilldual0987/
MIXdevAI-gemma3-4B-GGUF

like

0

text-generation

Kolyadual/MIXdevAI-gemma3-4B

endpoints_compatible

Views

No views yet

MIXdevAI-gemma3-4B-GGUF

Full set of GGUF quantizations for Kolyadual/MIXdevAI-gemma3-4B.

Based on the Gemma 3 architecture.

Files

File	Quantization	Type
`mixdev-gemma3-f16.gguf`	F16	Base Model
`mixdev-gemma3-q8_0.gguf`	Q8_0	Text Model
`mixdev-gemma3-q6_k.gguf`	Q6_K	Text Model
`mixdev-gemma3-q5_k_m.gguf`	Q5_K_M	Text Model
`mixdev-gemma3-q5_k_s.gguf`	Q5_K_S	Text Model
`mixdev-gemma3-q5_1.gguf`	Q5_1	Text Model
`mixdev-gemma3-q5_0.gguf`	Q5_0	Text Model
`mixdev-gemma3-q4_k_m.gguf`	Q4_K_M	Text Model
`mixdev-gemma3-q4_k_s.gguf`	Q4_K_S	Text Model
`mixdev-gemma3-q4_1.gguf`	Q4_1	Text Model
`mixdev-gemma3-q4_0.gguf`	Q4_0	Text Model
`mixdev-gemma3-q3_k_l.gguf`	Q3_K_L	Text Model
`mixdev-gemma3-q3_k_m.gguf`	Q3_K_M	Text Model
`mixdev-gemma3-q3_k_s.gguf`	Q3_K_S	Text Model
`mixdev-gemma3-q2_k.gguf`	Q2_K	Text Model

Quantization notes

Q8_0 / F16: Almost lossless. Best quality, largest size.
Q6_K / Q5_K_M: Excellent balance between quality and size.
Q4_K_M: Golden standard for local inference.
Q3_K_M / Q2_K: Noticeable quality degradation. Use only if you have severe RAM/VRAM constraints.

How to run locally

Example using llama.cpp server:

bash

llama-server \
  -m mixdev-gemma3-q4_k_m.gguf \
  -ngl 999 \
  --host 0.0.0.0 --port 8080 \
  -c 32768