LLM / MODEL FILE
Gemma 3 27B
Google model for larger multimodal assistant. Memory figures are estimates, not measured benchmarks.
Parameters27.0B
Q4 estimate20.4 GB
WorkloadLLM
Best proofTest exact runtime
QUANTIZATION
Memory scenarios
MEMORY FILE
Q4_K_M
common balance of size and quality. Estimated requirement: 20.4 GB.
Inspect →MEMORY FILEQ5_K_M
more quality with a larger footprint. Estimated requirement: 24.6 GB.
Inspect →MEMORY FILEQ8_0
near-full quality with high memory use. Estimated requirement: 35.0 GB.
Inspect →MEMORY FILEFP16
full half-precision weights. Estimated requirement: 68.6 GB.
Inspect →CLOSEST FITS
Hardware near the Q4 line
FITS
RTX 3090 24GB
used-market 24 GB local AI favorite
24 GB VRAMInspect →FITSRTX 4090 24GB
strong 24 GB inference and image generation
24 GB VRAMInspect →FITSRadeon RX 7900 XTX 24GB
24 GB value with a more selective software path
24 GB VRAMInspect →OFFLOADRTX 4060 Ti 16GB
efficient 16 GB consumer option
16 GB VRAMInspect →OFFLOADRTX 4070 Ti Super 16GB
faster 16 GB card for mid-size models
16 GB VRAMInspect →OFFLOADRTX 4080 Super 16GB
high throughput but still limited to 16 GB
16 GB VRAMInspect →Runtime, drivers, memory bandwidth, context, batch size, offloading, and model architecture all matter.