LLM / MODEL FILE
Mistral Small 24B
Mistral model for mid-size general assistant. Memory figures are estimates, not measured benchmarks.
Parameters24.0B
Q4 estimate18.3 GB
WorkloadLLM
Best proofTest exact runtime
QUANTIZATION
Memory scenarios
MEMORY FILE
Q4_K_M
common balance of size and quality. Estimated requirement: 18.3 GB.
Inspect →MEMORY FILEQ5_K_M
more quality with a larger footprint. Estimated requirement: 22.0 GB.
Inspect →MEMORY FILEQ8_0
near-full quality with high memory use. Estimated requirement: 31.3 GB.
Inspect →MEMORY FILEFP16
full half-precision weights. Estimated requirement: 61.1 GB.
Inspect →CLOSEST FITS
Hardware near the Q4 line
TIGHT
RTX 4060 Ti 16GB
efficient 16 GB consumer option
16 GB VRAMInspect →TIGHTRTX 4070 Ti Super 16GB
faster 16 GB card for mid-size models
16 GB VRAMInspect →TIGHTRTX 4080 Super 16GB
high throughput but still limited to 16 GB
16 GB VRAMInspect →TIGHTRTX 5060 Ti 16GB
current mid-range 16 GB option
16 GB VRAMInspect →TIGHTRTX 5070 Ti 16GB
current performance card with 16 GB ceiling
16 GB VRAMInspect →TIGHTRTX 5080 16GB
fast compute with a 16 GB memory ceiling
16 GB VRAMInspect →Runtime, drivers, memory bandwidth, context, batch size, offloading, and model architecture all matter.