gemma-2-9b-it · bartowski

gemma-2-9b-it F16

This file is exactly 10,687,308,704 bytes — 9.95 GiB / 10.69 GB at an effective 9.251 bits per weight. The nominal rate for F16 is lower; mixed-precision tensors make the real figure higher, always.

From the file· 1 file(s), summedFrom the file· 464 tensors parsed

Get it

9.95 GiB · 1 file
llama.cpp
llama-cli -hf bartowski/gemma-2-9b-it-GGUF:F16

Downloads and runs in one step, resolving the quantization by name.

Hugging Face CLI
hf download bartowski/gemma-2-9b-it-GGUF gemma-2-9b-it-Q8_0-f16.gguf
Direct download

Straight from the Hugging Face CDN — we host nothing and earn nothing from this. Verify what you received against the exact byte count above; a size mismatch is the usual cause of a file that will not load.

Size
9.95 GiB
10.69 GB
Effective bpw
9.251
from real bytes ÷ params
Tensors
464
Header
6.06 MB
GGUF metadata

What this quantization actually contains

per-tensor types, parsed from the GGUF header
Q8_0
294
F32
169
F16
1

A quantization label names a mixture, not a uniform precision. Attention and output tensors are routinely kept at higher precision than the label implies, which is exactly why the effective bits-per-weight above exceeds the nominal rate.

Fit by accelerator

AcceleratorMemoryTotal @4KTotal @32KFitstok/s @4K
Arc A310 4GB4 GB12.11 GiB16.78 GiBno
Arc A350M 4GB4 GB12.11 GiB16.78 GiBno
Arc A370M 4GB4 GB12.11 GiB16.78 GiBno
Arc A530M 4GB4 GB12.11 GiB16.78 GiBno
Arc Pro A30M 4GB4 GB12.11 GiB16.78 GiBno
Radeon Pro W64004 GB12.21 GiB16.88 GiBno
Radeon RX 64004 GB12.21 GiB16.88 GiBno
Radeon RX 6500 XT4 GB12.21 GiB16.88 GiBno
RTX A4004 GB12.31 GiB16.98 GiBno
Arc A380 6GB6 GB12.11 GiB16.78 GiBno
Arc Pro A40 6GB6 GB12.11 GiB16.78 GiBno
Arc Pro A50 6GB6 GB12.11 GiB16.78 GiBno
GeForce RTX 20606 GB12.11 GiB16.78 GiBno
GeForce RTX 30506 GB12.11 GiB16.78 GiBno
GeForce RTX 3060 OEM6 GB12.11 GiB16.78 GiBno
RTX A20006 GB12.31 GiB16.98 GiBno
Apple M18 GB11.86 GiB16.53 GiBno
Apple M28 GB11.86 GiB16.53 GiBno
Apple M38 GB11.86 GiB16.53 GiBno
Apple M48 GB11.86 GiB16.53 GiBno
Arc A530M 8GB8 GB12.11 GiB16.78 GiBno
Arc A550M 8GB8 GB12.11 GiB16.78 GiBno
Arc A570M 8GB8 GB12.11 GiB16.78 GiBno
Arc A580 8GB8 GB12.11 GiB16.78 GiBno
Spec sheetPredictedwhat these mean

Memory at context

ContextWeightsKV (f16)KV (q8_0)Working bufferTotal (f16)
4,0969.95 GiB1.31 GiB0.70 GiB0.34 GiB11.61 GiB
8,1929.95 GiB2.05 GiB1.09 GiB0.34 GiB12.34 GiB
16,3849.95 GiB3.36 GiB1.79 GiB0.34 GiB13.66 GiB
32,7689.95 GiB5.99 GiB3.18 GiB0.34 GiB16.28 GiB
65,5369.95 GiB11.24 GiB5.97 GiB0.34 GiB21.53 GiB
131,0729.95 GiB21.74 GiB11.55 GiB0.34 GiB32.03 GiB
From the filePredictedwhat these mean

Quantizing the KV cache to q8_0 is a roughly 2× lever on the dominant term at long context, and it is the single most useful setting most local users never touch. Totals here exclude the allocator reserve your driver takes, which is hardware-specific — the per-accelerator table above includes it.