Yi-Coder-1.5B-Chat · bartowski

Yi-Coder-1.5B-Chat Q5_K_M

This file is exactly 1,100,185,792 bytes — 1.02 GiB / 1.10 GB at an effective 5.961 bits per weight. The nominal rate for Q5_K_M is lower; mixed-precision tensors make the real figure higher, always.

From the file· 1 file(s), summedFrom the file· 219 tensors parsed

Get it

1.02 GiB · 1 file
llama.cpp
llama-cli -hf bartowski/Yi-Coder-1.5B-Chat-GGUF:Q5_K_M

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

Hugging Face CLI
hf download bartowski/Yi-Coder-1.5B-Chat-GGUF Yi-Coder-1.5B-Chat-Q5_K_M.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.

Repository →
Size
1.02 GiB
1.10 GB
Effective bpw
5.961
from real bytes ÷ params
Tensors
219
Header
1.49 MB
GGUF metadata

What this quantization actually contains

per-tensor types, parsed from the GGUF header
Q5_K
133
F32
49
Q6_K
13
Q5_1
12
Q8_0
12

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

AcceleratorMemory○Total @4K◐Total @32K◐Fits◐tok/s @4K◐
Arc A310 4GB4 GB2.56 GiB7.81 GiByes4K only36±30%
Arc A350M 4GB4 GB2.56 GiB7.81 GiByes4K only33±30%
Arc A370M 4GB4 GB2.56 GiB7.81 GiByes4K only33±30%
Arc A530M 4GB4 GB2.56 GiB7.81 GiByes4K only62±30%
Arc Pro A30M 4GB4 GB2.56 GiB7.81 GiByes4K only33±30%
Radeon Pro W64004 GB2.66 GiB7.91 GiByes4K only44±26.5%
Radeon RX 64004 GB2.66 GiB7.91 GiByes4K only44±26.5%
Radeon RX 6500 XT4 GB2.66 GiB7.91 GiByes4K only49±26.5%
RTX A4004 GB2.76 GiB8.01 GiByes4K only31±22%
Arc A380 6GB6 GB2.56 GiB7.81 GiByes4K only52±30%
Arc Pro A40 6GB6 GB2.56 GiB7.81 GiByes4K only54±30%
Arc Pro A50 6GB6 GB2.56 GiB7.81 GiByes4K only54±30%
GeForce RTX 20606 GB2.56 GiB7.81 GiByes4K only126±12.9%
GeForce RTX 30506 GB2.56 GiB7.81 GiByes4K only66±12.9%
GeForce RTX 3060 OEM6 GB2.56 GiB7.81 GiByes4K only126±12.9%
RTX A20006 GB2.76 GiB8.01 GiByes4K only89±22%
Apple M18 GB2.31 GiB7.56 GiByes4K only28±8.3%
Apple M28 GB2.31 GiB7.56 GiByes4K only38±8.3%
Apple M38 GB2.31 GiB7.56 GiByes4K only38±8.3%
Apple M48 GB2.31 GiB7.56 GiByes4K only43±8.3%
Arc A530M 8GB8 GB2.56 GiB7.81 GiByes4K only62±30%
Arc A550M 8GB8 GB2.56 GiB7.81 GiByes4K only62±30%
Arc A570M 8GB8 GB2.56 GiB7.81 GiByes4K only62±30%
Arc A580 8GB8 GB2.56 GiB7.81 GiByes4K only122±30%
○Spec sheet◐Predictedwhat these mean

Memory at context

ContextWeights●KV (f16)●KV (q8_0)●Working buffer◐Total (f16)◐
4,0961.02 GiB0.75 GiB0.40 GiB0.29 GiB2.06 GiB
8,1921.02 GiB1.50 GiB0.80 GiB0.29 GiB2.81 GiB
16,3841.02 GiB3.00 GiB1.59 GiB0.29 GiB4.31 GiB
32,7681.02 GiB6.00 GiB3.19 GiB0.29 GiB7.31 GiB
65,5361.02 GiB12.00 GiB6.38 GiB0.29 GiB13.31 GiB
131,0721.02 GiB24.00 GiB12.75 GiB0.29 GiB25.31 GiB
●From the file◐Predictedwhat 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.