Quantization publisher

qwp4w3hyb

qwp4w3hyb publishes 43 quantizations across 3 models in our index, averaging 3.981 effective bits per weight. Their files differ in size from other publishers' builds of the same nominal quantization on 23 of the pairs we can compare — the same label does not mean the same file.

From the file· summed file bytes
Repositories
3
Quantizations
43
Models covered
3
Avg effective bpw
3.981
across their files

Same model, same quant label, different bytes

largest disagreements first
ModelQuantqwp4w3hybvsTheirsDifference
Meta-Llama-3-70B-InstructQ4_K_M39.60 GiBLiteLLMs39.61 GiB-0.0%
Meta-Llama-3-70B-InstructQ5_K_M46.52 GiBLiteLLMs46.53 GiB-0.0%
Meta-Llama-3-70B-InstructQ4_K_S37.58 GiBLiteLLMs37.58 GiB-0.0%
Meta-Llama-3-70B-InstructQ5_K_S45.32 GiBLiteLLMs45.32 GiB-0.0%
Phi-3-mini-128k-instructQ4_K_M2.23 GiBlmstudio-community2.23 GiB-0.0%
Phi-3-mini-128k-instructQ4_K_S2.04 GiBbartowski2.04 GiB-0.0%
Phi-3-mini-128k-instructQ5_K_M2.62 GiBbartowski2.62 GiB-0.0%
Phi-3-mini-128k-instructQ5_K_M2.62 GiBlmstudio-community2.62 GiB-0.0%
Phi-3-mini-128k-instructQ5_K_S2.46 GiBbartowski2.46 GiB-0.0%
Phi-3-mini-128k-instructQ6_K2.92 GiBbartowski2.92 GiB-0.0%
Phi-3-mini-128k-instructIQ3_XS1.51 GiBbartowski1.51 GiB-0.0%
Phi-3-mini-128k-instructQ8_03.78 GiBbartowski3.78 GiB-0.0%
Phi-3-mini-128k-instructQ8_03.78 GiBlmstudio-community3.78 GiB-0.0%
Phi-3-mini-128k-instructIQ2_M1.23 GiBbartowski1.23 GiB-0.0%
Phi-3-mini-128k-instructIQ3_M1.73 GiBbartowski1.73 GiB-0.0%
Phi-3-mini-128k-instructIQ3_M1.73 GiBlmstudio-community1.73 GiB-0.0%
Phi-3-mini-128k-instructQ6_K2.92 GiBlmstudio-community2.92 GiB-0.0%
Phi-3-mini-128k-instructIQ4_XS1.92 GiBbartowski1.92 GiB-0.0%
Phi-3-mini-128k-instructIQ4_XS1.92 GiBlmstudio-community1.92 GiB-0.0%
Phi-3-mini-128k-instructQ4_K_M2.23 GiBbartowski2.23 GiB-0.0%
Phi-3-mini-128k-instructIQ2_XS1.07 GiBbartowski1.07 GiB-0.0%
Phi-3-mini-128k-instructIQ2_S1.13 GiBbartowski1.13 GiB-0.0%
Phi-3-mini-128k-instructIQ3_XXS1.41 GiBbartowski1.41 GiB-0.0%

A quantization label describes a target, not a recipe. Publishers make different choices about which tensors to keep at higher precision, and some apply an importance matrix while others don't — so two files both honestly labelled the same thing can differ measurably in size and in quality.

Models they publish

ModelQuantizationsSmallest
Phi-3-mini-128k-instruct190.78 GiB
Meta-Llama-3-70B-Instruct1514.29 GiB
c4ai-command-r-plus921.59 GiB