Quantization publisher

SanctumAI

SanctumAI publishes 51 quantizations across 3 models in our index, averaging 5.807 effective bits per weight. Their files differ in size from other publishers' builds of the same nominal quantization on 25 of the pairs we can compare — the same label does not mean the same file.

From the file· summed file bytes
Repositories
3
Quantizations
51
Models covered
3
Avg effective bpw
5.807
across their files

Same model, same quant label, different bytes

largest disagreements first
ModelQuantSanctumAIvsTheirsDifference
Mistral-7B-Instruct-v0.3Q4_K_M4.07 GiBlmstudio-community4.07 GiB-0.0%
Mistral-7B-Instruct-v0.3Q8_07.17 GiBlmstudio-community7.17 GiB-0.0%
Mistral-7B-Instruct-v0.3Q3_K_L3.56 GiBlmstudio-community3.56 GiB-0.0%
Mistral-7B-Instruct-v0.3Q6_K5.54 GiBlmstudio-community5.54 GiB-0.0%
Mistral-7B-Instruct-v0.3Q5_K_M4.78 GiBlmstudio-community4.78 GiB-0.0%
gemma-2-9b-itQ5_K_M6.19 GiBbartowski6.19 GiB-0.0%
gemma-2-9b-itQ3_K_S4.04 GiBbartowski4.04 GiB-0.0%
gemma-2-9b-itQ4_K_M5.37 GiBlmstudio-community5.37 GiB-0.0%
gemma-2-9b-itQ4_K_M5.37 GiBbartowski5.37 GiB-0.0%
gemma-2-9b-itQ4_K_S5.10 GiBbartowski5.10 GiB-0.0%
gemma-2-9b-itQ5_K_S6.04 GiBbartowski6.04 GiB-0.0%
gemma-2-9b-itQ6_K7.07 GiBbartowski7.07 GiB-0.0%
gemma-2-9b-itQ6_K7.07 GiBlmstudio-community7.07 GiB-0.0%
gemma-2-9b-itQ8_09.15 GiBbartowski9.15 GiB-0.0%
gemma-2-9b-itQ8_09.15 GiBlmstudio-community9.15 GiB-0.0%
gemma-2-9b-itQ5_K_M6.19 GiBlmstudio-community6.19 GiB-0.0%
gemma-2-9b-itQ2_K3.54 GiBbartowski3.54 GiB-0.0%
gemma-2-9b-itQ3_K_L4.78 GiBlmstudio-community4.78 GiB-0.0%
gemma-2-9b-itQ3_K_L4.78 GiBbartowski4.78 GiB-0.0%
gemma-2-9b-itQ3_K_M4.43 GiBbartowski4.43 GiB-0.0%
Mistral-7B-Instruct-v0.3Q4_K_M4.07 GiBMaziyarPanahi4.07 GiB-0.0%
Mistral-7B-Instruct-v0.3Q4_K_S3.86 GiBMaziyarPanahi3.86 GiB-0.0%
Mistral-7B-Instruct-v0.3Q5_K_M4.78 GiBMaziyarPanahi4.78 GiB-0.0%
Mistral-7B-Instruct-v0.3Q3_K_S2.95 GiBMaziyarPanahi2.95 GiB-0.0%
Mistral-7B-Instruct-v0.3Q5_K_S4.66 GiBMaziyarPanahi4.66 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
Mistral-7B-Instruct-v0.3172.54 GiB
gemma-2-9b-it173.54 GiB
granite-8b-code-base-4k172.85 GiB