Quantization publisher

NousResearch

NousResearch publishes 61 quantizations across 7 models in our index, averaging 5.506 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
8
Quantizations
61
Models covered
7
Avg effective bpw
5.506
across their files

Same model, same quant label, different bytes

largest disagreements first
ModelQuantNousResearchvsTheirsDifference
Mistral-7B-v0.1Q8_07.17 GiBbartowski10.62 GiB-32.5%
Mistral-7B-v0.1Q8_07.17 GiBbartowski10.62 GiB-32.5%
Mistral-7B-v0.1Q6_K5.53 GiBbartowski8.20 GiB-32.5%
Mistral-7B-v0.1Q6_K5.53 GiBbartowski8.20 GiB-32.5%
Mistral-7B-v0.1Q5_K_M4.78 GiBbartowski7.08 GiB-32.5%
Mistral-7B-v0.1Q5_K_M4.78 GiBbartowski7.08 GiB-32.5%
Mistral-7B-v0.1Q5_K_S4.65 GiBbartowski6.89 GiB-32.4%
Mistral-7B-v0.1Q5_04.65 GiBbartowski6.89 GiB-32.4%
Mistral-7B-v0.1Q5_04.65 GiBbartowski6.89 GiB-32.4%
Mistral-7B-v0.1Q5_K_S4.65 GiBbartowski6.89 GiB-32.4%
Mixtral-8x7B-v0.1Q3_K_M21.00 GiBTheBloke18.96 GiB+10.7%
Mistral-7B-v0.1Q4_K_M4.07 GiBbartowski6.02 GiB-32.4%
Mistral-7B-v0.1Q4_K_M4.07 GiBbartowski6.02 GiB-32.4%
Mixtral-8x7B-v0.1Q4_K_M26.49 GiBTheBloke24.63 GiB+7.6%
Mistral-7B-v0.1Q4_K_S3.86 GiBbartowski5.70 GiB-32.3%
Mistral-7B-v0.1Q4_K_S3.86 GiBbartowski5.70 GiB-32.3%
Mistral-7B-v0.1Q4_03.83 GiBbartowski5.66 GiB-32.3%
Mistral-7B-v0.1Q4_03.83 GiBbartowski5.66 GiB-32.3%
Mistral-7B-v0.1Q3_K_L3.56 GiBbartowski5.26 GiB-32.4%
Mistral-7B-v0.1Q3_K_L3.56 GiBbartowski5.26 GiB-32.4%
Mistral-7B-v0.1Q3_K_M3.28 GiBbartowski4.84 GiB-32.3%
Mistral-7B-v0.1Q3_K_M3.28 GiBbartowski4.84 GiB-32.3%
Mixtral-8x7B-v0.1Q2_K16.12 GiBTheBloke14.57 GiB+10.6%
Mistral-7B-v0.1Q3_K_S2.95 GiBbartowski4.34 GiB-32.2%
Mistral-7B-v0.1Q3_K_S2.95 GiBbartowski4.34 GiB-32.2%

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
Llama-3.1-8B44.58 GiB
Mistral-7B-v0.1242.53 GiB
Seed-OSS-36B-Base516.41 GiB
Llama-3.1-70B728.79 GiB
Mixtral-8x7B-v0.11216.12 GiB
Meta-Llama-3.2-3B41.88 GiB
Meta-Llama-3-8B54.58 GiB