Quantization publisher

unsloth

unsloth publishes 4,573 quantizations across 248 models in our index, averaging 5.207 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
263
Quantizations
4,573
Models covered
248
Avg effective bpw
5.207
across their files

Same model, same quant label, different bytes

largest disagreements first
ModelQuantunslothvsTheirsDifference
Kimi-K2.5Q6_K785.02 GiBbartowski542.20 GiB+44.8%
InklingQ8_0797.92 GiBAtomicChat937.42 GiB-14.9%
Kimi-K2.5Q5_K_M678.69 GiBbartowski541.32 GiB+25.4%
Kimi-K2.5Q5_K_S658.45 GiBbartowski540.65 GiB+21.8%
Kimi-K2.5Q4_K_M578.58 GiBbartowski540.50 GiB+7.0%
GLM-4.6Q6_K272.97 GiBReadyArt248.62 GiB+9.8%
Kimi-K2.5Q3_K_M456.14 GiBbartowski435.23 GiB+4.8%
Qwen3.5-397B-A17BQ6_K304.17 GiBbartowski324.92 GiB-6.4%
FLUX.2-devQ8_032.60 GiBgguf-org51.67 GiB-36.9%
MiniMax-H3Q5_025.90 GiBAbiray42.43 GiB-39.0%
Qwen3.5-397B-A17BQ3_K_S153.04 GiBbartowski167.58 GiB-8.7%
Kimi-K2.5Q2_K348.11 GiBbartowski334.01 GiB+4.2%
GLM-4.6IQ4_XS177.59 GiBReadyArt163.75 GiB+8.5%
Kimi-K2.5Q2_K_L348.36 GiBbartowski335.08 GiB+4.0%
DeepSeek-R1-0528Q4_K_S354.38 GiBbartowski367.08 GiB-3.5%
Mistral-Large-3-675B-Instruct-2512Q4_K_S356.38 GiBbartowski368.91 GiB-3.4%
DeepSeek-V3.1-TerminusQ4_K_S354.89 GiBbartowski367.08 GiB-3.3%
DeepSeek-V3.1Q4_K_S354.89 GiBbartowski367.08 GiB-3.3%
DeepSeek-V3.1Q3_K_M298.44 GiBbartowski286.78 GiB+4.1%
DeepSeek-V3.1-TerminusQ3_K_M298.44 GiBbartowski286.78 GiB+4.1%
FLUX.2-devQ4_017.97 GiBgguf-org29.28 GiB-38.6%
Mistral-Large-3-675B-Instruct-2512Q3_K_M299.74 GiBbartowski288.62 GiB+3.9%
DeepSeek-R1-0528Q3_K_M297.88 GiBbartowski286.78 GiB+3.9%
Qwen3.5-397B-A17BQ4_K_S212.33 GiBbartowski223.12 GiB-4.8%
Qwen3-Coder-480B-A35B-InstructQ3_K_M213.50 GiBbartowski203.44 GiB+4.9%

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
Qwen3-Coder-30B-A3B-Instruct427.46 GiB
Qwen3.6-27B328.74 GiB
Qwen3.6-35B-A3B319.36 GiB
Qwen3.8-27B168.39 GiB
Qwen3.5-9B312.97 GiB
gemma-4-26B-A4B-it149.24 GiB
gemma-4-12B-it153.92 GiB
DeepSeek-V4-Flash976.87 GiB
Qwen3.5-4B311.42 GiB
MiniMax-H3812.20 GiB
gemma-4-E4B-it153.30 GiB
Qwen3-30B-A3B-Thinking-2507217.59 GiB
gemma-4-31B-it167.95 GiB
Muse-Glimmer-30B910.01 GiB
Qwen3-4B201.01 GiB
FLUX.2-klein-9B153.71 GiB
Qwen3-8B192.12 GiB
Qwen3.5-122B-A10B3131.87 GiB
DeepSeek-V4-Flash-0731976.87 GiB
Qwen3.5-0.8B160.31 GiB
Llama-3.2-1B-Instruct210.39 GiB
Qwen-AgentWorld-35B-A3B1410.71 GiB
gemma-4-E2B-it152.13 GiB
gpt-oss-20b1310.68 GiB
LTX-2.3637.39 GiB
Qwen3-VL-30B-A3B-Instruct217.60 GiB
Qwen3-30B-A3B208.42 GiB
Laguna-S-2.11631.45 GiB
Qwen3.5-35B-A3B179.93 GiB
Llama-3.1-8B-Instruct192.02 GiB