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Kandinsky-6.0-Pro-distill-5s-Diffusers

kandinskylab · on Arena since 9 Sept 2026

Download New · waiting for Arena votes
Arena score—Not voted on Arena yet
Size30.1 Bparameters
4-bit download18 GBweights only, Q4_K_M
Max context—

Where to use it for free

New: waiting for Arena votes

Released on 9 Sept 2026. Arena has not voted on this model yet. As soon as it does, the model moves into the ranking automatically, usually the next night. Until then you can still check its size, memory needs and speed below.

Speed on popular hardware

HardwareGPU memoryFits?Speed
RTX 3060 12 GB12 GBGPU + 64 GB RAM5.4 tok/s
RTX 4060 Ti 16 GB16 GBGPU + 64 GB RAM6.1 tok/s
RTX 309024 GBFits in GPU30 tok/s
RTX 409024 GBFits in GPU32 tok/s
RTX 509032 GBFits in GPU57 tok/s
RX 7900 XTX24 GBFits in GPU30 tok/s
2 × RTX 309048 GBFits in GPU29 tok/s
4 × RTX 309096 GBFits in GPU27 tok/s
Mac M4 Max 128 GB96 GBFits in GPU17 tok/s
Ryzen AI Max+ 395 128 GB96 GBFits in GPU8.1 tok/s
8 × H100 SXM640 GBFits in GPU87 tok/s

Estimate at 4-bit with 32K context, 64 GB of DDR5 for offload. Speed ≈ memory bandwidth × 70% ÷ data read per token; real numbers vary by about ±30%.

GPU memory needed

Level8K context32K context128K contextQuality vs full
Q3_K_M17 GB20 GB31 GB+7.0% noticeable loss
Q4_K_M20 GB23 GB35 GB+1.8% small loss
Q5_K_M23 GB26 GB38 GB+0.6% near-lossless
Q6_K26 GB29 GB41 GB+0.2% near-lossless
Q8_034 GB37 GB48 GB≈ 0% same as full
F1662 GB65 GB77 GB≈ 0% same as full

Weights + context cache (from the model's architecture) + runtime. Quality: increase in perplexity against the full model, from llama.cpp tests, scaled by model size. Simulate your own setup.