Model comparison

Qwen3-Coder-30B-A3B-Instruct vs DeepSeek-V2-Lite-Chat-Uncensored-Unbiased-Reasoner

At Q4_K_M, DeepSeek-V2-Lite-Chat-Uncensored-Unbiased-Reasoner is the smaller download — 10,361,112,672 bytes against 18,556,689,568. At long context the gap widens: DeepSeek-V2-Lite-Chat-Uncensored-Unbiased-Reasoner's KV cache at 32K is 3.2× smaller, which usually matters more than the difference in weights.

From the file· summed bytes, KV per layer

Side by side

Qwen3-Coder-30B-A3B-InstructDeepSeek-V2-Lite-Chat-Uncensored-Unbiased-Reasoner
Parameters30.5B15.7B
Architectureqwen3moedeepseek2
Layers4827
Native context262,1444,096
Mixture of expertsyes, 128 expertsyes, 64 experts
Quantizations published4612
Smallest quantization7.46 GiB5.99 GiB
Q4_K_M17.28 GiB9.65 GiB
Licenceapache-2.0llama3.3

KV cache by context

the term that decides long-context viability
ContextQwen3-Coder-30B-A3B-InstructDeepSeek-V2-Lite-Chat-Uncensored-Unbiased-ReasonerRatio
4,0960.38 GiB0.12 GiB3.16×
8,1920.75 GiB0.24 GiB3.16×
16,3841.50 GiB0.47 GiB3.16×
32,7683.00 GiB0.95 GiB3.16×
65,5366.00 GiB1.90 GiB3.16×
131,07212.00 GiB3.80 GiB3.16×