KV Cache Quantization: I Stretched Qwen 35B's Context 8 on 12GB VRAM

600 MiB of headroom My RTX 4070 was running Qwen 35B beautifully after the --cpu-moe trick from a previous run. The tokens/sec were where I wanted them. VRAM sat at 11,714 MiB out of 12,281 — 95% full. That leaves 600 MiB. Not enough for a serious agent. The context window I was giving llama.cpp was -c 4096 . Fine for chat. Not fine when a Claude Code-style agent hands the model 12,000 tokens of tool definitions before it says hello. I wanted -c 32768 . That's an 8× jump. And the memory that grows with context length is the KV cache. Multiply the cache by 8 with 600 MiB free, and llama.cpp dies during warm-up. I know because I tried it first. What actually sits on the GPU After offloading the MoE experts to CPU (the previous chapter's trick), the GPU is holding two things: The attention weights and non-MoE parameters The KV cache — a running record of every token the model has already read The first is fixed. The second grows linearly with context length. Double the context, double the cache. -c 4096 → -c 32768 doesn't just want 8× more tokens processed, it wants 8× more cache resident in VRAM the whole time. There is no room. So the cache itself has to shrink. Two flags llama.cpp takes two flags for KV cache dtype: llama-server -m qwen35.gguf -ngl 99 --cpu-moe -c 32768 \ -ctk q8_0 -ctv q8_0 -ctk is the Key cache, -ctv is the Value cache. Default is f16 (16-bit). q8_0 cuts each in half. Halving both means the KV cache footprint drops by roughly 50%. That freed-up VRAM is exactly what I need to make the context 8× bigger without touching the model weights. The measurement Same prompt, same seed, two runs — one at f16 KV, one at q8_0 KV: KV dtype Max -c I could allocate Tokens/sec (decode) Perplexity delta f16 (default) 4096 ~34.6 baseline q8_0 32768 ~34.1 negligible in my tests The speed loss is inside noise. The context is 8× longer. The quality drop I could not tell apart from run-to-run variance. Community measurements agree: symmetric q8_0 KV lands somewhere unde