Dev.to
7/28/2026

The headline needs to capture: KV cache quantization, Qwen 35B, 8x context, 12GB VRAM, and the key technique.
Original: KV Cache Quantization: I Stretched Qwen 35B's Context 8 on 12GB VRAM
Short summary
By quantizing the KV cache to q8_0 (halving its VRAM footprint) and offloading MoE experts to CPU, you can run Qwen 35B with 8× longer context (32k vs 4k) on a 12GB RTX 4070 with negligible speed or quality loss. The author benchmarks f16 vs q8_0 KV cache, showing identical decode speed and imperceptible perplexity delta. Three flags (--cpu-moe -ctk q8_0 -ctv q8_0) unlock agent-grade context windows on consumer hardware.
- •q8_0 KV cache halves VRAM usage with no measurable quality or speed regression
- •Three flags enable 32k context on 12GB VRAM for agent workloads
- •Context size should be tiered by workload: 4k for chat, 8k for light agents, 32k for heavy multi-tool agents
Generated with AI, which can make mistakes.
Is this a good recommendation for you?



