Source: https://getrigbase.com/models/qwen3-5-4b/ Last updated: 2026-11-01 [Models](https://getrigbase.com/models/) / Qwen3.5 4B # Best home rig for Qwen3.5 4B Quick answer **How much VRAM does Qwen3.5 4B need?** The weights are about 2.4 GB at Q4_K_M (4B params × 4.89 bits ÷ 8, before context/KV cache). Add memory for context (KV cache) and the runtime. The smallest-memory setup with a measured result here, fully in memory, is Apple M4 (16 GB) at 29.7 tok/s. **What is the fastest measured hardware for Qwen3.5 4B?** RTX 2060 Super 8 GB + Core i9-10900K: Qwen3.5 9B Q4_K_M at 54.4 tok/s, Gemma 4 12B at 27.7 (llama.cpp): 83.7 tok/s generation (llama.cpp server (CUDA, Docker), Q4_K_M), from https://mustafa.net/2026/10/13/local-llm-calculator-tested-four-machines/. Last updated: 1 Nov 2026 Legacy model 4B dense 2 measured results fastest plain decode: 83.7 tok/s [model info ↗](https://ollama.com/library/qwen3.5) Older model. For current picks see [current models](https://getrigbase.com/models/). Real, measured generation speeds for Qwen3.5 4B on home hardware, fastest first. Different quants/engines aren't directly comparable. | Build | Quant | Engine | tok/s | Prompt processing (tok/s) | Cost | Source | |---|---|---|---|---|---|---| | [RTX 2060 Super 8 GB + Core i9-10900K: Qwen3.5 9B Q4_K_M at 54.4 tok/s, Gemma 4 12B at 27.7 (llama.cpp)](https://getrigbase.com/builds/rtx-2060-super-8gb-i9-10900k-qwen35-gemma4-mustafa/) | Q4_K_M | llama.cpp server (CUDA, Docker) | **83.7** | – | | [mustafa.net ↗](https://mustafa.net/2026/10/13/local-llm-calculator-tested-four-machines/) | | [Mac mini M4 (16 GB): Qwen3.5 9B Q4_K_M at 17.7 tok/s, Gemma 4 12B at 13.1 (llama.cpp Metal)](https://getrigbase.com/builds/mac-mini-m4-16gb-qwen35-gemma4-mustafa/) | Q4_K_M | llama.cpp server (Metal) | **29.7** | – | | [mustafa.net ↗](https://mustafa.net/2026/10/13/local-llm-calculator-tested-four-machines/) | Prompt processing = prefill speed reported by the source, @ prompt length. * est. TTFT @8k is calculated from measured prefill, not measured. [Why it matters](https://getrigbase.com/can-it-run/#prefill). Ad · this space is available **Sponsor this spot: reach people building local AI rigs.** One clearly-labeled slot per page, no tracking scripts. [Sponsor this spot →](https://getrigbase.com/advertise/#inquiry) **Rent before you buy:** try this model on a cloud GPU for a few dollars first: [Runpod](https://runpod.io?ref=77qcpl2c) (referral link; sign up with Google to get the new-user bonus) ## Memory math: how much VRAM / RAM does Qwen3.5 4B need? Qwen3.5 4B has **4B parameters** ([source](https://ollama.com/library/qwen3.5): Ollama library tag 4b (nominal)). Weight size = parameters × bits-per-weight ÷ 8, before context (KV cache) and runtime overhead. | Format | Bits/weight | Weights | Smallest common memory size that holds the weights alone | |---|---|---|---| | Q8_0 | 8.50 | 4.3 GB | 8 GB | | Q6_K | 6.56 | 3.3 GB | 8 GB | | Q5_K_M | 5.70 | 2.9 GB | 8 GB | | Q4_K_M | 4.89 | **2.4 GB** | 8 GB | | Q3_K_M | 4.00 | 2.0 GB | 8 GB | | Q2_K | 3.16 | 1.6 GB | 8 GB | Bits-per-weight for GGUF quants are llama.cpp's own figures ([llama.cpp quantize README](https://github.com/ggml-org/llama.cpp/blob/master/tools/quantize/README.md)). "As measured" rows apply the source's stated bits-per-weight to the parameter count; real files differ slightly because some layers stay at higher precision. Try other combinations in the [VRAM calculator](https://getrigbase.com/can-it-run/). ## FAQ ### How much VRAM does Qwen3.5 4B need? The weights are about 2.4 GB at Q4_K_M (4B params × 4.89 bits ÷ 8, before context/KV cache). Add memory for context (KV cache) and the runtime. The smallest-memory setup with a measured result here, fully in memory, is Apple M4 (16 GB) at 29.7 tok/s. ### What is the fastest measured hardware for Qwen3.5 4B? RTX 2060 Super 8 GB + Core i9-10900K: Qwen3.5 9B Q4_K_M at 54.4 tok/s, Gemma 4 12B at 27.7 (llama.cpp): 83.7 tok/s generation (llama.cpp server (CUDA, Docker), Q4_K_M), from https://mustafa.net/2026/10/13/local-llm-calculator-tested-four-machines/. Related: [what GPU do you need for 2026 models](https://getrigbase.com/guides/what-gpu-for-qwen3-6-gemma-4-gpt-oss/) · [all builds](https://getrigbase.com/builds/)