Qwen3.5-4B requirements — can you run it?
~4.2B parameters · 22 quantizations measured · updated 2026-03-02 · source: unsloth/Qwen3.5-4B-GGUF
Every quantization: real file size vs what you actually need
| Quant | File (measured) | VRAM/RAM needed (8K ctx) | Runs on (first fit) |
|---|---|---|---|
| UD-IQ2_XXS | 1.5 GB | 3.3 GB | RTX 3060 12GB |
| UD-IQ2_M | 1.8 GB | 3.6 GB | RTX 3060 12GB |
| UD-Q2_K_XL | 1.9 GB | 3.8 GB | RTX 3060 12GB |
| UD-IQ3_XXS | 1.9 GB | 3.8 GB | RTX 3060 12GB |
| Q3_K_S | 2.1 GB | 4.0 GB | RTX 3060 12GB |
| Q3_K_M | 2.3 GB | 4.3 GB | RTX 3060 12GB |
| UD-Q3_K_XL | 2.4 GB | 4.4 GB | RTX 3060 12GB |
| IQ4_XS | 2.5 GB | 4.5 GB | RTX 3060 12GB |
| IQ4_NL | 2.6 GB | 4.6 GB | RTX 3060 12GB |
| Q4_0 | 2.6 GB | 4.6 GB | RTX 3060 12GB |
| Q4_K_S | 2.6 GB | 4.6 GB | RTX 3060 12GB |
| Q4_K_M | 2.7 GB | 4.8 GB | RTX 3060 12GB |
| Q4_1 | 2.8 GB | 4.8 GB | RTX 3060 12GB |
| UD-Q4_K_XL | 2.9 GB | 5.0 GB | RTX 3060 12GB |
| Q5_K_S | 3.0 GB | 5.1 GB | RTX 3060 12GB |
| Q5_K_M | 3.1 GB | 5.3 GB | RTX 3060 12GB |
| UD-Q5_K_XL | 3.3 GB | 5.4 GB | RTX 3060 12GB |
| Q6_K | 3.5 GB | 5.7 GB | RTX 3060 12GB |
| UD-Q6_K_XL | 4.1 GB | 6.5 GB | RTX 3060 12GB |
| Q8_0 | 4.5 GB | 6.9 GB | RTX 3060 12GB |
| UD-Q8_K_XL | 6.0 GB | 8.6 GB | RTX 3060 12GB |
| BF16 | 8.4 GB | 11.6 GB | RTX 4060 Ti 16GB |
KV cache uses a flat +20% context/overhead rule because this repo does not publish its config; exact numbers may differ for long contexts. MoE models keep all experts in memory — total size counts, not just active params.
Can I run Qwen3.5-4B on my GPU? (UD-IQ2_XXS recommended quant)
| Hardware | Memory | Verdict |
|---|---|---|
| RTX 3060 12GB | 12 GB | RUNS |
| RTX 4060 Ti 16GB | 16 GB | RUNS |
| RTX 3090 24GB | 24 GB | RUNS |
| RTX 4090 24GB | 24 GB | RUNS |
| RTX 5090 32GB | 32 GB | RUNS |
| RTX PRO 6000 96GB | 96 GB | RUNS |
| Mac 16GB unified | 16 GB | RUNS |
| Mac 32GB unified | 32 GB | RUNS |
| Mac 64GB unified | 64 GB | RUNS |
| Mac 128GB unified | 128 GB | RUNS |
| Mac 256GB unified | 256 GB | RUNS |
| Mac 512GB unified | 512 GB | RUNS |
| 32GB system RAM (CPU) | 32 GB | RUNS |
| 64GB system RAM (CPU) | 64 GB | RUNS |
| 128GB system RAM (CPU) | 128 GB | RUNS |
| 256GB system RAM (CPU) | 256 GB | RUNS |
| 1TB server RAM (CPU) | 1024 GB | RUNS |
| 2TB server RAM (CPU) | 2048 GB | RUNS |
How much VRAM does Qwen3.5-4B need?
The honest answer: 3.3 GB at the UD-IQ2_XXS quant with 8K context — that is the measured file size (1.5 GB) plus KV cache and runtime overhead. The smallest published build needs 3.3 GB; the lossless one needs 11.6 GB.
Can I run it with CPU offload?
Yes, if combined RAM+VRAM ≥ file size — but generation speed is limited by memory bandwidth. Expect roughly: DDR5 dual channel ~10-30 tok/s for small MoE actives, single digits for big ones, 0.1-1 tok/s when experts page from disk. CPU-only is fine for batch jobs, painful for chat.
Why do other sites show different numbers?
Most pages compute weights from a formula (params × bits/8). We use the actual file sizes published in GGUF repos, which include the embedding table, unquantized tensors, and container overhead — that is why our numbers can differ from a naive calculation.
FAQ
How much VRAM does Qwen3.5-4B need?
The measured answer: 3.3 GB at the UD-IQ2_XXS quant with 8K context. The smallest published build needs 3.3 GB; the lossless (F16/BF16) build needs 11.6 GB. These are real GGUF file sizes from Hugging Face, not formula estimates.
Can I run Qwen3.5-4B on a 24GB GPU (RTX 3090/4090)?
Yes — at UD-IQ2_XXS (3.3 GB). Quants that fit 24GB: UD-IQ2_XXS, UD-IQ2_M, UD-Q2_K_XL, UD-IQ3_XXS, Q3_K_S, Q3_K_M, UD-Q3_K_XL, IQ4_XS, IQ4_NL, Q4_0, Q4_K_S, Q4_K_M, Q4_1, UD-Q4_K_XL, Q5_K_S, Q5_K_M, UD-Q5_K_XL, Q6_K, UD-Q6_K_XL, Q8_0, UD-Q8_K_XL, BF16.
Can I run Qwen3.5-4B on CPU with system RAM?
Yes, if your usable RAM is at least the file size. At UD-IQ2_XXS you need ~3.3 GB of RAM. CPU generation is memory-bandwidth-bound: expect single-digit tok/s for large MoE models, 10-30 tok/s for small active params, and below 1 tok/s when experts page from disk.
Why do VRAM numbers for Qwen3.5-4B differ between sites?
Most sites compute weights from a formula (params x bits/8). ModelFit uses the actual GGUF file sizes published on Hugging Face, which include the embedding table, unquantized tensors, and container overhead — so our numbers reflect what you really download and load.