GeForce RTX 4060
NVIDIA
CompatibleRuns Qwen3 8B Q4_K_M entirely in memory
Model · Alibaba Qwen
At Q4_K_M with an 8K context, Qwen3 8B needs about 6.9 GB: a GPU with 8 GB or more runs it entirely in VRAM.
Official specData updated 24 days agoSource: Hugging Face config.json + model card
| Quantization | File size | Memory needed | Minimum GPU memory | Quality |
|---|---|---|---|---|
| BF16 | 15.3 GB | ~18.1 GB | 20 GB | Reference (unquantized) |
| Q8_0 | 8.1 GB | ~10.5 GB | 11 GB | Near-lossless |
| Q6_K | 6.3 GB | ~8.6 GB | 10 GB | Near-lossless |
| Q5_K_M | 5.4 GB | ~7.7 GB | 10 GB | Very good |
| Q4_K_MMost used | 4.7 GB | ~6.9 GB | 8 GB | Good — the usual choice |
| IQ4_XS | 4.2 GB | ~6.5 GB | 8 GB | Good — the usual choice |
| Q3_K_M | 3.8 GB | ~6 GB | 8 GB | Noticeable loss |
| Q2_K | 3.1 GB | ~5.3 GB | 8 GB | Significant loss |
File sizes: not available until imported from the model repository. Memory = weights (estimated from bits per weight) + KV cache + runtime overhead + safety margin. (BF16 ≈ 16 bpw, Q8_0 ≈ 8.5 bpw, Q6_K ≈ 6.57 bpw, Q5_K_M ≈ 5.7 bpw, Q4_K_M ≈ 4.9 bpw, IQ4_XS ≈ 4.46 bpw, Q3_K_M ≈ 4 bpw, Q2_K ≈ 3.17 bpw)
Q4, Q5 or Q8: how to choose a quantization
| RTX 509032 GB · 64 GB RAM~6.9 GB · 161–256 tok/s estimate | Excellent |
|---|---|
| RTX 409024 GB · 64 GB RAM~6.9 GB · 107–157 tok/s estimate | Excellent |
| RTX 309024 GB · 64 GB RAM~6.9 GB · 101–147 tok/s estimate | Excellent |
| RX 7900 XTX24 GB · 64 GB RAM~7 GB · 84–131 tok/s estimate | Excellent |
| RTX 5060 Ti 16 GB16 GB · 64 GB RAM~6.9 GB · 54–74 tok/s estimate | Excellent |
| RTX 5070 Ti16 GB · 64 GB RAM~6.9 GB · 97–141 tok/s estimate | Excellent |
| RTX 508016 GB · 64 GB RAM~6.9 GB · 103–150 tok/s estimate | Excellent |
| RTX 4060 Ti 16 GB16 GB · 64 GB RAM~6.9 GB · 36–49 tok/s estimate | Excellent |
| RTX 4070 Ti SUPER16 GB · 64 GB RAM~6.9 GB · 77–109 tok/s estimate | Excellent |
| RX 9070 XT16 GB · 64 GB RAM~7 GB · 62–93 tok/s estimate | Excellent |
| RTX 3060 12 GB12 GB · 64 GB RAM~6.9 GB · 45–60 tok/s estimate | Excellent |
| RTX 407012 GB · 64 GB RAM~6.9 GB · 60–83 tok/s estimate | Excellent |
| RTX 507012 GB · 64 GB RAM~6.9 GB · 77–109 tok/s estimate | Excellent |
| RTX 40608 GB · 64 GB RAM~6.9 GB · 35–46 tok/s estimate | Compatible |
| M3 Ultra (80-core GPU) · 512 GBMac Studio~6.7 GB · 72–134 tok/s estimate | Excellent |
|---|---|
| M4 Max (40-core GPU) · 128 GBMacBook Pro 14, MacBook Pro 16~6.7 GB · 52–90 tok/s estimate | Excellent |
| M3 Max (40-core GPU) · 128 GBMacBook Pro 14, MacBook Pro 16~6.7 GB · 40–66 tok/s estimate | Excellent |
| M4 Pro (20-core GPU) · 64 GBMac mini, MacBook Pro 14~6.7 GB · 29–45 tok/s estimate | Excellent |
| M4 Max (32-core GPU) · 36 GBMacBook Pro 14, MacBook Pro 16~6.7 GB · 41–67 tok/s estimate | Excellent |
| M4 · 32 GBMacBook Air, MacBook Pro 14~6.7 GB · 14–20 tok/s estimate | Excellent |
| M5 · 32 GBMacBook Pro 14~6.7 GB · 17–25 tok/s estimate | Excellent |
| M3 · 24 GBMacBook Air, MacBook Pro 14~6.7 GB · 12–17 tok/s estimate | Excellent |
EstimateData updated 24 days agoSource: Run LLM Locally engine
The KV cache grows with context: at 32K it adds about 4.5 GB on top of the weights.
With under 8 GB of VRAM, use a smaller quantization or a smaller model of the same family.
Prices and links follow the market you choose.
NVIDIA
CompatibleRuns Qwen3 8B Q4_K_M entirely in memory
AMD
ExcellentRuns Qwen3 8B Q4_K_M entirely in memory
Unified memory PC
ExcellentRuns Qwen3 8B Q4_K_M entirely in memory
No current offer imported for this market: the link opens a marketplace search.