Autor: Jakub Rusinowski · Ostatnia aktualizacja: 12 lipca 2026
Yes, comfortably — you'll have ~3.9 GB of headroom running InternLM 3 20B Instruct at Q4_K_M (12.075 GB, ~28 tok/s (est.)) with room for up to 8K context.
or compare on Vast.ai from $0.35/hr (typical low · varies)
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| VRAM | 16 GB |
| Memory Bandwidth | 448 GB/s |
| Quant | VRAM needed | Fits 16 GB? | Max context |
|---|---|---|---|
| F16 | 41.6 GB | ✗ No | — |
| Q8_0 | 22.8 GB | ✗ No | — |
| Q6_K | 18 GB | ✗ No | — |
| Q5_K_M | 15.8 GB | ✓ Yes | 4K |
| Q4_K_M | 13.7 GB | ✓ Yes | 8K |
| Q3_K_M | 10.1 GB | ✓ Yes | 32K |
| Q2_K | 8.2 GB | ✓ Yes | 32K |
VRAM needed assumes a 4K-token context with an f16 KV cache; “Max context” is the largest window that still fits in 16 GB. Figures are estimates from parameter count, quantization and memory bandwidth — the analyzer lets you tune KV-cache quant and context.
| InternLM 3 20B Instruct | Q4_K_M · 12.075 GB · ~28 tok/s (est.) |
| InternLM 3 8B Instruct | Q4_K_M · 5.313000000000001 GB · ~60 tok/s (est.) |
At 2 hrs/day, buying (~$429) beats renting at $0.34/hr after about 21 months.
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Cloud rates verified 2026-07 — estimates, and marketplace prices vary. Buying price is GPU MSRP only, not a full PC.
Yes, comfortably — you'll have ~3.9 GB of headroom running InternLM 3 20B Instruct at Q4_K_M (12.075 GB, ~28 tok/s (est.)) with room for up to 8K context.
InternLM 3 20B Instruct at Q4_K_M quantization (12.075 GB), estimated ~28 tokens/sec, up to 8K context.
| Size | VRAM | Verdict | Speed |
|---|---|---|---|
| InternLM 3 20B Instruct | 12.1 GB | Runs | ~28 tok/s |
| InternLM 3 8B Instruct | 5.3 GB | Runs | ~60 tok/s |
← Can I Run It? | InternLM 3 Model Page | NVIDIA GeForce RTX 5060 Ti 16GB GPU Page | Check Your Hardware