Can I Run Llama 3.2 Vision on NVIDIA GeForce RTX 3080 (10GB)?
Autor: Jakub Rusinowski · Ostatnia aktualizacja: 12 lipca 2026
Yes, comfortably — Llama 3.2 Vision 11B at Q4_K_M needs 8.5 GB at 8K context (6.4 GB weights + 2.1 GB KV cache/overhead), leaving ~1.5 GB of the NVIDIA GeForce RTX 3080 (10GB)'s 10 GB, at ~58 tok/s (est.), with room for up to 16K context.
See what else this hardware can run →
lub porównaj w Vast.ai od $0.35/godz. (typical low · varies)
Jako partner Amazon zarabiamy na kwalifikujących się zakupach. Linki do chmurowych GPU są linkami polecającymi — możemy otrzymać prowizję bez dodatkowych kosztów dla Ciebie.
NVIDIA GeForce RTX 3080 (10GB) Specs
| VRAM | 10 GB |
| Memory Bandwidth | 760 GB/s |
Llama 3.2 Vision 11B on the NVIDIA GeForce RTX 3080 (10GB): VRAM by quantization
| Quant | VRAM needed | Fits 10 GB? | Max context | Whole PC |
|---|---|---|---|---|
| F16 | 23.3 GB | ✗ No | — | — |
| Q8_0 | 13.4 GB | ✗ No | — | — |
| Q6_K | 10.8 GB | ✗ No | — | — |
| Q5_K_M | 9.7 GB | ✓ Yes | 8K | — |
| Q4_K_M | 8.5 GB | ✓ Yes | 16K | — |
| Q3_K_M | 6.7 GB | ✓ Yes | 16K | — |
| Q2_K | 5.6 GB | ✓ Yes | 32K | — |
Assumes an 8K-token context with an f16 KV cache. A longer window needs more; a quantized KV cache needs less. “Max context” is the largest window that still fits in 10 GB. Figures are estimates from parameter count, quantization and memory bandwidth — the analyzer lets you tune KV-cache quant and context.
Context costs VRAM too. At Q4_K_M on the NVIDIA GeForce RTX 3080 (10GB): 8K 8.5 GB · 32K 12.6 GB ✗ · 125K 28.2 GB ✗. Past 32K it no longer fits 10 GB — a q8_0 KV cache buys roughly half of that back, which the calculator will price for you.
No compatible GPU? Llama 3.2 Vision 11B on 8 GB of system RAM, CPU only: runs.
Llama 3.2 Vision Sizes That Fit the NVIDIA GeForce RTX 3080 (10GB) (at 8K context)
| Llama 3.2 Vision 11B | Q4_K_M · 8.5 GB at 8K context · ~58 tok/s (est.) |
At 2 hrs/day, buying (~$699) beats renting at $0.34/hr after about 2.9 years.
Affiliate links — we may earn a commission if you sign up, at no extra cost to you.
Cloud rates verified 2026-07 — estimates, and marketplace prices vary. Buying price is GPU MSRP only, not a full PC.
FAQ
Will Llama 3.2 Vision run on the NVIDIA GeForce RTX 3080 (10GB)?
Yes, comfortably — Llama 3.2 Vision 11B at Q4_K_M needs 8.5 GB at 8K context (6.4 GB weights + 2.1 GB KV cache/overhead), leaving ~1.5 GB of the NVIDIA GeForce RTX 3080 (10GB)'s 10 GB, at ~58 tok/s (est.), with room for up to 16K context.
Which Llama 3.2 Vision variant fits best on the NVIDIA GeForce RTX 3080 (10GB)?
Llama 3.2 Vision 11B at Q4_K_M quantization needs 8.5 GB at 8K context (6.4 GB weights + 2.1 GB KV cache/overhead), estimated ~58 tokens/sec, up to 16K context.
Every Llama 3.2 Vision size on the NVIDIA GeForce RTX 3080 (10GB)
| Size | VRAM at 8K | Verdict | Speed |
|---|---|---|---|
| Llama 3.2 Vision 90B | 57.8 GB | Does not fit | — |
| Llama 3.2 Vision 11B | 8.5 GB | Runs | ~58 tok/s |
Llama 3.2 Vision on Other GPUs
- Llama 3.2 Vision on Intel Arc B570
- Llama 3.2 Vision on NVIDIA GeForce RTX 5070
- Llama 3.2 Vision on NVIDIA GeForce RTX 5060 Ti 8GB
- Llama 3.2 Vision on NVIDIA GeForce RTX 5060
- Llama 3.2 Vision on NVIDIA GeForce RTX 4070 Ti
Popular Models on the NVIDIA GeForce RTX 3080 (10GB)
- DeepSeek R1 on NVIDIA GeForce RTX 3080 (10GB)
- Qwen 3 on NVIDIA GeForce RTX 3080 (10GB)
- Qwen 2.5 Family on NVIDIA GeForce RTX 3080 (10GB)
VRAM Tier
Troubleshooting
Buying Guide
← Can I Run It? | Llama 3.2 Vision Model Page | NVIDIA GeForce RTX 3080 (10GB) GPU Page | VRAM calculator | Check Your Hardware