Can I Run Llama 3.3 on NVIDIA GeForce RTX 3080 (10GB)?
Written by Jakub Rusinowski · Last updated July 12, 2026
No — Llama 3.3 70B Instruct at Q2_K_XS (Tight) needs 23.7 GB at 8K context (20.2 GB weights + 3.5 GB KV cache/overhead), and the NVIDIA GeForce RTX 3080 (10GB)'s 10 GB leaves it ~13.7 GB short. The cheapest card that runs it is the NVIDIA GeForce RTX 5090 Laptop GPU (24 GB).
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NVIDIA GeForce RTX 3080 (10GB) Specs
| VRAM | 10 GB |
| Memory Bandwidth | 760 GB/s |
Llama 3.3 70B Instruct on the NVIDIA GeForce RTX 3080 (10GB): VRAM by quantization
| Quant | VRAM needed | Fits 10 GB? | Max context | Whole PC |
|---|---|---|---|---|
| F16 | 143.5 GB | ✗ No | — | — |
| Q8_0 | 77.9 GB | ✗ No | — | — |
| Q6_K | 60.9 GB | ✗ No | — | — |
| Q5_K_M | 53.1 GB | ✗ No | — | — |
| Q4_K_M | 45.7 GB | ✗ No | — | — |
| Q3_K_M | 33.3 GB | ✗ No | — | — |
| Q2_K | 26.5 GB | ✗ No | — | — |
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 Q2_K_XS (Tight) on the NVIDIA GeForce RTX 3080 (10GB): 8K 23.7 GB ✗ · 32K 31.7 GB ✗ · 128K 64 GB ✗. Past 8K 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 3.3 70B Instruct on 256 GB of system RAM, CPU only: runs, but too slowly to be worth it.
Why It Does Not Fit
Every Llama 3.3 variant requires more VRAM than the NVIDIA GeForce RTX 3080 (10GB) provides (10 GB).
Nearest GPU That Fits
NVIDIA GeForce RTX 5090 Laptop GPU (24 GB VRAM).
Llama 3.3 needs ~24 GB but this GPU has 10 GB. Rent a RTX 4090 (24 GB)-class GPU by the hour instead of buying one:
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FAQ
Will Llama 3.3 run on the NVIDIA GeForce RTX 3080 (10GB)?
No — Llama 3.3 70B Instruct at Q2_K_XS (Tight) needs 23.7 GB at 8K context (20.2 GB weights + 3.5 GB KV cache/overhead), and the NVIDIA GeForce RTX 3080 (10GB)'s 10 GB leaves it ~13.7 GB short. The cheapest card that runs it is the NVIDIA GeForce RTX 5090 Laptop GPU (24 GB).
What GPU should I get instead to run Llama 3.3?
The NVIDIA GeForce RTX 5090 Laptop GPU (24 GB VRAM) is the cheapest upgrade that fits it.
Llama 3.3 on Other GPUs
- Llama 3.3 on Intel Arc B570
- Llama 3.3 on NVIDIA GeForce RTX 5070
- Llama 3.3 on NVIDIA GeForce RTX 4070 Ti
Popular Models on the NVIDIA GeForce RTX 3080 (10GB)
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VRAM Tier
Troubleshooting
- CUDA out of memory — why it happens and how to fix it
- Which GGUF quant should I download? (Q4 vs Q5 vs Q8)
Buying Guide
← Can I Run It? | Llama 3.3 Model Page | NVIDIA GeForce RTX 3080 (10GB) GPU Page | VRAM calculator | Check Your Hardware