Best LLMs for 48 GB VRAM
Professional / Apple Silicon (RTX 6000 Ada, L40S, MacBook Pro M4 Max 48GB) — 70B at Q4-Q5
With 48 GB of memory, this is a high-end configuration for local AI. You can comfortably run most open-source LLMs including large 70B parameter models at good quantization levels, making it one of the best setups for serious local AI work.
At this memory tier, nearly every popular open-source model is within reach. You can run Llama 3 70B at Q4_K_M or even Q5_K_M quantization with room to spare, handle coding assistants like DeepSeek Coder 33B at high quality, and easily run any 7B–30B model at full or near-full precision. Context windows remain generous even with larger models, so multi-turn conversations and long-document processing work smoothly.
Runs Well
- 70B models (Llama 3 70B, Qwen 72B) at Q4–Q5
- 30B models at Q6–Q8 quality
- 7B–14B models at full FP16 precision
- Vision models (LLaVA, CogVLM) without compromise
Challenging
- Mixture-of-experts models like Mixtral 8x22B at higher quants
- 120B+ models still require lower quantizations
GPUs with ~48.0 GB VRAM
AMD Radeon PRO W7900
AMD · RDNA 3
NVIDIA L40S
NVIDIA · Ada Lovelace
NVIDIA L40
NVIDIA · Ada Lovelace
NVIDIA A40
NVIDIA · Ampere
NVIDIA RTX 6000 Ada Generation
NVIDIA · Ada Lovelace
NVIDIA RTX A6000
NVIDIA · Ampere
Models That Fit in 48 GB VRAM
Speed estimated for NVIDIA RTX 6000 Ada Generation
| Model | Quant | VRAM | Speed | Context | Status | Grade |
|---|---|---|---|---|---|---|
| Q4_K_M | 5.4 GB11% | 116.2 t/s | 131K | EASY RUN | C31 | |
| Q4_K_M | 2.9 GB6% | 215.9 t/s | 41K | EASY RUN | D28 | |
| Q4_K_M | 5.4 GB11% | 115.8 t/s | 131K | EASY RUN | C31 | |
| Q8_0 | 4.9 GB10% | 127.1 t/s | 4K | EASY RUN | C30 | |
| Q4_K_M | 6.1 GB13% | 102.3 t/s | 8K | EASY RUN | C32 | |
| Q4_K_M | 5.0 GB10% | 125.1 t/s | 131K | EASY RUN | C30 | |
| Q4_K_M | 2.0 GB4% | 315.2 t/s | 131K | EASY RUN | D27 | |
| Q4_K_M | 2.6 GB6% | 236.4 t/s | 2K | EASY RUN | D28 |
Frequently Asked Questions
- What models can I run with 48.0 GB VRAM?
With 48.0 GB VRAM, you can run most 7B-30B models at good quality, and 70B models at lower quantizations.
- Is 48.0 GB enough for local AI?
48.0 GB is excellent for local AI. You can comfortably run a wide range of models from small 7B assistants to large 30B models. This is the enthusiast tier where most popular models work well.
- What GPU should I get for 48.0 GB VRAM?
There are several GPUs with approximately 48.0 GB VRAM at different price points. Popular choices include AMD Radeon PRO W7900, NVIDIA L40S, NVIDIA L40. Memory bandwidth also matters — higher bandwidth means faster token generation. Check the GPU cards above for specific specs and pricing.
- What quantization works best with 48.0 GB?
For 48.0 GB, Q4_K_M is typically the best starting quantization — it offers a good balance of model quality and VRAM usage. You can also try Q5_K_M or Q6_K for better quality with 7B models. Use Q2_K or Q3_K_M only when you need to squeeze in a model that's otherwise too large.