Minimum VRAM
16GB
FP16 (full model) • Q4 option ≈ 4GB
Best Performance
AMD Instinct MI300X
~290 tok/s • FP16
Most Affordable
RX 7600 XT
FP16 • ~17 tok/s • From $329
Quick answer: Nousresearch Hermes 3 Llama 3 1 8B needs roughly 4GB VRAM for Q4_K_M and 6GB for Q5_K_M. Use Q8 (8GB) or FP16 (16GB) for higher quality output.
Full-model (FP16) requirements are shown by default. Quantized builds like Q4 trade accuracy for lower VRAM usage.
Ready to buy?
See our tested GPU picks for running Nousresearch Hermes 3 Llama 3 1 8B locally.
Best GPU for Running LLMs →Filter by quantization, price, and VRAM to compare performance estimates.
Showing FP16 compatibility. Switch tabs to explore other quantizations.
| GPU | Speed | VRAM Requirement | Typical price |
|---|---|---|---|
AMD Instinct MI300XEstimated AMD | ~290 tok/s FP16 | 16GB VRAM used192GB total on card | $15,000View GPU → |
NVIDIA H200 SXM 141GBEstimated NVIDIA | ~262 tok/s FP16 | 16GB VRAM used141GB total on card | $35,000View GPU → |
NVIDIA H100 SXM5 80GBEstimated NVIDIA | ~188 tok/s FP16 | 16GB VRAM used80GB total on card | $30,000View GPU → |
AMD Instinct MI250XEstimated AMD | ~181 tok/s FP16 | 16GB VRAM used128GB total on card | $11,000View GPU → |
NVIDIA H100 PCIe 80GBEstimated NVIDIA | ~119 tok/s FP16 | 16GB VRAM used80GB total on card | $25,000View GPU → |
RTX 5090Estimated NVIDIA | ~114 tok/s FP16 | 16GB VRAM used32GB total on card | $1,999View GPU → |
NVIDIA A100 80GB SXM4Estimated NVIDIA | ~111 tok/s FP16 | 16GB VRAM used80GB total on card | $11,000View GPU → |
AMD Instinct MI210Estimated AMD | ~90 tok/s FP16 | 16GB VRAM used64GB total on card | $6,000View GPU → |
NVIDIA A100 40GB PCIeEstimated NVIDIA | ~86 tok/s FP16 | 16GB VRAM used40GB total on card | $9,000View GPU → |
RTX 4090Estimated NVIDIA | ~68 tok/s FP16 | 16GB VRAM used24GB total on card | $1,599View GPU → |
NVIDIA RTX 6000 AdaEstimated NVIDIA | ~68 tok/s FP16 | 16GB VRAM used48GB total on card | $6,999View GPU → |
NVIDIA L40Estimated NVIDIA | ~63 tok/s FP16 | 16GB VRAM used48GB total on card | $7,999View GPU → |
NVIDIA L40SEstimated NVIDIA | ~63 tok/s FP16 | 16GB VRAM used48GB total on card | $10,000View GPU → |
RTX 5080Tight VRAM NVIDIA | ~60 tok/s FP16 | 16GB VRAM used16GB total on card | $1,199View GPU → |
RTX 3090Estimated NVIDIA | ~59 tok/s FP16 | 16GB VRAM used24GB total on card | $1,499View GPU → |
RX 7900 XTXEstimated AMD | ~55 tok/s FP16 | 16GB VRAM used24GB total on card | $999View GPU → |
AMD Radeon Pro W7900Estimated AMD | ~55 tok/s FP16 | 16GB VRAM used48GB total on card | $3,999View GPU → |
RTX 5070 TiTight VRAM NVIDIA | ~55 tok/s FP16 | 16GB VRAM used16GB total on card | $799View GPU → |
NVIDIA A6000Estimated NVIDIA | ~50 tok/s FP16 | 16GB VRAM used48GB total on card | $4,699View GPU → |
RTX 4080 SuperTight VRAM NVIDIA | ~48 tok/s FP16 | 16GB VRAM used16GB total on card | $999View GPU → |
RTX 3080Estimated NVIDIA | ~48 tok/s FP16⚠ Insufficient VRAM | 16GB VRAM used10GB total on card | $699View GPU → |
NVIDIA A5000Estimated NVIDIA | ~48 tok/s FP16 | 16GB VRAM used24GB total on card | $2,399View GPU → |
RTX 4080Tight VRAM NVIDIA | ~47 tok/s FP16 | 16GB VRAM used16GB total on card | $1,199View GPU → |
RX 7900 XTEstimated AMD | ~46 tok/s FP16 | 16GB VRAM used20GB total on card | $899View GPU → |
RTX 4070 Ti SuperTight VRAM NVIDIA | ~43 tok/s FP16 | 16GB VRAM used16GB total on card | $799View GPU → |
RTX 5070Estimated NVIDIA | ~41 tok/s FP16⚠ Insufficient VRAM | 16GB VRAM used12GB total on card | $599View GPU → |
Apple M2 UltraEstimated Apple | ~41 tok/s FP16 | 16GB VRAM used192GB total on card | $5,999View GPU → |
RX 9070 XTTight VRAM AMD | ~37 tok/s FP16 | 16GB VRAM used16GB total on card | $599View GPU → |
RX 7800 XTTight VRAM AMD | ~36 tok/s FP16 | 16GB VRAM used16GB total on card | $499View GPU → |
RX 7900 GRETight VRAM AMD | ~35 tok/s FP16 | 16GB VRAM used16GB total on card | $649View GPU → |
AMD Radeon Pro W7800Estimated AMD | ~34 tok/s FP16 | 16GB VRAM used32GB total on card | $2,499View GPU → |
RTX 4070 TiEstimated NVIDIA | ~34 tok/s FP16⚠ Insufficient VRAM | 16GB VRAM used12GB total on card | $799View GPU → |
RTX 4070 SuperEstimated NVIDIA | ~33 tok/s FP16⚠ Insufficient VRAM | 16GB VRAM used12GB total on card | $599View GPU → |
RX 9070Tight VRAM AMD | ~33 tok/s FP16 | 16GB VRAM used16GB total on card | $499View GPU → |
Intel Arc A770 16GBTight VRAM Intel | ~33 tok/s FP16 | 16GB VRAM used16GB total on card | $349View GPU → |
RTX 4070Estimated NVIDIA | ~32 tok/s FP16⚠ Insufficient VRAM | 16GB VRAM used12GB total on card | $599View GPU → |
RX 6900 XTTight VRAM AMD | ~31 tok/s FP16 | 16GB VRAM used16GB total on card | $999View GPU → |
RX 6800 XTTight VRAM AMD | ~31 tok/s FP16 | 16GB VRAM used16GB total on card | $649View GPU → |
Intel Arc A750Tight VRAM Intel | ~30 tok/s FP16⚠ Insufficient VRAM | 16GB VRAM used8GB total on card | $289View GPU → |
NVIDIA A4000Tight VRAM NVIDIA | ~29 tok/s FP16 | 16GB VRAM used16GB total on card | $999View GPU → |
RTX 3070Tight VRAM NVIDIA | ~29 tok/s FP16⚠ Insufficient VRAM | 16GB VRAM used8GB total on card | $499View GPU → |
Intel Arc B580Estimated Intel | ~29 tok/s FP16⚠ Insufficient VRAM | 16GB VRAM used12GB total on card | $249View GPU → |
Apple M4 MaxEstimated Apple | ~28 tok/s FP16 | 16GB VRAM used128GB total on card | $3,999View GPU → |
RX 7700 XTEstimated AMD | ~26 tok/s FP16⚠ Insufficient VRAM | 16GB VRAM used12GB total on card | $449View GPU → |
Intel Arc B570Estimated Intel | ~24 tok/s FP16⚠ Insufficient VRAM | 16GB VRAM used10GB total on card | $219View GPU → |
Intel Arc Pro A60Estimated Intel | ~23 tok/s FP16⚠ Insufficient VRAM | 16GB VRAM used12GB total on card | $599View GPU → |
NVIDIA L4Estimated NVIDIA | ~23 tok/s FP16 | 16GB VRAM used24GB total on card | $5,000View GPU → |
RTX 3060 12GBEstimated NVIDIA | ~22 tok/s FP16⚠ Insufficient VRAM | 16GB VRAM used12GB total on card | $329View GPU → |
Apple M3 MaxEstimated Apple | ~20 tok/s FP16 | 16GB VRAM used128GB total on card | $3,999View GPU → |
Apple M2 MaxEstimated Apple | ~20 tok/s FP16 | 16GB VRAM used96GB total on card | $3,199View GPU → |
RTX 4060 Ti 8GBTight VRAM NVIDIA | ~19 tok/s FP16⚠ Insufficient VRAM | 16GB VRAM used8GB total on card | $399View GPU → |
RTX 4060 Ti 16GBTight VRAM NVIDIA | ~19 tok/s FP16 | 16GB VRAM used16GB total on card | $499View GPU → |
RTX 4060Tight VRAM NVIDIA | ~17 tok/s FP16⚠ Insufficient VRAM | 16GB VRAM used8GB total on card | $299View GPU → |
Intel Arc Pro A40Estimated Intel | ~17 tok/s FP16⚠ Insufficient VRAM | 16GB VRAM used6GB total on card | $399View GPU → |
RX 7600Tight VRAM AMD | ~17 tok/s FP16⚠ Insufficient VRAM | 16GB VRAM used8GB total on card | $269View GPU → |
RX 7600 XTTight VRAM AMD | ~17 tok/s FP16 | 16GB VRAM used16GB total on card | $329View GPU → |
Apple M4 ProEstimated Apple | ~14 tok/s FP16 | 16GB VRAM used64GB total on card | $1,999View GPU → |
AMD Ryzen AI Max+ 395Estimated AMD | ~14 tok/s FP16 | 16GB VRAM used128GB total on card | EnterpriseView GPU → |
AMD Ryzen AI Max 385Estimated AMD | ~14 tok/s FP16 | 16GB VRAM used128GB total on card | EnterpriseView GPU → |
AMD Ryzen AI Max Pro 385Estimated AMD | ~14 tok/s FP16 | 16GB VRAM used128GB total on card | EnterpriseView GPU → |
Apple M2 ProEstimated Apple | ~10 tok/s FP16 | 16GB VRAM used32GB total on card | $1,999View GPU → |
Apple M3 ProEstimated Apple | ~8 tok/s FP16 | 16GB VRAM used36GB total on card | $1,999View GPU → |
Nousresearch Hermes 3 Llama 3 1 8B 8B parametre içerir ve 4GB VRAM gerektirir - choose the best GPU for your needs
For Better Performance
Run Nousresearch Hermes 3 Llama 3 1 8B faster with AMD Instinct MI300X. For just $150 more, significantly boost your tokens/sec performance.
Hardware requirements and model sizes at a glance.
| Component | Minimum | Recommended | Optimal |
|---|---|---|---|
| VRAM | 4GB (Q4) | 8GB (Q8) | 16GB (FP16) |
| RAM | 16GB | 32GB | 64GB |
| Disk | 10GB | 20GB | - |
| Model size | 4GB (Q4) | 8GB (Q8) | 16GB (FP16) |
| CPU | Modern CPU (Ryzen 5/Intel i5 or better) | Modern CPU (Ryzen 5/Intel i5 or better) | Modern CPU (Ryzen 5/Intel i5 or better) |
Note: Performance estimates are calculated. Real results may vary. Methodology · Submit real data
Common questions about running Nousresearch Hermes 3 Llama 3 1 8B locally
Llama 3 8B is the go-to lightweight assistant. It runs on almost any 12GB GPU, making it ideal for chatbots, agent prototypes, and personal copilots.
Use runtimes like llama.cpp, text-generation-webui, or vLLM. Download the quantized weights from Hugging Face, ensure you have enough VRAM for your target quantization, and launch with GPU acceleration (CUDA/ROCm/Metal).
Start with Q4 for wide GPU compatibility. Upgrade to Q8 if you have spare VRAM and want extra quality. FP16 delivers the highest fidelity but demands workstation or multi-GPU setups.
Q4_K_M and Q5_K_M are GGUF quantization formats that balance quality and VRAM usage. Q4_K_M uses about 4GB VRAM. Q5_K_M uses about 6GB VRAM and keeps more accuracy. Q8 (~8GB) offers near-FP16 quality. Standard Q4 is the most memory-efficient option for Nousresearch Hermes 3 Llama 3 1 8B.
Official weights are available via Hugging Face. Quantized builds (Q4, Q8) can be loaded into runtimes like llama.cpp, text-generation-webui, or vLLM. Always verify the publisher before downloading.
See how Nousresearch Hermes 3 Llama 3 1 8B compares to other popular models.