Local LLM Hardware
Local LLM on NVIDIA A100 80GB
80GB VRAM · HBM2e · 2039 GB/s memory bandwidth · 400W TDP · released 2020
At a glance
| VRAM | 80 GB |
|---|---|
| Memory | HBM2e |
| Memory bandwidth | 2039 GB/s |
| TDP | 400 W |
| Released | 2020 |
| 2026 price (used / new) | ~$15000 |
| Tier | data-center |
| Best for | production serving, 80GB fits most models comfortably |
What models fit on NVIDIA A100 80GB?
Memory bandwidth is the bottleneck for LLM token generation. The NVIDIA A100 80GB's 2039 GB/s bandwidth gives roughly the throughput below at Q4_K_M quantization. Numbers are conservative and assume a single request (batch=1), 2048-token context.
| Model | Quantization | Fits? | Approx tokens/sec |
|---|---|---|---|
| Llama 3.2 1B | Q4_K_M | Yes (0.8 GB) | ~367 tok/s |
| Llama 3.1 8B | Q4_K_M | Yes (~5 GB) | ~122 |
| Llama 3.1 8B | Q8_0 | Yes (~8 GB) | ~92 |
| Qwen 2.5 14B | Q4_K_M | Yes (~9 GB) | ~71 |
| Mistral Nemo 12B | Q4_K_M | Yes (~8 GB) | ~82 |
| Qwen 3 32B | Q4_K_M | Yes (~20 GB) | ~37 |
| DeepSeek R1 distilled 32B | Q4_K_M | Yes (~20 GB) | ~37 |
| Llama 3.1 70B | Q4_K_M | Yes (~42 GB) | ~20 |
| Llama 4 Scout 109B (MoE) | Q4_K_M | Yes (~64 GB) | ~16 |
Token estimates use a simple bandwidth heuristic (~tokens/sec ≈ bandwidth_GB/s × model_efficiency). Real numbers vary with model architecture, batch size, and KV-cache size. Treat as ballpark.
Build recommendations for NVIDIA A100 80GB
Best model to download first
Llama 3.1 8B for everyday chat and coding; Qwen 3 32B for top quality on 24GB. Start with ollama pull llama3.1:8b.
Recommended inference backend
Use Ollama for general use or Mullama if you need a drop-in Ollama alternative with native bindings for 6 languages. For production serving on multi-GPU setups, see vLLM.
Other GPUs to consider
- NVIDIA RTX 3090 — 24GB VRAM, high-end consumer (used market)
- NVIDIA RTX 4090 — 24GB VRAM, flagship consumer
- NVIDIA RTX 5090 — 32GB VRAM, flagship consumer 2025+
- NVIDIA RTX 6000 Ada — 48GB VRAM, workstation
- NVIDIA H100 80GB — 80GB VRAM, data-center flagship
- Apple M4 Max — 36GB VRAM, Apple Silicon flagship
- Apple M3 Ultra — 192GB VRAM, Apple Silicon workstation
- AMD Radeon RX 7900 XTX — 24GB VRAM, high-end AMD consumer
Sources
[1] nvidia.com/a100