Model benchmarks
llama3.1:8b local LLM performance
As of May 2026, llama3.1:8b runs at up to 74.0 tok/s for local inference (best of 7 community benchmark runs across 0 GPUs).
OllamaQ4_K_M
Model size
8.0B
Peak speed
74.0 tok/s
Average speed
38.6 tok/s
Min memory
4.8 GB
Max context
3,135 tokens
Best quality
80.9
Benchmark runs
7
GPUs tested
0
Performance by hardware and tool
Every hardware/tool/quantization combination llama3.1:8b has been benchmarked on, ranked by peak token generation speed. Last updated May 2026.
| Hardware | Tool | Quant | Best tok/s | Avg tok/s | Memory | Context | Quality | Runs |
|---|---|---|---|---|---|---|---|---|
| CPU only | Ollama | Q4_K_M | 74.0 tok/s | 38.6 tok/s | 4.8 GB | 3,135 tokens | 45.9 | 7 |
Frequently asked questions
- How fast is llama3.1:8b for local inference?
- Across 7 community benchmark runs, llama3.1:8b reaches up to 74.0 tok/s and averages 38.6 tok/s.
- How much memory does llama3.1:8b need?
- The leanest observed configuration used about 4.8 GB of memory (quantizations tested: Q4_K_M).
- Which tools have been used to run llama3.1:8b?
- Benchmarks were submitted using Ollama. Results are community-contributed and updated as new runs arrive.