Model benchmarks
gemma4:e4b local LLM performance
As of July 2026, gemma4:e4b runs at up to 75.2 tok/s for local inference (best of 3 community benchmark runs across 2 GPUs).
OllamaQ4_K_M
Model size
8.0B
Peak speed
75.2 tok/s
Average speed
62.4 tok/s
Min memory
3.1 GB
Max context
6,292 tokens
Best quality
81.3
Benchmark runs
3
GPUs tested
2
Performance by hardware and tool
Every hardware/tool/quantization combination gemma4:e4b has been benchmarked on, ranked by peak token generation speed. Last updated July 2026.
| Hardware | Tool | Quant | Best tok/s | Avg tok/s | Memory | Context | Quality | Runs |
|---|---|---|---|---|---|---|---|---|
| CPU only | Ollama | Q4_K_M | 75.2 tok/s | 75.2 tok/s | 3.2 GB | 6,292 tokens | 62.4 | 1 |
| NVIDIA GeForce RTX 4070 Laptop GPU | Ollama | Q4_K_M | 57.6 tok/s | 57.6 tok/s | 3.1 GB | 5,750 tokens | 61.4 | 1 |
| Apple M4 Pro | Ollama | Q4_K_M | 54.3 tok/s | 54.3 tok/s | 9.0 GB | 5,622 tokens | 54.0 | 1 |
Frequently asked questions
- How fast is gemma4:e4b for local inference?
- Across 3 community benchmark runs, gemma4:e4b reaches up to 75.2 tok/s and averages 62.4 tok/s.
- How much memory does gemma4:e4b need?
- The leanest observed configuration used about 3.1 GB of memory (quantizations tested: Q4_K_M).
- Which tools have been used to run gemma4:e4b?
- Benchmarks were submitted using Ollama. Results are community-contributed and updated as new runs arrive.