Model benchmarks
gemma4:26b-a4b-it-qat local LLM performance
As of July 2026, gemma4:26b-a4b-it-qat runs at up to 78.6 tok/s for local inference (best of 10 community benchmark runs across 2 GPUs).
OllamaQ4_0
Model size
25.2B
Peak speed
78.6 tok/s
Average speed
56.0 tok/s
Min memory
14.0 GB
Max context
6,441 tokens
Best quality
87.8
Benchmark runs
10
GPUs tested
2
Performance by hardware and tool
Every hardware/tool/quantization combination gemma4:26b-a4b-it-qat 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_0 | 78.6 tok/s | 67.9 tok/s | 14.0 GB | 6,203 tokens | 70.3 | 4 |
| Apple M4 Pro | Ollama | Q4_0 | 62.3 tok/s | 53.9 tok/s | 14.0 GB | 5,474 tokens | 70.2 | 5 |
| NVIDIA GeForce RTX 4070 Laptop GPU | Ollama | Q4_0 | 19.3 tok/s | 19.3 tok/s | 14.1 GB | 6,441 tokens | 52.9 | 1 |
Frequently asked questions
- How fast is gemma4:26b-a4b-it-qat for local inference?
- Across 10 community benchmark runs, gemma4:26b-a4b-it-qat reaches up to 78.6 tok/s and averages 56.0 tok/s.
- How much memory does gemma4:26b-a4b-it-qat need?
- The leanest observed configuration used about 14.0 GB of memory (quantizations tested: Q4_0).
- Which tools have been used to run gemma4:26b-a4b-it-qat?
- Benchmarks were submitted using Ollama. Results are community-contributed and updated as new runs arrive.