Model benchmarks
gemma4:26b-a4b-it-qat local LLM performance
As of August 2026, gemma4:26b-a4b-it-qat runs at up to 121.4 tok/s for local inference (best of 13 community benchmark runs across 3 GPUs).
OllamaQ4_0
Model size
25.2B
Peak speed
121.4 tok/s
Average speed
69.9 tok/s
Min memory
14.0 GB
Max context
524,288 tokens
Avg runtime / run
2m 31s
Avg quality
68.1
Benchmark runs
13
GPUs tested
3
Quality by task
Average LLM-judged quality (0–100) with the run-to-run spread shown as a P5–P95 band, overall and for each benchmark task, across all 13 runs. The low and high columns show how much the judge’s score varies between runs, and need at least two runs to display.
| Task | P5 (low) | Avg | P95 (high) |
|---|---|---|---|
| Overall | 57.9 | 68.1 | 73.7 |
| Agent Workflow | 40.4 | 74.3 | 87.7 |
| Code Generation | 56.8 | 61.3 | 68.3 |
| Role Play & Narrative | 43.9 | 72.6 | 87.0 |
| Research & Analysis | 55.8 | 64.2 | 70.4 |
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 August 2026.
| Hardware | Tool | Quant | Best tok/s | Avg tok/s | Memory | Context | Quality | Runs |
|---|---|---|---|---|---|---|---|---|
| AMD Radeon RX 7900 XTX | Ollama | Q4_0 | 121.4 tok/s | 116.0 tok/s | 14.1 GB | 131,072 tokens | 69.2 | 3 |
| CPU only | Ollama | Q4_0 | 78.6 tok/s | 67.9 tok/s | 14.0 GB | 131,072 tokens | 67.3 | 4 |
| Apple M4 Pro | Ollama | Q4_0 | 62.3 tok/s | 53.9 tok/s | 14.0 GB | 524,288 tokens | 71.5 | 5 |
| NVIDIA GeForce RTX 4070 Laptop GPU | Ollama | Q4_0 | 19.3 tok/s | 19.3 tok/s | 14.1 GB | 8,192 tokens | 51.3 | 1 |
Frequently asked questions
- Is gemma4:26b-a4b-it-qat good for coding?
- In our benchmarks, gemma4:26b-a4b-it-qat scores 61.3/100 for coding. It runs at about 69.9 tok/s, so if you want more speed, unsloth/Qwen3.8-27B-GGUF:IQ3_S is faster (~104.3 tok/s) and still scores well for coding (83.0/100).
- Is gemma4:26b-a4b-it-qat good for agentic (tool-using) tasks?
- In our benchmarks, gemma4:26b-a4b-it-qat scores 74.3/100 for agentic workflows. It runs at about 69.9 tok/s, so if you want more speed, Tiel-Coder-35B-A3B-Q4_K_S is faster (~165.0 tok/s) and still scores well for agentic workflows (89.3/100).
- How fast is gemma4:26b-a4b-it-qat for local inference?
- Across 13 community benchmark runs, gemma4:26b-a4b-it-qat reaches up to 121.4 tok/s and averages 69.9 tok/s, with the fastest results on AMD Radeon RX 7900 XTX.
- 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.