Model benchmarks
gemma4:26b local LLM performance
As of July 2026, gemma4:26b runs at up to 31.7 tok/s for local inference (best of 13 community benchmark runs across 1 GPU).
OllamaQ4_K_M
Model size
25.8B
Peak speed
31.7 tok/s
Average speed
25.0 tok/s
Min memory
16.2 GB
Max context
128,000 tokens
Avg quality
59.4
Benchmark runs
13
GPUs tested
1
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 | 35.4 | 59.4 | 69.3 |
| Agent Workflow | 37.0 | 72.0 | 87.2 |
| Code Generation | 13.1 | 32.8 | 57.8 |
| Role Play & Narrative | 58.2 | 76.8 | 85.8 |
| Research & Analysis | 31.3 | 56.1 | 70.4 |
Performance by hardware and tool
Every hardware/tool/quantization combination gemma4:26b 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 |
|---|---|---|---|---|---|---|---|---|
| AMD Radeon RX 7900 XTX | Ollama | Q4_K_M | 31.7 tok/s | 25.0 tok/s | 16.2 GB | 128,000 tokens | 59.4 | 13 |
Frequently asked questions
- Is gemma4:26b good for coding?
- In our benchmarks, gemma4:26b scores 32.8/100 for coding. It runs at about 25.0 tok/s, so if you want more speed, Gemma4:E2B/QAT-MTP@131K is faster (~303.9 tok/s) and still scores well for coding (66.9/100).
- Is gemma4:26b good for agentic (tool-using) tasks?
- In our benchmarks, gemma4:26b scores 72.0/100 for agentic workflows. It runs at about 25.0 tok/s, so if you want more speed, Gemma4:E2B/QAT-MTP@131K is faster (~303.9 tok/s) and still scores well for agentic workflows (71.7/100).
- How fast is gemma4:26b for local inference?
- Across 13 community benchmark runs, gemma4:26b reaches up to 31.7 tok/s and averages 25.0 tok/s, with the fastest results on AMD Radeon RX 7900 XTX.
- How much memory does gemma4:26b need?
- The leanest observed configuration used about 16.2 GB of memory (quantizations tested: Q4_K_M).
- Which tools have been used to run gemma4:26b?
- Benchmarks were submitted using Ollama. Results are community-contributed and updated as new runs arrive.