Model benchmarks
gemma3:latest local LLM performance
As of October 2026, gemma3:latest runs at up to 25.0 tok/s for local inference (best of 4 community benchmark runs across 1 GPU).
Model size
4.3B
Peak speed
25.0 tok/s
Average speed
22.3 tok/s
Avg PP
554.0 tok/s
Min memory
2.7 GB
Max context
65,536 tokens
Avg output / run
5,650 tokens
Avg runtime / run
4m 30s
Avg quality
53.1
Benchmark runs
4
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 4 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 | 50.1 | 53.1 | 55.3 |
| Agent Workflow | 59.3 | 68.8 | 77.8 |
| Code Generation | 25.4 | 27.3 | 29.3 |
| Role Play & Narrative | 66.1 | 74.7 | 81.5 |
| Research & Analysis | 31.6 | 41.4 | 50.1 |
Performance by hardware and tool
Every hardware/tool/quantization combination gemma3:latest has been benchmarked on, ranked by peak token generation speed. Last updated October 2026.
| Hardware | Tool | Quant | Best tok/s | Avg tok/s | Memory | Context | Quality | Runs |
|---|---|---|---|---|---|---|---|---|
| Intel Arc B390 | Ollama | Q4_K_M | 25.0 tok/s | 22.3 tok/s | 2.7 GB | 65,536 tokens | 53.1 | 4 |
Benchmark runs
All 4 gemma3:latest runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.
Frequently asked questions
- Is gemma3:latest good for coding?
- In our benchmarks, gemma3:latest scores 27.3/100 for coding. It runs at about 22.3 tok/s, so if you want more speed, Qwen3.8-27B-oQ4e-fp16-mtp is faster (~38.6 tok/s) and still scores well for coding (82.6/100).
- Is gemma3:latest good for agentic (tool-using) tasks?
- In our benchmarks, gemma3:latest scores 68.8/100 for agentic workflows. It runs at about 22.3 tok/s, so if you want more speed, muse-glimmer:latest is faster (~33.3 tok/s) and still scores well for agentic workflows (91.6/100).
- How fast is gemma3:latest for local inference?
- Across 4 community benchmark runs, gemma3:latest reaches up to 25.0 tok/s and averages 22.3 tok/s, with the fastest results on Intel Arc B390.
- How much memory does gemma3:latest need?
- The leanest observed configuration used about 2.7 GB of memory (quantizations tested: Q4_K_M).
- Which tools have been used to run gemma3:latest?
- Benchmarks were submitted using Ollama. Results are community-contributed and updated as new runs arrive.