Model benchmarks
gemma4:12b-it-qat local LLM performance
As of September 2026, gemma4:12b-it-qat runs at up to 54.0 tok/s for local inference (best of 2 community benchmark runs across 2 GPUs).
Model size
11.9B
Peak speed
54.0 tok/s
Average speed
43.8 tok/s
Avg PP
1113.9 tok/s
Min memory
7.4 GB
Max context
65.536 tokens
Avg output / run
13.117 tokens
Avg runtime / run
5m 49s
Avg quality
72.2
Benchmark runs
2
GPUs tested
2
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 2 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 | 70.0 | 72.2 | 74.4 |
| Agent Workflow | 66.4 | 74.0 | 81.7 |
| Code Generation | 63.3 | 64.5 | 65.7 |
| Role Play & Narrative | 73.2 | 77.7 | 82.2 |
| Research & Analysis | 70.4 | 72.6 | 74.9 |
Performance by hardware and tool
Every hardware/tool/quantization combination gemma4:12b-it-qat has been benchmarked on, ranked by peak token generation speed. Last updated September 2026.
| Hardware | Tool | Quant | Best tok/s | Avg tok/s | Memory | Context | Quality | Runs |
|---|---|---|---|---|---|---|---|---|
| AMD Radeon RX 7800 XT | Ollama | Q4_0 | 54.0 tok/s | 54.0 tok/s | 7.4 GB | 8.192 tokens | 69.8 | 1 |
| AMD Radeon RX 9050 / 9060 XT | Ollama | Q4_0 | 33.5 tok/s | 33.5 tok/s | 8.2 GB | 65.536 tokens | 74.6 | 1 |
Benchmark runs
All 2 gemma4:12b-it-qat runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.
Frequently asked questions
- Is gemma4:12b-it-qat good for coding?
- In our benchmarks, gemma4:12b-it-qat scores 64.5/100 for coding. It runs at about 43.8 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 gemma4:12b-it-qat good for agentic (tool-using) tasks?
- In our benchmarks, gemma4:12b-it-qat scores 74.0/100 for agentic workflows. It runs at about 43.8 tok/s, so if you want more speed, granite-4.2-8b-Q4_K_L is faster (~71.6 tok/s) and still scores well for agentic workflows (92.9/100).
- How fast is gemma4:12b-it-qat for local inference?
- Across 2 community benchmark runs, gemma4:12b-it-qat reaches up to 54.0 tok/s and averages 43.8 tok/s, with the fastest results on AMD Radeon RX 7800 XT.
- How much memory does gemma4:12b-it-qat need?
- The leanest observed configuration used about 7.4 GB of memory (quantizations tested: Q4_0).
- Which tools have been used to run gemma4:12b-it-qat?
- Benchmarks were submitted using Ollama. Results are community-contributed and updated as new runs arrive.