Model benchmarks
google/gemma-4-12b local LLM performance
As of August 2026, google/gemma-4-12b runs at up to 32.4 tok/s for local inference (best of 2 community benchmark runs across 2 GPUs).
LM Studio
Model size
12B
Peak speed
32.4 tok/s
Average speed
28.7 tok/s
Min memory
9.3 GB
Max context
5,365 tokens
Best quality
85.6
Benchmark runs
2
GPUs tested
2
Performance by hardware and tool
Every hardware/tool/quantization combination google/gemma-4-12b 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 6800 XT | LM Studio | — | 32.4 tok/s | 32.4 tok/s | 9.3 GB | 5,017 tokens | 73.8 | 1 |
| NVIDIA GeForce RTX 4070 Ti SUPER | LM Studio | — | 24.9 tok/s | 24.9 tok/s | 12.0 GB | 5,365 tokens | 75.4 | 1 |
Frequently asked questions
- How fast is google/gemma-4-12b for local inference?
- Across 2 community benchmark runs, google/gemma-4-12b reaches up to 32.4 tok/s and averages 28.7 tok/s, with the fastest results on AMD Radeon RX 6800 XT.
- How much memory does google/gemma-4-12b need?
- The leanest observed configuration used about 9.3 GB of memory.
- Which tools have been used to run google/gemma-4-12b?
- Benchmarks were submitted using LM Studio. Results are community-contributed and updated as new runs arrive.