Model benchmarks
gemma-4-e4b-uncensored-hauhaucs-aggressive local LLM performance
As of October 2026, gemma-4-e4b-uncensored-hauhaucs-aggressive runs at up to 104.0 tok/s for local inference (best of 4 community benchmark runs across 3 GPUs).
Model size
4B
Peak speed
104.0 tok/s
Average speed
41.3 tok/s
Avg PP
721.3 tok/s
Min memory
n/a
Max context
8,192 tokens
Avg output / run
11,527 tokens
Avg runtime / run
11m 11s
Avg quality
64.6
Benchmark runs
4
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 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 | 61.8 | 64.6 | 69.4 |
| Agent Workflow | 64.3 | 70.6 | 76.7 |
| Code Generation | 42.9 | 48.4 | 54.5 |
| Role Play & Narrative | 69.8 | 77.5 | 86.7 |
| Research & Analysis | 59.3 | 61.7 | 63.0 |
Performance by hardware and tool
Every hardware/tool/quantization combination gemma-4-e4b-uncensored-hauhaucs-aggressive 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 |
|---|---|---|---|---|---|---|---|---|
| NVIDIA GeForce RTX 3070 Ti | Unsloth Studio | IQ4_XS | 104.0 tok/s | 104.0 tok/s | n/a | 8,192 tokens | 62.2 | 1 |
| AMD Radeon RX 6600 | LM Studio | — | 27.6 tok/s | 17.8 tok/s | n/a | 8,192 tokens | 67.1 | 2 |
| Intel(R) Arc(TM) Pro 140T GPU (16GB) | LM Studio | — | 25.6 tok/s | 25.6 tok/s | n/a | 8,192 tokens | 61.8 | 1 |
Benchmark runs
All 4 gemma-4-e4b-uncensored-hauhaucs-aggressive runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.
Frequently asked questions
- Is gemma-4-e4b-uncensored-hauhaucs-aggressive good for coding?
- In our benchmarks, gemma-4-e4b-uncensored-hauhaucs-aggressive scores 48.4/100 for coding. It runs at about 41.3 tok/s, so if you want more speed, local-qwen is faster (~60.2 tok/s) and still scores well for coding (84.8/100).
- Is gemma-4-e4b-uncensored-hauhaucs-aggressive good for agentic (tool-using) tasks?
- In our benchmarks, gemma-4-e4b-uncensored-hauhaucs-aggressive scores 70.6/100 for agentic workflows. It runs at about 41.3 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 gemma-4-e4b-uncensored-hauhaucs-aggressive for local inference?
- Across 4 community benchmark runs, gemma-4-e4b-uncensored-hauhaucs-aggressive reaches up to 104.0 tok/s and averages 41.3 tok/s, with the fastest results on NVIDIA GeForce RTX 3070 Ti.
- Which tools have been used to run gemma-4-e4b-uncensored-hauhaucs-aggressive?
- Benchmarks were submitted using LM Studio, Unsloth Studio. Results are community-contributed and updated as new runs arrive.