Model benchmarks
gemma-4-e4b-uncensored-hauhaucs-aggressive local LLM performance
As of September 2026, gemma-4-e4b-uncensored-hauhaucs-aggressive runs at up to 25.6 tok/s for local inference (best of 2 community benchmark runs across 2 GPUs).
Model size
4B
Peak speed
25.6 tok/s
Average speed
16.8 tok/s
Avg PP
403.0 tok/s
Min memory
5.9 GB
Max context
8.192 tokens
Avg output / run
11.653 tokens
Avg runtime / run
17m 17s
Avg quality
62.8
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 | 61.9 | 62.8 | 63.7 |
| Agent Workflow | 64.5 | 69.5 | 74.4 |
| Code Generation | 42.5 | 44.3 | 46.1 |
| Role Play & Narrative | 71.5 | 76.4 | 81.4 |
| Research & Analysis | 59.1 | 61.0 | 62.8 |
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 September 2026.
| Hardware | Tool | Quant | Best tok/s | Avg tok/s | Memory | Context | Quality | Runs |
|---|---|---|---|---|---|---|---|---|
| Intel(R) Arc(TM) Pro 140T GPU (16GB) | LM Studio | — | 25.6 tok/s | 25.6 tok/s | 5.9 GB | 8.192 tokens | 61.8 | 1 |
| AMD Radeon RX 6600 | LM Studio | — | 8.0 tok/s | 8.0 tok/s | 5.9 GB | 8.192 tokens | 63.8 | 1 |
Benchmark runs
All 2 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 44.3/100 for coding. It runs at about 16.8 tok/s, so if you want more speed, /home/polaris/models/Tiel-Coder-35B-A3B-MTP-UD-Q6_K_XL.gguf is faster (~35.6 tok/s) and still scores well for coding (84.9/100).
- Is gemma-4-e4b-uncensored-hauhaucs-aggressive good for agentic (tool-using) tasks?
- In our benchmarks, gemma-4-e4b-uncensored-hauhaucs-aggressive scores 69.5/100 for agentic workflows. It runs at about 16.8 tok/s, so if you want more speed, muse-glimmer:latest is faster (~34.5 tok/s) and still scores well for agentic workflows (93.0/100).
- How fast is gemma-4-e4b-uncensored-hauhaucs-aggressive for local inference?
- Across 2 community benchmark runs, gemma-4-e4b-uncensored-hauhaucs-aggressive reaches up to 25.6 tok/s and averages 16.8 tok/s, with the fastest results on Intel(R) Arc(TM) Pro 140T GPU (16GB).
- How much memory does gemma-4-e4b-uncensored-hauhaucs-aggressive need?
- The leanest observed configuration used about 5.9 GB of memory.
- Which tools have been used to run gemma-4-e4b-uncensored-hauhaucs-aggressive?
- Benchmarks were submitted using LM Studio. Results are community-contributed and updated as new runs arrive.