Model benchmarks
unsloth/gemma-4-E4B-it-qat-mobile-GGUF local LLM performance
As of September 2026, unsloth/gemma-4-E4B-it-qat-mobile-GGUF runs at up to 73.6 tok/s for local inference (best of 2 community benchmark runs across 1 GPU).
Model size
4B
Peak speed
73.6 tok/s
Average speed
73.1 tok/s
Avg PP
864.1 tok/s
Min memory
2.0 GB
Max context
131.072 tokens
Avg output / run
7.526 tokens
Avg runtime / run
1m 49s
Avg quality
26.4
Benchmark runs
2
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 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 | 23.7 | 26.4 | 29.2 |
| Agent Workflow | 24.5 | 32.2 | 39.8 |
| Code Generation | 4.0 | 9.9 | 15.7 |
| Role Play & Narrative | 38.1 | 40.4 | 42.6 |
| Research & Analysis | 23.1 | 23.4 | 23.7 |
Performance by hardware and tool
Every hardware/tool/quantization combination unsloth/gemma-4-E4B-it-qat-mobile-GGUF 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 |
|---|---|---|---|---|---|---|---|---|
| NVIDIA GeForce RTX 4070 | llama.cpp | — | 73.6 tok/s | 73.1 tok/s | 2.0 GB | 131.072 tokens | 26.4 | 2 |
Benchmark runs
All 2 unsloth/gemma-4-E4B-it-qat-mobile-GGUF runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.
Frequently asked questions
- Is unsloth/gemma-4-E4B-it-qat-mobile-GGUF good for coding?
- In our benchmarks, unsloth/gemma-4-E4B-it-qat-mobile-GGUF scores 9.9/100 for coding. It runs at about 73.1 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 unsloth/gemma-4-E4B-it-qat-mobile-GGUF good for agentic (tool-using) tasks?
- In our benchmarks, unsloth/gemma-4-E4B-it-qat-mobile-GGUF scores 32.2/100 for agentic workflows. It runs at about 73.1 tok/s, so if you want more speed, Tiel-Coder-35B-A3B-Q4_K_S is faster (~165.0 tok/s) and still scores well for agentic workflows (89.3/100).
- How fast is unsloth/gemma-4-E4B-it-qat-mobile-GGUF for local inference?
- Across 2 community benchmark runs, unsloth/gemma-4-E4B-it-qat-mobile-GGUF reaches up to 73.6 tok/s and averages 73.1 tok/s, with the fastest results on NVIDIA GeForce RTX 4070.
- How much memory does unsloth/gemma-4-E4B-it-qat-mobile-GGUF need?
- The leanest observed configuration used about 2.0 GB of memory.
- Which tools have been used to run unsloth/gemma-4-E4B-it-qat-mobile-GGUF?
- Benchmarks were submitted using llama.cpp. Results are community-contributed and updated as new runs arrive.