Model benchmarks
unsloth/gemma-4-31B-it-qat-GGUF local LLM performance
As of October 2026, unsloth/gemma-4-31B-it-qat-GGUF runs at up to 42.1 tok/s for local inference (best of 2 community benchmark runs across 1 GPU).
Model size
31B
Peak speed
42.1 tok/s
Average speed
35.4 tok/s
Avg PP
444.6 tok/s
Min memory
n/a
Max context
65,536 tokens
Avg output / run
10,285 tokens
Avg runtime / run
5m 1s
Avg quality
73.4
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 | 72.4 | 73.4 | 74.5 |
| Agent Workflow | 77.7 | 79.4 | 81.1 |
| Code Generation | 66.0 | 66.2 | 66.4 |
| Role Play & Narrative | 73.1 | 79.1 | 85.2 |
| Research & Analysis | 68.6 | 69.0 | 69.5 |
Performance by hardware and tool
Every hardware/tool/quantization combination unsloth/gemma-4-31B-it-qat-GGUF 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 |
|---|---|---|---|---|---|---|---|---|
| Apple M5 Max | Unsloth Studio | UD-Q4_K_XL | 42.1 tok/s | 42.1 tok/s | n/a | 65,536 tokens | 72.3 | 1 |
| Apple M5 Max | llama.cpp | — | 28.8 tok/s | 28.8 tok/s | n/a | 65,536 tokens | 74.6 | 1 |
Benchmark runs
All 2 unsloth/gemma-4-31B-it-qat-GGUF runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.
Frequently asked questions
- Is unsloth/gemma-4-31B-it-qat-GGUF good for coding?
- In our benchmarks, unsloth/gemma-4-31B-it-qat-GGUF scores 66.2/100 for coding. It runs at about 35.4 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 unsloth/gemma-4-31B-it-qat-GGUF good for agentic (tool-using) tasks?
- In our benchmarks, unsloth/gemma-4-31B-it-qat-GGUF scores 79.4/100 for agentic workflows. It runs at about 35.4 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 unsloth/gemma-4-31B-it-qat-GGUF for local inference?
- Across 2 community benchmark runs, unsloth/gemma-4-31B-it-qat-GGUF reaches up to 42.1 tok/s and averages 35.4 tok/s, with the fastest results on Apple M5 Max.
- Which tools have been used to run unsloth/gemma-4-31B-it-qat-GGUF?
- Benchmarks were submitted using Unsloth Studio, llama.cpp. Results are community-contributed and updated as new runs arrive.