Model benchmarks

unsloth/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-GGUF:UD-Q4_K_XL local LLM performance

As of August 2026, unsloth/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-GGUF:UD-Q4_K_XL runs at up to 179.3 tok/s for local inference (best of 2 community benchmark runs across 1 GPU).

llama.cppQ4_K
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Model size

30B

Peak speed

179.3 tok/s

Average speed

169.2 tok/s

Min memory

14.6 GB

Max context

65,536 tokens

Avg output / run

52,001 tokens

Avg runtime / run

4m 44s

Avg quality

76.8

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.

TaskP5 (low)AvgP95 (high)
Overall76.376.877.4
Agent Workflow77.783.088.2
Code Generation62.163.865.4
Role Play & Narrative71.779.387.0
Research & Analysis79.881.382.7

Performance by hardware and tool

Every hardware/tool/quantization combination unsloth/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-GGUF:UD-Q4_K_XL has been benchmarked on, ranked by peak token generation speed. Last updated August 2026.

HardwareToolQuantBest tok/sAvg tok/sMemoryContextQualityRuns
NVIDIA GeForce RTX 3080 Tillama.cppQ4_K179.3 tok/s169.2 tok/s14.6 GB65,536 tokens76.82

Frequently asked questions

Is unsloth/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-GGUF:UD-Q4_K_XL good for coding?
In our benchmarks, unsloth/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-GGUF:UD-Q4_K_XL scores 63.8/100 for coding. It runs at about 169.2 tok/s, so if you want more speed, Gemma4:E2B/QAT-MTP@131K is faster (~303.9 tok/s) and still scores well for coding (66.9/100).
How fast is unsloth/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-GGUF:UD-Q4_K_XL for local inference?
Across 2 community benchmark runs, unsloth/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-GGUF:UD-Q4_K_XL reaches up to 179.3 tok/s and averages 169.2 tok/s, with the fastest results on NVIDIA GeForce RTX 3080 Ti.
How much memory does unsloth/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-GGUF:UD-Q4_K_XL need?
The leanest observed configuration used about 14.6 GB of memory (quantizations tested: Q4_K).
Which tools have been used to run unsloth/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-GGUF:UD-Q4_K_XL?
Benchmarks were submitted using llama.cpp. Results are community-contributed and updated as new runs arrive.