Model benchmarks

gpt-oss-20b-UD-Q6_K_XL local LLM performance

As of September 2026, gpt-oss-20b-UD-Q6_K_XL runs at up to 179.0 tok/s for local inference (best of 2 community benchmark runs across 1 GPU).

llama.cppQ6_K
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Model size

20B

Peak speed

179.0 tok/s

Average speed

151.2 tok/s

Avg prefill

1658.7 tok/s

Min memory

9.8 GB

Max context

131,072 tokens

Avg output / run

10,450 tokens

Avg runtime / run

1m 17s

Avg quality

74.0

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)
Overall70.874.077.2
Agent Workflow76.076.276.4
Code Generation69.574.178.7
Role Play & Narrative63.468.673.7
Research & Analysis73.977.180.2

Performance by hardware and tool

Every hardware/tool/quantization combination gpt-oss-20b-UD-Q6_K_XL has been benchmarked on, ranked by peak token generation speed. Last updated September 2026.

HardwareToolQuantBest tok/sAvg tok/sMemoryContextQualityRuns
NVIDIA GeForce RTX 5060llama.cppQ6_K179.0 tok/s151.2 tok/s9.8 GB131,072 tokens74.02

Frequently asked questions

How fast is gpt-oss-20b-UD-Q6_K_XL for local inference?
Across 2 community benchmark runs, gpt-oss-20b-UD-Q6_K_XL reaches up to 179.0 tok/s and averages 151.2 tok/s, with the fastest results on NVIDIA GeForce RTX 5060.
How much memory does gpt-oss-20b-UD-Q6_K_XL need?
The leanest observed configuration used about 9.8 GB of memory (quantizations tested: Q6_K).
Which tools have been used to run gpt-oss-20b-UD-Q6_K_XL?
Benchmarks were submitted using llama.cpp. Results are community-contributed and updated as new runs arrive.