Model benchmarks

swift-1.5-qwen3.8-27b-uncensored local LLM performance

As of October 2026, swift-1.5-qwen3.8-27b-uncensored runs at up to 282.2 tok/s for local inference (best of 7 community benchmark runs across 1 GPU).

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Model size

27B

Peak speed

282.2 tok/s

Average speed

275.1 tok/s

Avg PP

13123.0 tok/s

Min memory

28.8 GB

Max context

100,000 tokens

Avg output / run

20,702 tokens

Avg runtime / run

1m 13s

Avg quality

85.4

Benchmark runs

7

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 7 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)
Overall83.285.487.6
Agent Workflow81.186.690.9
Code Generation71.877.884.3
Role Play & Narrative87.292.295.1
Research & Analysis79.784.887.6

Performance by hardware and tool

Every hardware/tool/quantization combination swift-1.5-qwen3.8-27b-uncensored has been benchmarked on, ranked by peak token generation speed. Last updated October 2026.

HardwareToolQuantBest tok/sAvg tok/sMemoryContextQualityRuns
NVIDIA GeForce RTX 5060 Tininfer—282.2 tok/s275.1 tok/s28.8 GB100,000 tokens85.47

Benchmark runs

All 7 swift-1.5-qwen3.8-27b-uncensored runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.

Frequently asked questions

How fast is swift-1.5-qwen3.8-27b-uncensored for local inference?
Across 7 community benchmark runs, swift-1.5-qwen3.8-27b-uncensored reaches up to 282.2 tok/s and averages 275.1 tok/s, with the fastest results on NVIDIA GeForce RTX 5060 Ti.
How much memory does swift-1.5-qwen3.8-27b-uncensored need?
The leanest observed configuration used about 28.8 GB of memory.
Which tools have been used to run swift-1.5-qwen3.8-27b-uncensored?
Benchmarks were submitted using ninfer. Results are community-contributed and updated as new runs arrive.