Model benchmarks

ling-tiny local LLM performance

As of September 2026, ling-tiny runs at up to 3774429.8 tok/s for local inference (best of 2 community benchmark runs across 1 GPU).

LM Studio
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Model size

Unknown

Peak speed

3774429.8 tok/s

Average speed

1887238.2 tok/s

Avg prefill

206.6 tok/s

Min memory

3.4 GB

Max context

8,192 tokens

Avg output / run

14,602 tokens

Avg runtime / run

5m 36s

Avg quality

41.0

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)
Overall33.341.048.8
Agent Workflow36.451.666.9
Code Generation2.814.125.4
Role Play & Narrative34.644.053.3
Research & Analysis40.854.568.2

Performance by hardware and tool

Every hardware/tool/quantization combination ling-tiny has been benchmarked on, ranked by peak token generation speed. Last updated September 2026.

HardwareToolQuantBest tok/sAvg tok/sMemoryContextQualityRuns
Apple M1LM Studio3774429.8 tok/s1887238.2 tok/s3.4 GB8,192 tokens41.02

Frequently asked questions

How fast is ling-tiny for local inference?
Across 2 community benchmark runs, ling-tiny reaches up to 3774429.8 tok/s and averages 1887238.2 tok/s, with the fastest results on Apple M1.
How much memory does ling-tiny need?
The leanest observed configuration used about 3.4 GB of memory.
Which tools have been used to run ling-tiny?
Benchmarks were submitted using LM Studio. Results are community-contributed and updated as new runs arrive.