How fast is inclusionAI/Ling-3.0-tiny-GGUF for local inference?

Across 2 community benchmark runs, inclusionAI/Ling-3.0-tiny-GGUF reaches up to 249.2 tok/s and averages 215.9 tok/s, with the fastest results on NVIDIA GeForce RTX 4070.

How much memory does inclusionAI/Ling-3.0-tiny-GGUF need?

The leanest observed configuration used about 7.8 GB of memory (quantizations tested: Q6_K).

Which tools have been used to run inclusionAI/Ling-3.0-tiny-GGUF?

Benchmarks were submitted using Unsloth Studio, llama.cpp. Results are community-contributed and updated as new runs arrive.

Model benchmarks

inclusionAI/Ling-3.0-tiny-GGUF local LLM performance

As of October 2026, inclusionAI/Ling-3.0-tiny-GGUF runs at up to 249.2 tok/s for local inference (best of 2 community benchmark runs across 2 GPUs).

Unsloth Studiollama.cppQ6_K

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Model size

7.9B

Peak speed

249.2 tok/s

Average speed

215.9 tok/s

Avg PP

3921.2 tok/s

Min memory

7.8 GB

Max context

131,072 tokens

Avg output / run

55,886 tokens

Avg runtime / run

3m 37s

Avg quality

48.5

Benchmark runs

GPUs tested

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	48.0	48.5	49.0
Agent Workflow	71.8	73.4	74.9
Code Generation	29.9	32.8	35.8
Role Play & Narrative	11.3	18.4	25.6
Research & Analysis	65.6	69.4	73.2

Performance by hardware and tool

Every hardware/tool/quantization combination inclusionAI/Ling-3.0-tiny-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
NVIDIA GeForce RTX 4070	Unsloth Studio	Q6_K	249.2 tok/s	249.2 tok/s	7.8 GB	65,536 tokens	47.9	1
NVIDIA RTX A6000	llama.cpp	—	182.6 tok/s	182.6 tok/s	22.3 GB	131,072 tokens	49.1	1

Benchmark runs

All 2 inclusionAI/Ling-3.0-tiny-GGUF runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.

Open run page →

Frequently asked questions

How fast is inclusionAI/Ling-3.0-tiny-GGUF for local inference?: Across 2 community benchmark runs, inclusionAI/Ling-3.0-tiny-GGUF reaches up to 249.2 tok/s and averages 215.9 tok/s, with the fastest results on NVIDIA GeForce RTX 4070.
How much memory does inclusionAI/Ling-3.0-tiny-GGUF need?: The leanest observed configuration used about 7.8 GB of memory (quantizations tested: Q6_K).
Which tools have been used to run inclusionAI/Ling-3.0-tiny-GGUF?: Benchmarks were submitted using Unsloth Studio, llama.cpp. Results are community-contributed and updated as new runs arrive.