Model benchmarks

unsloth/Qwen3.5-0.8B-MTP-GGUF local LLM performance

As of September 2026, unsloth/Qwen3.5-0.8B-MTP-GGUF runs at up to 549.7 tok/s for local inference (best of 6 community benchmark runs across 2 GPUs).

Unsloth Studiollama.cppUD-Q4_K_XLUD-Q8_K_XL
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Model size

0.8B

Peak speed

549.7 tok/s

Average speed

296.2 tok/s

Avg PP

1633.9 tok/s

Min memory

4.7 GB

Max context

262,144 tokens

Avg output / run

55,473 tokens

Avg runtime / run

2m 18s

Avg quality

20.5

Benchmark runs

6

GPUs tested

2

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 6 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)
Overall11.320.526.1
Agent Workflow14.527.939.6
Code Generation7.411.516.1
Role Play & Narrative3.124.240.6
Research & Analysis8.218.429.8

Performance by hardware and tool

Every hardware/tool/quantization combination unsloth/Qwen3.5-0.8B-MTP-GGUF has been benchmarked on, ranked by peak token generation speed. Last updated September 2026.

HardwareToolQuantBest tok/sAvg tok/sMemoryContextQualityRuns
NVIDIA GeForce RTX 4070Unsloth StudioUD-Q8_K_XL549.7 tok/s394.9 tok/s4.7 GB262,144 tokens16.82
NVIDIA GeForce RTX 4070Unsloth StudioUD-Q4_K_XL441.4 tok/s441.4 tok/s4.7 GB65,536 tokens15.71
NVIDIA GeForce RTX 4070llama.cpp—241.2 tok/s239.1 tok/sn/a262,144 tokens24.32
Intel(R) Arc(TM) 140V GPU (16GB)Unsloth Studio—68.2 tok/s68.2 tok/sn/a262,144 tokens25.21

Benchmark runs

All 6 unsloth/Qwen3.5-0.8B-MTP-GGUF runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.

Frequently asked questions

How fast is unsloth/Qwen3.5-0.8B-MTP-GGUF for local inference?
Across 6 community benchmark runs, unsloth/Qwen3.5-0.8B-MTP-GGUF reaches up to 549.7 tok/s and averages 296.2 tok/s, with the fastest results on NVIDIA GeForce RTX 4070.
How much memory does unsloth/Qwen3.5-0.8B-MTP-GGUF need?
The leanest observed configuration used about 4.7 GB of memory (quantizations tested: UD-Q4_K_XL, UD-Q8_K_XL).
Which tools have been used to run unsloth/Qwen3.5-0.8B-MTP-GGUF?
Benchmarks were submitted using Unsloth Studio, llama.cpp. Results are community-contributed and updated as new runs arrive.