Local AI · Recipe · 1× DGX Spark

GLM-5.3-Flash EXL3 2.25 bpw with vLLM on 1× DGX Spark

GLM-5.3-Flash EXL3 2.25 bpw with vLLM on 1× DGX Spark: 19.5 tok/s according to github.com (dataset as of Nov 3, 2026).

19.5tok/sEveryday

1 request, prose prompt, with DFlash2 (per recipe)

Intelligence (original model) · Artificial Analysis42with thinkingOriginal model's value. Heavily compressed (~2.3 bit), intelligence is likely much lower.

≤ 3 bit: quantization may cost quality

Instructions in the README Repo

Engine: vLLM v0.30.0rc1 @ a00a3544b93e
Quantization: EXL3 2.25 bpw (Drafter EXL3 3.00 bpw)
Model family: GLM-5.3-Flash
Context: 32,768
Creator: r0b0tlab
GitHub stars: 0
Repo updated: Sep 27, 2026

Measurements

Every sourced value of this recipe, each with its condition and source. Bars relative to the largest value in the group.

Decode · 1 request

Everyday (decode)19.5 tok/sOpen prose, single-stream Median aus 5, 2048 cap (Prompt-Länge nicht angegeben) Source
Peak (decode)50.2 tok/sStructured output, single-stream Median aus 5, 2048-Token-Cap, temp 0 Source

What you need

Hardware: 1 × NVIDIA DGX Spark (GB10)
Weights: Main weightsr0b0tlab/GLM-5.3-Flash-EXL3-2.25bpw-sm121 MIT
Draft modelincoai/GLM-5.3-Flash-DFlash2 Non-commercial · CC-BY-NC-ND-4.0
Engine: vLLM v0.30.0rc1 @ a00a3544b93e
Context: 32,768 tokens

Notes

What matters before you rebuild it.

≤ 3 bit: quantization may cost qualityAt 3 bit and below the model may answer noticeably worse than the original. The intelligence number refers to the original.
Experimental
Custom kernel required
Non-commercial

Sources

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Engine

Measurements

Decode · 1 request

What you need

Notes

Sources

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