4× RTX PRO 6000
81.7tok/sEveryday
1 request, prose prompt, with MTP Source
Intelligence34with thinkingno thinking 22
- ≤ 3 bit: quantization may cost quality
Local AI · Recipe · 4× RTX PRO 6000
GLM-5.2 EXL3 3.0 bpw with vLLM on 4× RTX PRO 6000 (500k context, text)
by jcartu
Intelligence (original model) · Artificial Analysis34with thinkingno thinking 22
≤ 3 bit: quantization may cost quality
Engine
- Engine
- vLLM
- Quantization
- EXL3/Trellis 3.0 bpw, nvfp4_ds_mla KV
- Model family
- GLM-5.2
- Context
- 512,000
- Creator
- jcartu
- GitHub stars
- 0
- Repo updated
- Jul 27, 2026
Measurements
Every sourced value of this recipe, each with its condition and source. Bars relative to the largest value in the group.
No sourced measurements for this recipe.
What you need
- Hardware
- 4 × NVIDIA RTX PRO 6000 Blackwell
- Weights
- Main weightsbrandonmusic/GLM-5.2-EXL3-TR3-3.0bpw MIT
- Engine
- vLLM
- Context
- 512,000 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.
Sources
- github.com/jcartu/glm52-exl3-blackwell-inference-study/blob/main/ISSUE33_STUDY.md#full-sustained-decode-comparison
- github.com/jcartu/glm52-exl3-blackwell-inference-study/blob/main/ISSUE33_STUDY.md#final-production-versus-matched-stock
- github.com/jcartu/glm52-exl3-blackwell-inference-study
- github.com/jcartu/glm52-exl3-blackwell-inference-study/blob/main/ISSUE33_STUDY.md
- github.com/jcartu/glm52-exl3-blackwell-inference-study/blob/main/results/issue33-upgrade/production-final-dcp2-g9675-owner0-chunk1-pf64-sh16-ckv140k-b3072-max512k-inference-temp1.json
- github.com/jcartu/glm52-exl3-blackwell-inference-study/blob/main/configs/docker-compose.exl3-v20.yml
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