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 504B NVFP4 with vLLM on 4× RTX PRO 6000
by jcartu
Intelligence (original model) · Artificial Analysisno independent value
Engine
- Engine
- vLLM
- Quantization
- NVFP4 (modelopt) Experten, BF16 Router/Attention, FP8 KV
- Model family
- GLM-5.2
- Context
- 262,144
- Parameters
- 504B
- Creator
- jcartu
- GitHub stars
- 3
- Repo updated
- Jun 21, 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 weights0xSero/GLM-5.2-504B MIT
- Engine
- vLLM
- Context
- 262,144 tokens
Notes
What matters before you rebuild it.
- REAP-pruned
Sources
- github.com/jcartu/dsv4-flash-blackwell-inference-study/blob/main/GLM-5.2-504B.md#sustained-decode--aggregate-toks-30-scell
- github.com/jcartu/dsv4-flash-blackwell-inference-study/blob/main/GLM-5.2-504B.md#prefill--toks--ttft
- github.com/jcartu/dsv4-flash-blackwell-inference-study/blob/main/GLM-5.2-504B.md
- github.com/jcartu/dsv4-flash-blackwell-inference-study/blob/main/data/glm52_0xsero_benchmark_results_standard.json
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