SuperGLM 5.2 W4W8 Abliterated DCP4 600K K6 — Hardware Requirements & GPU Compatibility
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SuperGLM 5.2 W4W8 Abliterated DCP4 600K K6 is a 785.0B-parameter open language model from OxTank in the GLM 5 family. At Q4_K_M it needs about 518.08 GB of VRAM — see which GPUs and Macs can run it below.
81 downloads
2 likesSpecifications
- Publisher
- OxTank
- Family
- GLM 5
- Parameters
- 785.0B
- Release Date
- 2026-07-15
- License
- MIT
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How Much VRAM Does SuperGLM 5.2 W4W8 Abliterated DCP4 600K K6 Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_Kest. | 3.40 | 367.0 GB | — | 333.62 GB | 2-bit quantization with K-quant improvements |
| Q3_K_Mest. | 3.90 | 420.9 GB | — | 382.68 GB | 3-bit medium quantization |
| Q4_K_Mest. | 4.80 | 518.1 GB | — | 470.99 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_Mest. | 5.70 | 615.2 GB | — | 559.30 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_Kest. | 6.60 | 712.4 GB | — | 647.61 GB | 6-bit quantization, very good quality |
| Q8_0est. | 8.00 | 863.5 GB | — | 784.98 GB | 8-bit quantization, near-lossless |
| BF16est. | 16.00 | 1727.0 GB | — | 1569.95 GB | Brain floating point 16 — preferred for training |
est.= calculated VRAM estimate; no published GGUF file found for that quantization yet. Other rows are verified against real community uploads.
Which GPUs Can Run SuperGLM 5.2 W4W8 Abliterated DCP4 600K K6?
Q4_K_M · 518.1 GBSuperGLM 5.2 W4W8 Abliterated DCP4 600K K6 (Q4_K_M) requires 518.1 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 674+ GB is recommended. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Which Devices Can Run SuperGLM 5.2 W4W8 Abliterated DCP4 600K K6?
Q4_K_M · 518.1 GB2 devices with unified memory can run SuperGLM 5.2 W4W8 Abliterated DCP4 600K K6, including NVIDIA DGX H100.
Decent
— Enough memory, may be tightRelated Models
Frequently Asked Questions
- How much VRAM does SuperGLM 5.2 W4W8 Abliterated DCP4 600K K6 need?
SuperGLM 5.2 W4W8 Abliterated DCP4 600K K6 requires 518.1 GB of VRAM at Q4_K_M, or 1727.0 GB at BF16.
VRAM = Weights + KV Cache + Overhead
Weights = 785.0B × 4.8 bits ÷ 8 = 471 GB
KV Cache + Overhead ≈ 47.1 GB (at 2K context + ~0.3 GB framework)
VRAM usage by quantization
Q4_K_M518.1 GB- Can NVIDIA GeForce RTX 5090 run SuperGLM 5.2 W4W8 Abliterated DCP4 600K K6?
No — SuperGLM 5.2 W4W8 Abliterated DCP4 600K K6 requires at least 367.0 GB at Q2_K, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.
- What's the best quantization for SuperGLM 5.2 W4W8 Abliterated DCP4 600K K6?
For SuperGLM 5.2 W4W8 Abliterated DCP4 600K K6, Q4_K_M (518.1 GB) offers the best balance of quality and VRAM usage. Q5_K_M (615.2 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 367.0 GB.
VRAM requirement by quantization
Q2_K367.0 GBQ4_K_M ★518.1 GBQ5_K_M615.2 GBQ6_K712.4 GBQ8_0863.5 GBBF161727.0 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run SuperGLM 5.2 W4W8 Abliterated DCP4 600K K6 on a Mac?
SuperGLM 5.2 W4W8 Abliterated DCP4 600K K6 requires at least 367.0 GB at Q2_K, which exceeds the unified memory of most consumer Macs. You would need a Mac Studio or Mac Pro with a high-memory configuration.
- Can I run SuperGLM 5.2 W4W8 Abliterated DCP4 600K K6 locally?
Yes — SuperGLM 5.2 W4W8 Abliterated DCP4 600K K6 can run locally on consumer hardware. At Q4_K_M quantization it needs 518.1 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- What's the download size of SuperGLM 5.2 W4W8 Abliterated DCP4 600K K6?
At Q4_K_M, the download is about 470.99 GB. The full-precision BF16 version is 1569.95 GB. The smallest option (Q2_K) is 333.62 GB.
- Which GPUs can run SuperGLM 5.2 W4W8 Abliterated DCP4 600K K6?
No single consumer GPU has enough VRAM to run SuperGLM 5.2 W4W8 Abliterated DCP4 600K K6 at Q4_K_M (518.1 GB). Multi-GPU or professional hardware is required.
- Which devices can run SuperGLM 5.2 W4W8 Abliterated DCP4 600K K6?
2 devices with unified memory can run SuperGLM 5.2 W4W8 Abliterated DCP4 600K K6 at Q4_K_M (518.1 GB), including NVIDIA DGX A100 640GB, NVIDIA DGX H100. Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.