Dpo Selective Redteaming — Hardware Requirements & GPU Compatibility
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Dpo Selective Redteaming is a 7.2B-parameter open language model from wxzhang. It supports a context window of up to 32,768 tokens. At Q4_K_M it needs about 4.91 GB of VRAM — see which GPUs and Macs can run it below.
23 downloads
1 likesSpecifications
- Publisher
- wxzhang
- Parameters
- 7.2B
- Architecture
- MistralForCausalLM
- Context Length
- 32,768 tokens
- Vocabulary Size
- 32,000
- Release Date
- 2024-04-23
- License
- MIT
Get Started
HuggingFace
How Much VRAM Does Dpo Selective Redteaming Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_Kest. | 3.40 | 3.6 GB | 7.7 GB | 3.08 GB | 2-bit quantization with K-quant improvements |
| Q3_K_Mest. | 3.90 | 4.1 GB | 8.1 GB | 3.53 GB | 3-bit medium quantization |
| Q4_K_Mest. | 4.80 | 4.9 GB | 8.9 GB | 4.35 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_Mest. | 5.70 | 5.7 GB | 9.8 GB | 5.16 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_Kest. | 6.60 | 6.5 GB | 10.6 GB | 5.97 GB | 6-bit quantization, very good quality |
| Q8_0est. | 8.00 | 7.8 GB | 11.8 GB | 7.24 GB | 8-bit quantization, near-lossless |
| BF16est. | 16.00 | 15.1 GB | 19.1 GB | 14.48 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 Dpo Selective Redteaming?
Q4_K_M · 4.9 GBDpo Selective Redteaming (Q4_K_M) requires 4.9 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 7+ GB is recommended. Using the full 33K context window can add up to 4.0 GB, bringing total usage to 8.9 GB. 52 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.
Runs great
— Plenty of headroomWhich Devices Can Run Dpo Selective Redteaming?
Q4_K_M · 4.9 GB59 devices with unified memory can run Dpo Selective Redteaming, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Apple iPhone 17 Pro.
Runs great
— Plenty of headroom
Decent
— Enough memory, may be tightRelated Models
Frequently Asked Questions
- How much VRAM does Dpo Selective Redteaming need?
Dpo Selective Redteaming requires 4.9 GB of VRAM at Q4_K_M, or 15.1 GB at BF16. Full 33K context adds up to 4.0 GB (8.9 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 7.2B × 4.8 bits ÷ 8 = 4.3 GB
KV Cache + Overhead ≈ 0.6 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 4.6 GB (at full 33K context)
VRAM usage by quantization
Q4_K_M4.9 GBQ4_K_M + full context8.9 GB- What's the best quantization for Dpo Selective Redteaming?
For Dpo Selective Redteaming, Q4_K_M (4.9 GB) offers the best balance of quality and VRAM usage. Q5_K_M (5.7 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 3.6 GB.
VRAM requirement by quantization
Q2_K3.6 GBQ4_K_M ★4.9 GBQ5_K_M5.7 GBQ6_K6.5 GBQ8_07.8 GBBF1615.1 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Dpo Selective Redteaming on a Mac?
Dpo Selective Redteaming requires at least 3.6 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 Dpo Selective Redteaming locally?
Yes — Dpo Selective Redteaming can run locally on consumer hardware. At Q4_K_M quantization it needs 4.9 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Dpo Selective Redteaming?
At Q4_K_M, Dpo Selective Redteaming can reach ~978 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~133 tok/s. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: NVIDIA B200 → 8000 ÷ 4.9 × 0.65 = ~1059 tok/s
Estimated speed at Q4_K_M (4.9 GB)
~1059 tok/s~133 tok/s~1059 tok/s~978 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Dpo Selective Redteaming?
At Q4_K_M, the download is about 4.35 GB. The full-precision BF16 version is 14.48 GB. The smallest option (Q2_K) is 3.08 GB.
- Which GPUs can run Dpo Selective Redteaming?
52 consumer GPUs can run Dpo Selective Redteaming at Q4_K_M (4.9 GB). Top options include AMD Radeon RX 6700 XT, AMD Radeon RX 6800, AMD Radeon RX 6800 XT. 52 GPUs have plenty of headroom for comfortable inference.
- Which devices can run Dpo Selective Redteaming?
59 devices with unified memory can run Dpo Selective Redteaming at Q4_K_M (4.9 GB), including AMD Ryzen AI 9 HX 370 (Strix Point) Laptop, ASUS Ascent GX10, Apple iPhone 17 Pro, Asus ROG Flow Z13 (2025, Ryzen AI Max+ 395, 128 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.