Nemotron Orchestrator 8B DeepSeek V3.2 Speciale Distill — Hardware Requirements & GPU Compatibility
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Nemotron Orchestrator 8B DeepSeek V3.2 Speciale Distill is a 8.2B-parameter open language model from TeichAI in the DeepSeek V3 family. It supports a context window of up to 40,960 tokens. At Q4_K_M it needs about 5.52 GB of VRAM — see which GPUs and Macs can run it below.
12 downloads
4 likesSpecifications
- Publisher
- TeichAI
- Family
- DeepSeek V3
- Parameters
- 8.2B
- Architecture
- Qwen3ForCausalLM
- Context Length
- 40,960 tokens
- Vocabulary Size
- 151,936
- Release Date
- 2025-12-06
- License
- Apache 2.0
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How Much VRAM Does Nemotron Orchestrator 8B DeepSeek V3.2 Speciale Distill Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_K | 3.40 | 4.1 GB | 9.8 GB | 3.48 GB | 2-bit quantization with K-quant improvements |
| Q3_K_S | 3.50 | 4.2 GB | 9.9 GB | 3.58 GB | 3-bit small quantization |
| Q3_K_M | 3.90 | 4.6 GB | 10.3 GB | 3.99 GB | 3-bit medium quantization |
| Q4_K_M | 4.80 | 5.5 GB | 11.3 GB | 4.91 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_M | 5.70 | 6.4 GB | 12.2 GB | 5.84 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_K | 6.60 | 7.4 GB | 13.1 GB | 6.76 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 8.8 GB | 14.5 GB | 8.19 GB | 8-bit quantization, near-lossless |
Which GPUs Can Run Nemotron Orchestrator 8B DeepSeek V3.2 Speciale Distill?
Q4_K_M · 5.5 GBNemotron Orchestrator 8B DeepSeek V3.2 Speciale Distill (Q4_K_M) requires 5.5 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 8+ GB is recommended. Using the full 41K context window can add up to 5.7 GB, bringing total usage to 11.3 GB. 50 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti, NVIDIA GeForce RTX 3070 Ti.
Runs great
— Plenty of headroom
Decent
— Enough VRAM, may be tightWhich Devices Can Run Nemotron Orchestrator 8B DeepSeek V3.2 Speciale Distill?
Q4_K_M · 5.5 GB58 devices with unified memory can run Nemotron Orchestrator 8B DeepSeek V3.2 Speciale Distill, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, MacBook Air 13" M3 (8 GB).
Runs great
— Plenty of headroomWhere to Download Nemotron Orchestrator 8B DeepSeek V3.2 Speciale Distill
Community quantizations of this model — GGUF for llama.cpp, Ollama, and LM Studio, plus AWQ/MLX variants where available.
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Frequently Asked Questions
- How much VRAM does Nemotron Orchestrator 8B DeepSeek V3.2 Speciale Distill need?
Nemotron Orchestrator 8B DeepSeek V3.2 Speciale Distill requires 5.5 GB of VRAM at Q4_K_M, or 17.0 GB at BF16. Full 41K context adds up to 5.7 GB (11.3 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 8.2B × 4.8 bits ÷ 8 = 4.9 GB
KV Cache + Overhead ≈ 0.6 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 6.4 GB (at full 41K context)
VRAM usage by quantization
Q4_K_M5.5 GBQ4_K_M + full context11.3 GB- What's the best quantization for Nemotron Orchestrator 8B DeepSeek V3.2 Speciale Distill?
For Nemotron Orchestrator 8B DeepSeek V3.2 Speciale Distill, Q4_K_M (5.5 GB) offers the best balance of quality and VRAM usage. Q5_K_S (6.2 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 4.1 GB.
VRAM requirement by quantization
Q2_K4.1 GBQ3_K_L4.8 GBIQ4_NL5.2 GBQ4_K_M ★5.5 GBQ5_K_M6.4 GBBF1617.0 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Nemotron Orchestrator 8B DeepSeek V3.2 Speciale Distill on a Mac?
Nemotron Orchestrator 8B DeepSeek V3.2 Speciale Distill requires at least 4.1 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 Nemotron Orchestrator 8B DeepSeek V3.2 Speciale Distill locally?
Yes — Nemotron Orchestrator 8B DeepSeek V3.2 Speciale Distill can run locally on consumer hardware. At Q4_K_M quantization it needs 5.5 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Nemotron Orchestrator 8B DeepSeek V3.2 Speciale Distill?
At Q4_K_M, Nemotron Orchestrator 8B DeepSeek V3.2 Speciale Distill can reach ~797 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~119 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 ÷ 5.5 × 0.65 = ~942 tok/s
Estimated speed at Q4_K_M (5.5 GB)
~942 tok/s~119 tok/s~942 tok/s~797 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Nemotron Orchestrator 8B DeepSeek V3.2 Speciale Distill?
At Q4_K_M, the download is about 4.91 GB. The full-precision BF16 version is 16.38 GB. The smallest option (Q2_K) is 3.48 GB.
- Which GPUs can run Nemotron Orchestrator 8B DeepSeek V3.2 Speciale Distill?
50 consumer GPUs can run Nemotron Orchestrator 8B DeepSeek V3.2 Speciale Distill at Q4_K_M (5.5 GB). Top options include AMD Radeon RX 6700 XT, AMD Radeon RX 6800, AMD Radeon RX 6800 XT, AMD Radeon RX 7600. 39 GPUs have plenty of headroom for comfortable inference.
- Which devices can run Nemotron Orchestrator 8B DeepSeek V3.2 Speciale Distill?
59 devices with unified memory can run Nemotron Orchestrator 8B DeepSeek V3.2 Speciale Distill at Q4_K_M (5.5 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.