DeepSeek V3.2 Speciale — Hardware Requirements & GPU Compatibility
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DeepSeek V3.2 Speciale is a 685.4B-parameter open language model from DeepSeek in the DeepSeek V3 family. It supports a context window of up to 163,840 tokens. At Q4_K_M it needs about 415.12 GB of VRAM — see which GPUs and Macs can run it below.
12.2K downloads
708 likesSpecifications
- Publisher
- DeepSeek
- Family
- DeepSeek V3
- Parameters
- 685.4B
- Architecture
- DeepseekV32ForCausalLM
- Context Length
- 163,840 tokens
- Vocabulary Size
- 129,280
- License
- MIT
Get Started
HuggingFace
How Much VRAM Does DeepSeek V3.2 Speciale Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_K | 3.40 | 295.2 GB | 578.1 GB | 291.29 GB | 2-bit quantization with K-quant improvements |
| Q3_K_S | 3.50 | 303.7 GB | 586.7 GB | 299.86 GB | 3-bit small quantization |
| Q3_K_M | 3.90 | 338.0 GB | 621.0 GB | 334.13 GB | 3-bit medium quantization |
| Q4_0 | 4.00 | 346.6 GB | 629.5 GB | 342.70 GB | 4-bit legacy quantization |
| Q4_K_M | 4.80 | 415.1 GB | 698.1 GB | 411.24 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_M | 5.70 | 492.2 GB | 775.2 GB | 488.35 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_K | 6.60 | 569.3 GB | 852.3 GB | 565.45 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 689.3 GB | 972.3 GB | 685.40 GB | 8-bit quantization, near-lossless |
Which GPUs Can Run DeepSeek V3.2 Speciale?
Q4_K_M · 415.1 GBDeepSeek V3.2 Speciale (Q4_K_M) requires 415.1 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 540+ GB is recommended. Using the full 164K context window can add up to 283.0 GB, bringing total usage to 698.1 GB. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Which Devices Can Run DeepSeek V3.2 Speciale?
Q4_K_M · 415.1 GB2 devices with unified memory can run DeepSeek V3.2 Speciale, including NVIDIA DGX H100, NVIDIA DGX A100 640GB.
Runs great
— Plenty of headroomBenchmarks
View all 1 →Related Models
Frequently Asked Questions
- How much VRAM does DeepSeek V3.2 Speciale need?
DeepSeek V3.2 Speciale requires 415.1 GB of VRAM at Q4_K_M, or 689.3 GB at Q8_0. Full 164K context adds up to 283.0 GB (698.1 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 685.4B × 4.8 bits ÷ 8 = 411.2 GB
KV Cache + Overhead ≈ 3.9 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 286.9 GB (at full 164K context)
VRAM usage by quantization
Q4_K_M415.1 GBQ4_K_M + full context698.1 GB- Can NVIDIA GeForce RTX 5090 run DeepSeek V3.2 Speciale?
No — DeepSeek V3.2 Speciale requires at least 192.4 GB at IQ2_XXS, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.
- What's the best quantization for DeepSeek V3.2 Speciale?
For DeepSeek V3.2 Speciale, Q4_K_M (415.1 GB) offers the best balance of quality and VRAM usage. Q5_K_S (475.1 GB) provides better quality if you have the VRAM. The smallest option is IQ2_XXS at 192.4 GB.
VRAM requirement by quantization
IQ2_XXS192.4 GBQ3_K_S303.7 GBQ4_1389.4 GBQ4_K_M ★415.1 GBQ5_K_S475.1 GBQ8_0689.3 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run DeepSeek V3.2 Speciale on a Mac?
DeepSeek V3.2 Speciale requires at least 192.4 GB at IQ2_XXS, 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 DeepSeek V3.2 Speciale locally?
Yes — DeepSeek V3.2 Speciale can run locally on consumer hardware. At Q4_K_M quantization it needs 415.1 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- What's the download size of DeepSeek V3.2 Speciale?
At Q4_K_M, the download is about 411.24 GB. The full-precision Q8_0 version is 685.40 GB. The smallest option (IQ2_XXS) is 188.48 GB.
- Which GPUs can run DeepSeek V3.2 Speciale?
No single consumer GPU has enough VRAM to run DeepSeek V3.2 Speciale at Q4_K_M (415.1 GB). Multi-GPU or professional hardware is required.
- Which devices can run DeepSeek V3.2 Speciale?
2 devices with unified memory can run DeepSeek V3.2 Speciale at Q4_K_M (415.1 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.