DeepSeek V4 Flash 162B — Hardware Requirements & GPU Compatibility
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DeepSeek V4 Flash 162B is a 92.2B-parameter open language model from 0xSero in the DeepSeek V4 family. It supports a context window of up to 1,048,576 tokens. At Q4_K_M it needs about 55.62 GB of VRAM — see which GPUs and Macs can run it below.
811 downloads
12 likesSpecifications
- Publisher
- 0xSero
- Family
- DeepSeek V4
- Parameters
- 92.2B
- Architecture
- DeepseekV4ForCausalLM
- Context Length
- 1,048,576 tokens
- Vocabulary Size
- 129,280
- Release Date
- 2026-05-27
- License
- MIT
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HuggingFace
How Much VRAM Does DeepSeek V4 Flash 162B Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_Kest. | 3.40 | 39.5 GB | 51.0 GB | 39.17 GB | 2-bit quantization with K-quant improvements |
| Q3_K_Mest. | 3.90 | 45.3 GB | 56.8 GB | 44.93 GB | 3-bit medium quantization |
| Q4_K_Mest. | 4.80 | 55.6 GB | 67.1 GB | 55.30 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_Mest. | 5.70 | 66.0 GB | 77.5 GB | 65.67 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_Kest. | 6.60 | 76.4 GB | 87.9 GB | 76.04 GB | 6-bit quantization, very good quality |
| Q8_0est. | 8.00 | 92.5 GB | 104.0 GB | 92.17 GB | 8-bit quantization, near-lossless |
| BF16est. | 16.00 | 184.7 GB | 196.2 GB | 184.33 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 DeepSeek V4 Flash 162B?
Q4_K_M · 55.6 GBDeepSeek V4 Flash 162B (Q4_K_M) requires 55.6 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 73+ GB is recommended. Using the full 1049K context window can add up to 11.5 GB, bringing total usage to 67.1 GB. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Which Devices Can Run DeepSeek V4 Flash 162B?
Q4_K_M · 55.6 GB22 devices with unified memory can run DeepSeek V4 Flash 162B, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Studio (M3 Ultra, 96GB).
Runs great
— Plenty of headroom
Where to Download DeepSeek V4 Flash 162B
Community quantizations of this model — GGUF for llama.cpp, Ollama, and LM Studio, plus AWQ/MLX variants where available.
Related Models
Frequently Asked Questions
- How much VRAM does DeepSeek V4 Flash 162B need?
DeepSeek V4 Flash 162B requires 55.6 GB of VRAM at Q4_K_M, or 184.7 GB at BF16. Full 1049K context adds up to 11.5 GB (67.1 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 92.2B × 4.8 bits ÷ 8 = 55.3 GB
KV Cache + Overhead ≈ 0.3 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 11.8 GB (at full 1049K context)
VRAM usage by quantization
Q4_K_M55.6 GBQ4_K_M + full context67.1 GB- Can NVIDIA GeForce RTX 5090 run DeepSeek V4 Flash 162B?
No — DeepSeek V4 Flash 162B requires at least 39.5 GB at Q2_K, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.
- What's the best quantization for DeepSeek V4 Flash 162B?
For DeepSeek V4 Flash 162B, Q4_K_M (55.6 GB) offers the best balance of quality and VRAM usage. Q5_K_M (66.0 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 39.5 GB.
VRAM requirement by quantization
Q2_K39.5 GBQ4_K_M ★55.6 GBQ5_K_M66.0 GBQ6_K76.4 GBQ8_092.5 GBBF16184.7 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run DeepSeek V4 Flash 162B on a Mac?
DeepSeek V4 Flash 162B requires at least 39.5 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 DeepSeek V4 Flash 162B locally?
Yes — DeepSeek V4 Flash 162B can run locally on consumer hardware. At Q4_K_M quantization it needs 55.6 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is DeepSeek V4 Flash 162B?
At Q4_K_M, DeepSeek V4 Flash 162B can reach ~79 tok/s on AMD Instinct MI350X. 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 ÷ 55.6 × 0.65 = ~94 tok/s
Estimated speed at Q4_K_M (55.6 GB)
~94 tok/s~94 tok/s~79 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of DeepSeek V4 Flash 162B?
At Q4_K_M, the download is about 55.30 GB. The full-precision BF16 version is 184.33 GB. The smallest option (Q2_K) is 39.17 GB.
- Which GPUs can run DeepSeek V4 Flash 162B?
No single consumer GPU has enough VRAM to run DeepSeek V4 Flash 162B at Q4_K_M (55.6 GB). Multi-GPU or professional hardware is required.
- Which devices can run DeepSeek V4 Flash 162B?
23 devices with unified memory can run DeepSeek V4 Flash 162B at Q4_K_M (55.6 GB), including ASUS Ascent GX10, Asus ROG Flow Z13 (2025, Ryzen AI Max+ 395, 128 GB), Beelink GTR9 Pro (Ryzen AI Max+ 395, 128 GB), Framework Desktop (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.