DeepSeek V4 Flash Vision Exp — Hardware Requirements & GPU Compatibility
Vision
DeepSeek V4 Flash Vision Exp is an experimental multimodal model from DeepSeek, a mixture-of-experts design with roughly 304.6 billion total parameters, only a small fraction of which are active per token. It extends the text-only DeepSeek V4 Flash line with image understanding, built for agentic tasks, reasoning, and tool use. Only the active parameters are computed per token, keeping decoding fast, but all weights must fit in memory, making this a server-class model best run across multiple GPUs or a hosted endpoint. The model supports a 1,048,576 token context window, suited to very long documents or codebases. It is released under the MIT license, one of the most permissive open licenses, with no restrictions on commercial use. Published in August 2026 as an experimental release, it brings image input to the Flash line.
866.0K downloads
926 likesSpecifications
- Publisher
- DeepSeek
- Family
- DeepSeek V4
- Parameters
- 304.6B
- Architecture
- DeepseekV4ForCausalLM
- Context Length
- 1,048,576 tokens
- Vocabulary Size
- 129,280
- Release Date
- 2026-08-31
- License
- MIT
Get Started
HuggingFace
How Much VRAM Does DeepSeek V4 Flash Vision Exp Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_K | 3.40 | 129.8 GB | 141.3 GB | 129.47 GB | 2-bit quantization with K-quant improvements |
| Q3_K_Mest. | 3.90 | 148.8 GB | 160.4 GB | 148.52 GB | 3-bit medium quantization |
| Q4_K_Mest. | 4.80 | 183.1 GB | 194.6 GB | 182.79 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_Mest. | 5.70 | 217.4 GB | 228.9 GB | 217.06 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_Kest. | 6.60 | 251.7 GB | 263.2 GB | 251.33 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 305.0 GB | 316.5 GB | 304.65 GB | 8-bit quantization, near-lossless |
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 Vision Exp?
Q4_K_M · 183.1 GBDeepSeek V4 Flash Vision Exp (Q4_K_M) requires 183.1 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 239+ GB is recommended. Using the full 1049K context window can add up to 11.5 GB, bringing total usage to 194.6 GB. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Which Devices Can Run DeepSeek V4 Flash Vision Exp?
Q4_K_M · 183.1 GB6 devices with unified memory can run DeepSeek V4 Flash Vision Exp, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Studio (M3 Ultra, 256GB).
Runs great
— Plenty of headroom
Decent
— Enough memory, may be tightWhere to Download DeepSeek V4 Flash Vision Exp
Community quantizations of this model — GGUF for llama.cpp, Ollama, and LM Studio, plus AWQ/MLX variants where available.
Benchmarks
Benchmark details →Related Models
Frequently Asked Questions
- How much VRAM does DeepSeek V4 Flash Vision Exp need?
DeepSeek V4 Flash Vision Exp requires 183.1 GB of VRAM at Q4_K_M, or 609.6 GB at BF16. Full 1049K context adds up to 11.5 GB (194.6 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 304.6B × 4.8 bits ÷ 8 = 182.8 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_M183.1 GBQ4_K_M + full context194.6 GB- Can NVIDIA GeForce RTX 5090 run DeepSeek V4 Flash Vision Exp?
No — DeepSeek V4 Flash Vision Exp requires at least 84.1 GB at IQ2_XXS, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.
- What's the best quantization for DeepSeek V4 Flash Vision Exp?
For DeepSeek V4 Flash Vision Exp, Q4_K_M (183.1 GB) offers the best balance of quality and VRAM usage. Q5_K_M (217.4 GB) provides better quality if you have the VRAM. The smallest option is IQ2_XXS at 84.1 GB.
VRAM requirement by quantization
IQ2_XXS84.1 GBQ2_K_S122.2 GBQ3_K_M148.8 GBQ4_K_M ★183.1 GBQ5_K_M217.4 GBBF16609.6 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run DeepSeek V4 Flash Vision Exp on a Mac?
DeepSeek V4 Flash Vision Exp requires at least 84.1 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 V4 Flash Vision Exp locally?
Yes — DeepSeek V4 Flash Vision Exp can run locally on consumer hardware. At Q4_K_M quantization it needs 183.1 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is DeepSeek V4 Flash Vision Exp?
At Q4_K_M, DeepSeek V4 Flash Vision Exp can reach ~95 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 ÷ 183.1 × 0.65 = ~242 tok/s
Estimated speed at Q4_K_M (183.1 GB)
~242 tok/s~242 tok/s~95 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 Vision Exp?
At Q4_K_M, the download is about 182.79 GB. The full-precision BF16 version is 609.29 GB. The smallest option (IQ2_XXS) is 83.78 GB.
- Which GPUs can run DeepSeek V4 Flash Vision Exp?
No single consumer GPU has enough VRAM to run DeepSeek V4 Flash Vision Exp at Q4_K_M (183.1 GB). Multi-GPU or professional hardware is required.
- Which devices can run DeepSeek V4 Flash Vision Exp?
6 devices with unified memory can run DeepSeek V4 Flash Vision Exp at Q4_K_M (183.1 GB), including Mac Pro M2 Ultra (192 GB), Mac Studio (M3 Ultra, 256GB), Mac Studio (M3 Ultra, 512GB), Mac Studio M2 Ultra (192 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.