Deepseek Coder 6.7B Instruct — Hardware Requirements & GPU Compatibility
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DeepSeek Coder 6.7B Instruct is a first-generation code-specialized model trained on a large corpus of source code and programming-related data. At 6.7 billion parameters, it provides solid code completion, generation, and explanation capabilities across popular programming languages while remaining small enough to run on most consumer GPUs. While newer models in the DeepSeek lineup have surpassed it in raw capability, this model remains a practical choice for users who need a lightweight local coding assistant with minimal hardware requirements. It runs well on GPUs with as little as 6 GB of VRAM when quantized.
127.0K downloads
481 likesSpecifications
- Publisher
- DeepSeek
- Family
- DeepSeek Coder
- Parameters
- 6.7B
- Architecture
- LlamaForCausalLM
- Context Length
- 16,384 tokens
- Vocabulary Size
- 32,256
- Release Date
- 2024-02-02
- License
- Other
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HuggingFace
How Much VRAM Does Deepseek Coder 6.7B Instruct Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| BF16 | 16.00 | 14.8 GB | 22.4 GB | 13.48 GB | Brain floating point 16 — preferred for training |
Which GPUs Can Run Deepseek Coder 6.7B Instruct?
BF16 · 14.8 GBDeepseek Coder 6.7B Instruct (BF16) requires 14.8 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 20+ GB is recommended. Using the full 16K context window can add up to 7.5 GB, bringing total usage to 22.4 GB. 17 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti, NVIDIA GeForce RTX 5080.
Runs great
— Plenty of headroom
Decent
— Enough VRAM, may be tightWhich Devices Can Run Deepseek Coder 6.7B Instruct?
BF16 · 14.8 GB27 devices with unified memory can run Deepseek Coder 6.7B Instruct, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Mini M4 (16 GB).
Runs great
— Plenty of headroomRelated Models
Frequently Asked Questions
- How much VRAM does Deepseek Coder 6.7B Instruct need?
Deepseek Coder 6.7B Instruct requires 14.8 GB of VRAM at BF16. Full 16K context adds up to 7.5 GB (22.4 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 6.7B × 16 bits ÷ 8 = 13.5 GB
KV Cache + Overhead ≈ 1.3 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 8.9 GB (at full 16K context)
VRAM usage by quantization
BF1614.8 GBBF16 + full context22.4 GB- Can I run Deepseek Coder 6.7B Instruct on a Mac?
Deepseek Coder 6.7B Instruct requires at least 14.8 GB at BF16, 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 Coder 6.7B Instruct locally?
Yes — Deepseek Coder 6.7B Instruct can run locally on consumer hardware. At BF16 quantization it needs 14.8 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Deepseek Coder 6.7B Instruct?
At BF16, Deepseek Coder 6.7B Instruct can reach ~196 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~44 tok/s. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: AMD Instinct MI300X → 5300 ÷ 14.8 × 0.55 = ~196 tok/s
Estimated speed at BF16 (14.8 GB)
AMD Instinct MI300X~196 tok/sNVIDIA GeForce RTX 4090~44 tok/sNVIDIA H100 SXM~147 tok/sAMD Instinct MI250X~121 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Deepseek Coder 6.7B Instruct?
At BF16, the download is about 13.48 GB.