CodingAI CodingAI Building15.7B
DeepSeek Coder V2 Lite 16B
DeepSeek · DeepSeek License
MoE architecture — 15.7B total, ~2.4B active per token. Excellent code generation and completion. Extremely fast inference despite total param count. One of the best coding models for its effective size.
- Parameters
- 15.7B
- Context
- 163,840 tokens
- Released
- 2024-06-17
- Engines
- llama.cpp, ollama, vLLM
- Builder Tools
- Cursor, Continue, Aider, Windsurf
DeepSeek Coder V2 Lite 16B (15.7B) requires 10.9 GB VRAM at recommended quality (Q5_K_M). At efficient quality (Q4_K_M), it fits in 9.1 GB VRAM, making it compatible with the NVIDIA GeForce RTX 3060 12GB. On NVIDIA GeForce RTX 4090, expect approximately 55 tok/s at Q5_K_M. For the best experience, Starter AI Desktop ($582) is recommended.
— OwnRig methodology, data updated 2026-03-01
VRAM Requirements
| Quality | Quantization | VRAM | File Size |
|---|---|---|---|
| full | Q8_0 | 16.9 GB | 15.7 GB |
| recommended | Q5_K_M | 10.9 GB | 9.4 GB |
| efficient | Q4_K_M | 9.1 GB | 7.9 GB |
| compressed | Q3_K_M | 7.4 GB | 6.1 GB |
Context Length Impact
KV cache VRAM at Q5_K_M quality. Longer context = more memory.
| Context | KV Cache | Total VRAM |
|---|---|---|
| 2K | 205 MB | 11.1 GB |
| 4K | 410 MB | 11.3 GB |
| 8K | 819 MB | 11.7 GB |
| 16K | 1.5 GB | 12.4 GB |
| 32K | 3.1 GB | 14 GB |
| 64K | 6.1 GB | 17 GB |
| 128K | 12.3 GB | 23.2 GB |
Compatible GPUs
Performance data for DeepSeek Coder V2 Lite 16B across different hardware.
| Device | Quantization | Speed | Rating | Fits in VRAM |
|---|---|---|---|---|
| NVIDIA GeForce RTX 3060 12GB | Q4_K_M | 40 tok/s | Good | ✓ |
| NVIDIA GeForce RTX 4060 Ti 16GB | Q5_K_M | 50 tok/s | Excellent | ✓ |
| NVIDIA GeForce RTX 4090 | Q5_K_M | 55 tok/s | Excellent | ✓ |
| Apple M4 Max (36GB Unified) | Q5_K_M | 35 tok/s | Good | ✓ |
| NVIDIA GeForce RTX 4060 8GB | Q3_K_M | 45 tok/s | Good | ✓ |
| NVIDIA GeForce RTX 4070 Ti 12GB | Q4_K_M | 55 tok/s | Excellent | ✓ |
| NVIDIA GeForce RTX 3080 10GB | Q4_K_M | 55 tok/s | Excellent | ✓ |
| Apple M3 Pro (18GB Unified) | Q4_K_M | 20 tok/s | Good | ✓ |
Builder Context
DeepSeek Coder V2 Lite 16B is commonly used with Cursor, Continue, Aider, Windsurf. For an AI coding workflow, pair it with an embedding model like nomic-embed-text for local RAG.
Recommended Builds
Complete PC builds that can run DeepSeek Coder V2 Lite 16B.
Frequently Asked Questions
- How much VRAM does DeepSeek Coder V2 Lite 16B need?
- DeepSeek Coder V2 Lite 16B requires 10.9 GB VRAM at recommended quality (Q5_K_M). At lower quality settings, it can fit in as little as 7.4 GB.
- What is the best GPU for DeepSeek Coder V2 Lite 16B?
- The NVIDIA GeForce RTX 4090 delivers the best performance for DeepSeek Coder V2 Lite 16B, achieving 55 tok/s at Q5_K_M with an excellent rating.
- Can I run DeepSeek Coder V2 Lite 16B on an RTX 4060 Ti?
- Yes. On the NVIDIA GeForce RTX 4060 Ti 16GB, DeepSeek Coder V2 Lite 16B runs at 50 tok/s (Q5_K_M, excellent).
- What quantization should I use for DeepSeek Coder V2 Lite 16B?
- For the best quality, use Q5_K_M (10.9 GB VRAM). If your GPU has limited VRAM, Q3_K_M (7.4 GB) is the most efficient option with acceptable quality.
- Is DeepSeek Coder V2 Lite 16B good for coding?
- Yes. DeepSeek Coder V2 Lite 16B is used with Cursor, Continue, Aider, Windsurf for local AI coding. For the best coding experience, pair it with an embedding model for local RAG.
Data confidence: verified. Last updated: 2026-03-01. Source