DeepSeek Coder V2 Lite (16B)

Positioning

The right coder when 8–12 GB VRAM is the constraint. DeepSeek Coder V2 Lite is a 16B MoE with only 2.4B active per token — runtime is fast (>100 tok/s on a 4090) and quality is excellent for the size class.

Strengths

• 2.4B active per token — autocomplete-fast even on mid-tier GPUs.
• DeepSeek license — clean for commercial use.
• Strong fill-in-the-middle comparable to Codestral 22B at lower VRAM.

Limitations

• MoE total memory still ~10 GB at Q4 — not as VRAM-frugal as the active-parameter count suggests.
• Qwen 2.5 Coder 32B is stronger when VRAM allows.
• Long-context behavior less polished than dedicated long-context coders.

Real-world performance on RTX 4090

• Q4_K_M (10 GB): 110–135 tok/s decode (active params keep this fast)
• Q5_K_M (12 GB): 95–115 tok/s
• Q8_0 (17.5 GB): 70–88 tok/s

Should you run this locally?

Yes, for 12–16 GB VRAM coders who want autocomplete speed without sacrificing quality. No, for 24 GB+ owners — Qwen 2.5 Coder 32B is materially stronger.

How it compares

• vs Qwen 2.5 Coder 32B → Qwen is stronger; DeepSeek Coder V2 Lite is faster and lower VRAM.
• vs Codestral 22B → Codestral has higher ceiling; DeepSeek Coder V2 Lite has MoE speed advantage.
• vs CodeGemma 7B → DeepSeek Coder V2 Lite wins on quality; CodeGemma wins on absolute VRAM minimum.

Run this yourself

ollama pull deepseek-coder-v2:lite-instruct-q4_K_M
ollama run deepseek-coder-v2:lite-instruct-q4_K_M

Settings: Q4_K_M GGUF, 16384 ctx, full GPU on RTX 3060 12 GB / 4060 Ti / 4090