Deepseek AI Deepseek Coder V2 Lite Instruct speed on RTX 3080 and quantization-level VRAM fit.
RTX 3080 meets the minimum VRAM requirement for Q4 inference of Deepseek AI Deepseek Coder V2 Lite Instruct. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.
RTX 3080 can run Deepseek AI Deepseek Coder V2 Lite Instruct with Q4 quantization. At approximately 86 tokens/second, you can expect Good speed - acceptable for interactive use.
VRAM usage will be very close to your GPU's limit. Consider closing other applications or using Q3 quantization for more margin.
| Quantization | VRAM needed | VRAM available | Estimated speed | Verdict |
|---|---|---|---|---|
| Q4 | 8GB | 10GB | 86.41 tok/s | ✅ Fits comfortably |
| Q8 | 16GB | 10GB | 60.49 tok/s | ❌ Not recommended |
| FP16 | 32GB | 10GB | 32.84 tok/s | ❌ Not recommended |
Need a GPU with 8GB+ VRAM? These guides match your requirements.
Check current pricing links for RTX 3080 and similar cards.
Open RTX 3080 buy links →Use workload-focused recommendations before committing to a purchase.
Browse best GPU guides →Compare complete systems if you want ready-to-run hardware.
Compare prebuilt systems →Rent cloud GPUs by the hour — no upfront hardware cost.
RTX 3080 can run Deepseek AI Deepseek Coder V2 Lite Instruct at Q4 with an estimated 86 tok/s.
Q4 inference is estimated to need about 8GB VRAM on this page, while RTX 3080 has 10GB available.
If you need more speed or context headroom, compare alternative GPUs below and check higher-tier VRAM options.