Home / Models / DeepSeek Coder 33B Instruct / NVIDIA RTX 3060 12 GB

Calculated memory fit · performance is a separate section

Can DeepSeek Coder 33B Instruct run on NVIDIA RTX 3060 12 GB?

Can it run? Yes, with CPU/RAM offload. Full GPU fit? No.

Can it run?

Can it run?
Yes, with CPU/RAM offload. This is not equivalent to full-GPU inference.
Full GPU fit?
No
Model
DeepSeek Coder 33B Instruct · 33B
GPU
NVIDIA RTX 3060 12 GB · 12 GB advertised

What else can NVIDIA RTX 3060 12 GB run? · Find other GPUs for DeepSeek Coder 33B Instruct · See 2× multi-GPU options

Memory calculation

Breakdown for Q4 at 8K context, batch size 1. Calculator v1.0.0.

Model weights19.6 GB
KV cache1.9 GB
Runtime reserve1.5 GB
Safety margin0.8 GB
Required (estimated)23.8 GB
GPU usable VRAM10.8 GB

Result: CPU RAM OFFLOAD REQUIRED

Quantization table

Quantization2K4K8K16K
BF16NoNoNoNo
FP16NoNoNoNo
Q3OffloadOffloadOffloadOffload
Q4OffloadOffloadOffloadOffload
Q5OffloadOffloadOffloadOffload
Q6NoNoNoNo
Q8NoNoNoNo

What fits entirely in VRAM?

No calculated full-VRAM fit at the evaluated quantizations and context lengths.

What requires RAM offload?

Weights may run with CPU/RAM offload. That is not equivalent to full-GPU inference. Performance numbers below are only published for full-VRAM fits.

Performance

No llama.cpp performance result is published for this pair yet. Memory fit above is unchanged. How performance is calculated

Available graphics cards

These SKUs use this GPU chip. Amazon CTAs appear only for EXACT/HIGH matches. Absence of a price does not change the compatibility result above.

Check price on Amazon

Sources

Model: official config deepseek-ai/deepseek-coder-33b-instruct (main). GPU/product specs: Icecat. Compatibility: RigForAI calculator v1.0.0 estimated VRAM · Q8 at 8K: DOES_NOT_FIT. Amazon: affiliate commerce match, not a spec source.