Home / Models / Code Llama 13B Instruct / NVIDIA RTX 3060 8 GB

Calculated memory fit · not a benchmark

Can Code Llama 13B Instruct run on NVIDIA RTX 3060 8 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
Code Llama 13B Instruct · 13B
GPU
NVIDIA RTX 3060 8 GB · 8 GB advertised

Memory calculation

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

Model weights7.6 GB
KV cache6.3 GB
Runtime reserve0.9 GB
Safety margin0.5 GB
Required (estimated)15.2 GB
GPU usable VRAM7.2 GB

Result: CPU RAM OFFLOAD REQUIRED

Quantization table

Quantization2K4K8K16K
BF16NoNoNoNo
FP16NoNoNoNo
Q3OffloadOffloadOffloadOffload
Q4OffloadOffloadOffloadOffload
Q5OffloadOffloadOffloadOffload
Q6OffloadOffloadOffloadOffload
Q8OffloadOffloadOffloadOffload

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. RigForAI does not estimate tokens/sec in this release.

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 codellama/CodeLlama-13b-Instruct-hf (main). GPU/product specs: Icecat. Compatibility: RigForAI calculator v1.0.0 estimated VRAM · Q8 at 8K: CPU_RAM_OFFLOAD_REQUIRED. Amazon: affiliate commerce match, not a spec source.