llamaperf

Best local LLM for coding with 16GB VRAM

The models people report running for coding on setups with more than 12 GB and up to 16 GB of memory, such as RTX 5060 Ti 16GB, RTX 5070 Ti, RTX 4060 Ti 16GB or RTX 5080. Each row shows the fastest coding run reported for that model in this band.

Ranked from 19 coding reports on llamaperf.

Ranked by community reports

#ModelFastest runMedian t/sFastest t/sReports
1Qwen3.8Alibaba27B · NVFP4 on RTX 5060 Ti 16GB286711
2Qwen3.6Alibaba35B · 3B active · Q4_K_XL on RTX 508052565
3Gemma 4Google DeepMind12B · Q5_K_XL50501
4Ornith1.59B · Q6_K36361
5MuseMeta30B · UD-Q2-K-XL20201

Frequently asked

What is the best local LLM for coding with 16GB of VRAM?

Ranked from community reports on setups with more than 12 GB and up to 16 GB of memory, Qwen3.8 has the strongest record, followed by Qwen3.6 and Gemma 4. The table shows the quant and GPU of each model's fastest coding run so you can copy a setup that is known to work.

What counts as a coding report?

A community performance report whose poster described using the model for coding: an editor assistant, an agent, or code generation. The memory band is the poster's reported VRAM, or the card's VRAM times the number of cards.

Which quant should I use for coding on 16GB?

Start from the quant in the fastest run column, which is one that is known to fit with room for a coding context. If you want a bigger model in the same memory, step down one quant rung; the VRAM calculator shows the exact memory at each rung for your card.

How we rank

Families are scored on report count, the fastest generation speed within this memory band, recency, and how complete the best report is. Reports come from r/LocalLLaMA and direct submissions. Nothing is sponsored.