Best local LLM for coding with 32GB VRAM
The models people report running for coding on setups with more than 24 GB and up to 32 GB of memory, such as RTX 5090, Radeon AI PRO R9700 32GB, AMD MI50 32GB or V100 32GB. Each row shows the fastest coding run reported for that model in this band.
Ranked from 18 coding reports on llamaperf.
Ranked by community reports
| # | Model | Fastest run | Median t/s | Fastest t/s | Reports |
|---|---|---|---|---|---|
| 1 | Qwen3.8Alibaba | 27B · NVFP4 on RTX 5090 | 104 | 201 | 10 |
| 2 | Qwen3.6Alibaba | 35B · 3B active · Q5_K_M on Radeon AI PRO R9700 32GB | 74 | 84 | 5 |
| 3 | MuseMeta | 30B · UD-Q5_K_M on RTX 5090 | 189 | 253 | 2 |
| 4 | DeepSeek V4 FlashDeepSeek | 284B · 13B active on RTX 5090 | 14 | 14 | 1 |
Frequently asked
What is the best local LLM for coding with 32GB of VRAM?
Ranked from community reports on setups with more than 24 GB and up to 32 GB of memory, Qwen3.8 has the strongest record, followed by Qwen3.6 and Muse. 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 32GB?
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.