Best local LLM for coding with 48GB VRAM
The models people report running for coding on setups with more than 32 GB and up to 48 GB of memory, such as RTX 6000, M4 Pro 48GB, M5 Pro 48GB or RTX A6000 48GB. Each row shows the fastest coding run reported for that model in this band.
Ranked from 11 coding reports on llamaperf.
Ranked by community reports
| # | Model | Fastest run | Median t/s | Fastest t/s | Reports |
|---|---|---|---|---|---|
| 1 | Qwen3.8Alibaba | 27B · FP8 on RTX 4090 | 58 | 68 | 7 |
| 2 | Qwen2.5Alibaba | 27B · Q6_K_XL on RTX 3090 | 70 | 70 | 1 |
| 3 | Qwen3.6Alibaba | 27B · FP8 | 80 | 80 | 1 |
| 4 | DeepSeek V4 FlashDeepSeek | 9B · Q4_K_M on M5 Pro 48GB | 44 | 44 | 1 |
| 5 | MuseMeta | 30B · 8-bit on M4 Pro 48GB | 18 | 18 | 1 |
Frequently asked
What is the best local LLM for coding with 48GB of VRAM?
Ranked from community reports on setups with more than 32 GB and up to 48 GB of memory, Qwen3.8 has the strongest record, followed by Qwen2.5 and Qwen3.6. 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 48GB?
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.