Best local LLM for coding with 128GB VRAM
The models people report running for coding on setups with more than 96 GB and up to 128 GB of memory, such as AMD Strix Halo 128GB, DGX Spark, M5 Max 128GB or M4 Max 128GB. 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
| # | Model | Fastest run | Median t/s | Fastest t/s | Reports |
|---|---|---|---|---|---|
| 1 | Qwen3.8Alibaba | 125B · 6B active · oQ4e on M5 Max 128GB | 26 | 55 | 8 |
| 2 | Qwen3.6Alibaba | 27B · Q4_K_M on AMD Strix Halo 128GB | 17 | 21 | 6 |
| 3 | Nex-N2.5-mini | MLX-4bit on M5 Max 128GB | 134 | 134 | 1 |
| 4 | DeepSeek V4 FlashDeepSeek | 284B · 13B active · UD-IQ3_XXS on DGX Spark | 24 | 24 | 1 |
| 5 | Ling-3.0Ant Group | INT4 on DGX Spark | 41 | 41 | 1 |
| 6 | Qwen3-Coder-Next | UD-Q6_K_XL on AMD Strix Halo 128GB | 37 | 37 | 1 |
| 7 | GLM-5.2Zhipu AI | NVFP4 on DGX Spark | 15 | 15 | 1 |
Frequently asked
What is the best local LLM for coding with 128GB of VRAM?
Ranked from community reports on setups with more than 96 GB and up to 128 GB of memory, Qwen3.8 has the strongest record, followed by Qwen3.6 and Nex-N2.5-mini. 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 128GB?
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.