Best local LLM for coding with 96GB VRAM
The models people report running for coding on setups with more than 64 GB and up to 96 GB of memory, such as RTX Pro 6000 Blackwell, M2 Max 96GB, RTX PRO 6000 Max-Q or M3 Max 96GB. Each row shows the fastest coding run reported for that model in this band.
Ranked from 17 coding reports on llamaperf.
Ranked by community reports
| # | Model | Fastest run | Median t/s | Fastest t/s | Reports |
|---|---|---|---|---|---|
| 1 | Qwen3.8Alibaba | 27B · Q6_K on RTX Pro 6000 Blackwell | 98 | 114 | 6 |
| 2 | DeepSeek V4 FlashDeepSeek | 284B · 13B active · Q4_K_XL on RTX Pro 6000 Blackwell | 13 | 31 | 5 |
| 3 | Qwen3.6Alibaba | 27B · Q5_K_M on M2 Max 96GB | 18 | 28 | 3 |
| 4 | Gemma 4Google DeepMind | 31B on H100 80GB | 125 | 125 | 1 |
| 5 | Qwen3Alibaba | 8B · Q4 on M2 Max 96GB | 43 | 43 | 1 |
| 6 | Mimo 2.5Xiaomi | RTX Pro 6000 Blackwell | - | - | 1 |
Frequently asked
What is the best local LLM for coding with 96GB of VRAM?
Ranked from community reports on setups with more than 64 GB and up to 96 GB of memory, Qwen3.8 has the strongest record, followed by DeepSeek V4 Flash 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 96GB?
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.