TokenAssemble

NVIDIA GPU

NVIDIA RTX 6000 Ada Generation

The NVIDIA RTX 6000 Ada Generation has 48GB of VRAM and 960 GB/s of memory bandwidth. Its sweet spot tops out around Qwen3.6-35B-A3B — the largest model that loads cleanly at a quality quant with llama.cpp at 8K context.

VRAM
48 GB
Memory bandwidth
960 GB/s
TDP
300 W
MSRP
$6,799
Backends
CUDA · Vulkan

Specs as of 2026-07-08 · source

NVIDIA RTX 6000 Ada Generation for local AI — common questions

How much VRAM does the NVIDIA RTX 6000 Ada Generation have?
The NVIDIA RTX 6000 Ada Generation has 48GB of VRAM with 960 GB/s of memory bandwidth. VRAM sets which models fit; bandwidth sets how fast they feel once they do.
Is the NVIDIA RTX 6000 Ada Generation good for running AI models locally?
Yes. 48GB is enough headroom for the large open models most people want to run locally. The largest model it loads cleanly is Qwen3.6-35B-A3B, at a quality quant with llama.cpp at 8K context.
What runtimes work with the NVIDIA RTX 6000 Ada Generation?
It runs on CUDA · Vulkan, which covers Ollama, llama.cpp and LM Studio. Runtime choice affects speed and features, not whether a model fits.

Affiliate link — we may earn a commission. Verdicts are computed before any link is attached.

What an NVIDIA RTX 6000 Ada Generation can run

Every model we track, graded at its best clean-fit quant. Click any verdict for the full breakdown.

ModelBest-quant verdict · llama.cpp · 8K context
Qwen3-8BFits · A · Q8_0interactive
gemma-4-26B-A4B-itFits · A · Q8_0interactivebeta
Qwen2.5-7B-InstructFits · A · Q8_0interactive
Qwen2.5-1.5B-InstructFits · A · Q8_0interactive
Llama-3.2-1B-InstructFits · A · Q8_0interactive
Llama-3.1-8B-InstructFits · A · Q8_0interactive
DeepSeek-R1Won't fitbeta
Qwen3.5-9BFits · A · Q8_0interactivebeta
gpt-oss-20bFits · A · MXFP4interactivebeta
Qwen3.6-35B-A3BFits · B · Q8_0interactivebeta
Qwen2.5-3B-InstructFits · A · Q8_0interactive
Qwen3-32BFits · B · Q8_0usable
Qwen3.6-27BFits · A · Q8_0interactivebeta
Qwen2.5-0.5B-InstructFits · A · Q8_0interactive
Mistral-7B-Instruct-v0.3Fits · A · Q8_0interactive
gpt-oss-120bTight · C · MXFP4interactive · offloadbeta
Qwen3-14BFits · A · Q8_0interactive
Qwen3-30B-A3BFits · B · Q8_0interactivebeta
Qwen2.5-32B-InstructFits · B · Q8_0usable
DeepSeek-V4-FlashTight · C · UD-Q2_K_XLinteractive · offloadbeta
Qwen2.5-14B-InstructFits · A · Q8_0interactive
Llama-3.2-3B-InstructFits · A · Q8_0interactive
gemma-3-4b-itFits · A · Q8_0interactivebeta
gemma-3-12b-itFits · A · Q8_0interactivebeta
Llama-3.1-70B-InstructTight · C · Q4_K_Musable
Phi-3.5-mini-instructFits · A · Q8_0interactive
Phi-4Fits · A · Q8_0interactive
DeepSeek-R1-Distill-Qwen-32BFits · B · Q8_0usable
gemma-3-27b-itFits · B · Q8_0interactivebeta
Llama-3.3-70B-InstructTight · C · Q4_K_Musable
Qwen2.5-72B-InstructTight · C · Q4_K_Mpainful · offloadbeta
gemma-2-2b-itFits · A · Q8_0interactivebeta
DeepSeek-R1-Distill-Qwen-14BFits · A · Q8_0interactive
DeepSeek-R1-Distill-Llama-8BFits · A · Q8_0interactive
DeepSeek-R1-Distill-Qwen-7BFits · A · Q8_0interactive
gemma-2-9b-itFits · A · Q8_0interactivebeta
Mistral-Nemo-Instruct-2407Fits · A · Q8_0interactive
QwQ-32BFits · B · Q8_0usable
Mistral-Small-24B-Instruct-2501Fits · A · Q8_0interactive
gemma-2-27b-itFits · A · Q8_0interactivebeta

Have a specific model in mind? Check it against the NVIDIA RTX 6000 Ada Generation at your own quant and context length.

Check with the NVIDIA RTX 6000 Ada Generation preselected →

Verdicts computed from published specs and measured GGUF sizes — how the math works.