Best AI Models for Framework Desktop (Ryzen AI Max+ 395, 128 GB)
128 GB total — ~96 GB usable as VRAM
128 GB unified memory; up to ~96 GB is allocatable as VRAM on Windows (more under Linux). Bandwidth-bound at 256 GB/s — large models load but generate slowly.
With 128 GB of memory, this is a high-end configuration for local AI. You can comfortably run most open-source LLMs including large 70B parameter models at good quantization levels, making it one of the best setups for serious local AI work.
At this memory tier, nearly every popular open-source model is within reach. You can run Llama 3 70B at Q4_K_M or even Q5_K_M quantization with room to spare, handle coding assistants like DeepSeek Coder 33B at high quality, and easily run any 7B–30B model at full or near-full precision. Context windows remain generous even with larger models, so multi-turn conversations and long-document processing work smoothly.
Runs Well
- 70B models (Llama 3 70B, Qwen 72B) at Q4–Q5
- 30B models at Q6–Q8 quality
- 7B–14B models at full FP16 precision
- Vision models (LLaVA, CogVLM) without compromise
Challenging
- Mixture-of-experts models like Mixtral 8x22B at higher quants
- 120B+ models still require lower quantizations
What LLMs Can Framework Desktop (Ryzen AI Max+ 395, 128 GB) Run?
122 models · 6 excellent · 4 good
Showing compatibility for Framework Desktop (Ryzen AI Max+ 395, 128 GB)
| Model | Quant | VRAM | Speed | Context | Status | Grade |
|---|---|---|---|---|---|---|
Q4_K_M·31.3 t/s tok/s·131K ctx·EASY RUN | Q4_K_M | 5.3 GB | 31.3 t/s | 131K | EASY RUN | D28 |
Q4_K_M·33.3 t/s tok/s·131K ctx·EASY RUN | Q4_K_M | 5.0 GB | 33.3 t/s | 131K | EASY RUN | D28 |
Q4_K_M·7.8 t/s tok/s·262K ctx·EASY RUN | Q4_K_M | 21.2 GB | 7.8 t/s | 262K | EASY RUN | C37 |
Q4_K_M·40.9 t/s tok/s·4K ctx·EASY RUN | Q4_K_M | 4.1 GB | 40.9 t/s | 4K | EASY RUN | D27 |
Q4_K_M·7.6 t/s tok/s·262K ctx·EASY RUN | Q4_K_M | 21.9 GB | 7.6 t/s | 262K | EASY RUN | C38 |
Q4_K_M·5.8 t/s tok/s·33K ctx·FAIR FIT | Q4_K_M | 28.6 GB | 5.8 t/s | 33K | FAIR FIT | B45 |
Q4_K_M·137.5 t/s tok/s·8K ctx·EASY RUN | Q4_K_M | 1.2 GB | 137.5 t/s | 8K | EASY RUN | D26 |
Q4_K_M·30.9 t/s tok/s·131K ctx·EASY RUN | Q4_K_M | 5.4 GB | 30.9 t/s | 131K | EASY RUN | D28 |
Q4_K_M·10.0 t/s tok/s·262K ctx·EASY RUN | Q4_K_M | 16.6 GB | 10.0 t/s | 262K | EASY RUN | C34 |
Q4_K_M·30.1 t/s tok/s·131K ctx·EASY RUN | Q4_K_M | 5.5 GB | 30.1 t/s | 131K | EASY RUN | D28 |
Q4_K_M·30.9 t/s tok/s·131K ctx·EASY RUN | Q4_K_M | 5.4 GB | 30.9 t/s | 131K | EASY RUN | D28 |
Q4_K_M·6.5 t/s tok/s·131K ctx·EASY RUN | Q4_K_M | 25.7 GB | 6.5 t/s | 131K | EASY RUN | C42 |
Q4_K_M·40.9 t/s tok/s·4K ctx·EASY RUN | Q4_K_M | 4.1 GB | 40.9 t/s | 4K | EASY RUN | D27 |
Q4_K_M·6.0 t/s tok/s·EASY RUN | Q4_K_M | 27.6 GB | 6.0 t/s | — | EASY RUN | C44 |
Q4_K_M·8.2 t/s tok/s·41K ctx·EASY RUN | Q4_K_M | 20.3 GB | 8.2 t/s | 41K | EASY RUN | C36 |
Q4_K_M·30.7 t/s tok/s·16K ctx·EASY RUN | Q4_K_M | 5.4 GB | 30.7 t/s | 16K | EASY RUN | D28 |
Framework Desktop (Ryzen AI Max+ 395, 128 GB) Specifications
- Brand
- Framework
- Chip
- Ryzen AI Max+ 395
- Type
- Desktop
- Unified Memory
- 128 GB
- Memory Bandwidth
- 256.0 GB/s
- GPU Cores
- 40
- CPU Cores
- 16
- Neural Engine
- 50.0 TOPS
- Form Factor
- Mini-ITX 4.5L
- GPU Architecture
- RDNA 3.5
- CPU Architecture
- Zen 5
- Memory Type
- LPDDR5X-8000 (256-bit bus, soldered)
- TDP
- 120–140 W
- NPU
- XDNA 2
- NPU Performance
- 126 TOPS total
- MSRP
- $1,999
- Release Date
- 2025-07-01
Get Started
Devices to Consider
Similar devices and upgrades with more memory or higher bandwidth
Frequently Asked Questions
- Can Framework Desktop (Ryzen AI Max+ 395, 128 GB) run GPT OSS 120B?
Yes, the Framework Desktop (Ryzen AI Max+ 395, 128 GB) with 128 GB unified memory can run GPT OSS 120B, Llama 4 Scout 17B 16E Instruct, NVIDIA Nemotron 3 Super 120B A12B BF16, and 1404 other models. 29 models achieve excellent performance, and 33 run at good quality. Apple Silicon's unified memory architecture lets the GPU access the full memory pool without copying data, making it efficient for AI workloads.
- How much memory is available for AI on Framework Desktop (Ryzen AI Max+ 395, 128 GB)?
The Framework Desktop (Ryzen AI Max+ 395, 128 GB) has 128 GB unified memory. After macOS reserves ~3.5 GB for the operating system, approximately 124.5 GB is available for AI models. Unlike discrete GPUs where VRAM is separate from system RAM, Apple Silicon shares one memory pool between the CPU and GPU — this means no data copying overhead, but you share memory with macOS and open apps.
- Is Framework Desktop (Ryzen AI Max+ 395, 128 GB) good for AI?
With 128 GB unified memory and 256.0 GB/s bandwidth, the Framework Desktop (Ryzen AI Max+ 395, 128 GB) is excellent for running local AI models. It supports 62 models at good quality or better. This is a premium configuration — you can run large 30B+ parameter models at good quality, and most 7B models at maximum quality. Ideal for professional AI workloads.
- What's the best model for Framework Desktop (Ryzen AI Max+ 395, 128 GB)?
The top-rated models for the Framework Desktop (Ryzen AI Max+ 395, 128 GB) are GPT OSS 120B, Llama 4 Scout 17B 16E Instruct, NVIDIA Nemotron 3 Super 120B A12B BF16. With this much memory, you can prioritize quality — use higher quantizations (Q5/Q6) for better output, or run larger 30B+ models for more capable reasoning.
- How fast is Framework Desktop (Ryzen AI Max+ 395, 128 GB) for AI inference?
With 256.0 GB/s memory bandwidth, the Framework Desktop (Ryzen AI Max+ 395, 128 GB) achieves approximately 40 tok/s on a 7B model at Q4_K_M — that's comfortable for real-time chat. A 14B model runs at ~20 tok/s. Apple Silicon achieves high efficiency (~70%) thanks to unified memory — there's no PCIe bottleneck between CPU and GPU.
tok/s = (256 GB/s ÷ model GB) × efficiency
Apple Silicon achieves ~70% bandwidth efficiency thanks to unified memory and Metal acceleration.
Estimated speed on Framework Desktop (Ryzen AI Max+ 395, 128 GB)
~2 tok/s~2 tok/s~2 tok/s~3 tok/sReal-world results typically within ±20%.
- Can I run AI offline on Framework Desktop (Ryzen AI Max+ 395, 128 GB)?
Yes — once you download a model, it runs entirely on the Framework Desktop (Ryzen AI Max+ 395, 128 GB) without internet. Applications like Ollama and LM Studio make it straightforward to download, manage, and run models locally. All your conversations stay private on your device with zero data sent to external servers. This is one of the key advantages of local AI: complete privacy, no API costs, and no rate limits.
- Anything to watch out for with Framework Desktop (Ryzen AI Max+ 395, 128 GB)?
128 GB unified memory; up to ~96 GB is allocatable as VRAM on Windows (more under Linux). Bandwidth-bound at 256 GB/s — large models load but generate slowly.