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Framework Desktop Ryzen AI Max+ 395 64GB vs NVIDIA GeForce RTX 3090 Ti

For running models locally, priced in the US. At 32k context the first runs 59 models fully in memory, the second 50.

In short

The Framework Desktop Ryzen AI Max+ 395 64GB has more memory for models: 64 GB against 24 GB. At 32k context the Framework Desktop Ryzen AI Max+ 395 64GB runs 59 of the models we track fully in memory and the NVIDIA GeForce RTX 3090 Ti 50; only the Framework Desktop Ryzen AI Max+ 395 64GB holds Qwen 3.5 122B-A10B. On the models both run fully in memory, the NVIDIA GeForce RTX 3090 Ti is about 4.4× as fast as the Framework Desktop Ryzen AI Max+ 395 64GB (estimated, median across models). In the US the Framework Desktop Ryzen AI Max+ 395 64GB costs $1,899 at eBay (used) and the NVIDIA GeForce RTX 3090 Ti $1,999 at Amazon: the Framework Desktop Ryzen AI Max+ 395 64GB is $100 cheaper.

Updated . Speeds are estimates; how they are worked out.

Framework Desktop Ryzen AI Max+ 395 64GB

$1,899

eBay, used (asking)

Add to build
NVIDIA GeForce RTX 3090 Ti

$1,999

Amazon

Add to build

Specifications

SpecFramework Desktop Ryzen AI Max+ 395 64GBNVIDIA GeForce RTX 3090 Ti
ChipRyzen AI Max+ 395 (Radeon 8060S)–
Memory bus256-bit384-bit
Memory bandwidth256 GB/s1,008 GB/s
FP16 compute59.4 TFLOPS80 TFLOPS
SoftwareROCmCUDA
Unified memory64 GB–
GPU can use by default48 GB–
GPU can use, tuned56 GB–
Operating systemlinux–
ProcessorRyzen AI Max+ 395–
Storage1000 GB–
GPU–GeForce RTX 3090 Ti
Memory–24 GB GDDR6X
Board power–450 W
PCIe generation–Gen 4
PCIe lanes–x16

What each runs

Estimated decode speed with the most precise quant that fits each one est.

ModelFramework Desktop Ryzen AI Max+ 395 64GBNVIDIA GeForce RTX 3090 Ti
Qwen 3.8 27B5tok/sQ8_027tok/sQ5_K_M
Qwen 3.5 122B-A10B20tok/sUD-Q2_K_XLoffload
Qwen 3.6 27B5tok/sQ8_029tok/sQ5_K_M
Qwen3 Coder Next26tok/sQ4_K_Moffload
Gemma 4 31B4tok/sQ8_029tok/sQ4_K_M
Mistral Small 4 119B27tok/sUD-Q2_K_XLoffload
Qwen 3.6 35B-A3B22tok/sQ8_0145tok/sQ4_K_M
Qwen 3.5 27B5tok/sQ8_029tok/sQ5_K_M
Gemma 4 26B-A4B17tok/sQ8_084tok/sUD-Q6_K
Qwen3 Next 80B-A3B32tok/sQ4_K_Moffload
Qwen 3.5 35B-A3B22tok/sQ8_0146tok/sQ4_K_M
GLM 4.7 Flash12tok/sQ8_070tok/sQ5_K_M
Devstral Small 2 24B5tok/sQ8_028tok/sQ5_K_M
Nemotron 3.5 Lightning 30B-A3B24tok/sUD-Q6_K_XLoffload
Kimi Linear 48B-A3B30tok/sQ6_Koffload
gpt-oss 20B26tok/sMXFP4116tok/sMXFP4
Qwen3 Coder 30B-A3B13tok/sQ8_074tok/sQ4_K_M
Qwen3 32B3tok/sQ8_0offload
Gemma 4 12B10tok/sQ8_046tok/sQ8_0
Qwen 3.5 9B13tok/sQ8_059tok/sQ8_0
Mistral Small 3.2 24B5tok/sQ8_028tok/sQ5_K_M
Gemma 3 27B4tok/sQ8_028tok/sQ5_K_M
DeepSeek R1 Distill Qwen 32B3tok/sQ8_0offload
Ministral 3 14B7tok/sQ8_032tok/sQ8_0
Qwen3 14B7tok/sQ8_030tok/sQ8_0
DeepSeek R1 0528 Qwen3 8B10tok/sQ8_046tok/sQ8_0
Qwen3 8B10tok/sQ8_046tok/sQ8_0
Phi-4 14B6tok/sQ8_028tok/sQ8_0
Qwen 3.5 4B25tok/sQ8_0112tok/sQ8_0
Ministral 3 8B10tok/sQ8_046tok/sQ8_0
Granite 4.2 8B10tok/sQ8_043tok/sQ8_0
Gemma 4 E4B15tok/sQ8_068tok/sQ8_0
LFM2.5 8B-A1B32tok/sQ8_0140tok/sQ8_0
Llama 3.1 8B13tok/sQ6_K57tok/sQ6_K
Qwen2.5 0.5B151tok/sQ8_0669tok/sQ8_0
Qwen3.5 0.8B114tok/sQ8_0507tok/sQ8_0
Qwen3.5 2B76tok/sQ5_K_M337tok/sQ5_K_M
DeepSeek R1 Distill Qwen 1.5B50tok/sQ8_0221tok/sQ8_0
MiniCPM5 2B34tok/sQ8_0153tok/sQ8_0
LFM2.5 2.6B29tok/sQ8_0128tok/sQ8_0
LFM2.5 VL 3B29tok/sQ8_0128tok/sQ8_0
Mellum2.1 12B A2.5B Thinking27tok/sQ8_0118tok/sQ8_0
granite vision 4.1 4b22tok/sQ8_099tok/sQ8_0
granite 4.2 3b21tok/sQ8_095tok/sQ8_0
Kimi VL A3B Thinking 250621tok/sQ8_091tok/sQ8_0
Kimi VL A3B20tok/smlx-8bit88tok/smlx-8bit
LFM2.5 24B A2B18tok/sQ8_084tok/sQ6_K
GLM 4 9B 041415tok/smlx-5bit65tok/smlx-5bit
DeepSeek R1 Distill Qwen 7B14tok/sQ8_063tok/sQ8_0
GLM 4.6V Flash12tok/sQ8_055tok/sQ8_0
DeepSeek R1 Distill Llama 8B11tok/sQ8_049tok/sQ8_0
GLM 4.1V 9B Thinking11tok/smlx-8bit48tok/smlx-8bit
Ministral 3 8B Reasoning 251210tok/sQ8_046tok/sQ8_0
DeepSeek R1 Distill Qwen 14B6tok/sQ8_028tok/sQ8_0
Devstral Small 25075tok/sQ8_028tok/sQ5_K_M
Magistral Small 25065tok/sQ8_028tok/sQ5_K_M
Magistral Small 25075tok/sQ8_028tok/sQ5_K_M
Magistral Small 25095tok/sQ8_028tok/sQ5_K_M
granite 4.2 30b4tok/sQ8_0offload
GLM 4.5 Airwon't runoffload
DeepSeek V4 Flashwon't runwon't run
GLM 5.3 Flashwon't runwon't run
Qwen 3.8 Flash Nextwon't runwon't run
MiniMax M2.7won't runwon't run
Nemotron 3 Super 120B-A12Bwon't runwon't run
gpt-oss 120Bwon't runwon't run
Llama 3.3 70Bwon't runwon't run
DeepSeek R1won't runwon't run
DeepSeek R1 0528won't runwon't run
DeepSeek R1 Distill Llama 70Bwon't runwon't run
DeepSeek R1 Zerowon't runwon't run
DeepSeek V3 0324won't runwon't run
DeepSeek V3.1won't runwon't run
DeepSeek V3.1 Terminuswon't runwon't run
DeepSeek V3.2won't runwon't run
DeepSeek V4 Flash 0731won't runwon't run
DeepSeek V4 Flash Vision Expwon't runwon't run
Devstral 2 123B Instruct 2512won't runwon't run
GLM 4.5Vwon't runwon't run
GLM 4.6won't runwon't run
GLM 4.6Vwon't runwon't run
GLM 4.7won't runwon't run
GLM 5.1won't runwon't run
GLM 5.2won't runwon't run
GLM 5.3won't runwon't run
Kimi Dev 72Bwon't runwon't run
Kimi K2won't runwon't run
Kimi K2 Instruct 0905won't runwon't run
Kimi K2 Thinkingwon't runwon't run
Kimi K2.5won't runwon't run
MiniMax M2won't runwon't run
MiniMax M2.1won't runwon't run
MiniMax M2.5won't runwon't run
MiniMax M3won't runwon't run
Mistral Medium 3.5 128Bwon't runwon't run

Questions

Which is better for local AI, the Framework Desktop Ryzen AI Max+ 395 64GB or the NVIDIA GeForce RTX 3090 Ti?
Choose the Framework Desktop Ryzen AI Max+ 395 64GB to run bigger models. Choose the NVIDIA GeForce RTX 3090 Ti for speed. Choose the Framework Desktop Ryzen AI Max+ 395 64GB to spend less.
Which can run bigger models, the Framework Desktop Ryzen AI Max+ 395 64GB or the NVIDIA GeForce RTX 3090 Ti?
At 32k context the Framework Desktop Ryzen AI Max+ 395 64GB runs 59 of the models we track fully in memory and the NVIDIA GeForce RTX 3090 Ti 50; only the Framework Desktop Ryzen AI Max+ 395 64GB holds Qwen 3.5 122B-A10B.
Which is faster for local AI, the Framework Desktop Ryzen AI Max+ 395 64GB or the NVIDIA GeForce RTX 3090 Ti?
On the models both run fully in memory, the NVIDIA GeForce RTX 3090 Ti is about 4.4× as fast as the Framework Desktop Ryzen AI Max+ 395 64GB (estimated, median across models).
What is the price difference between the Framework Desktop Ryzen AI Max+ 395 64GB and the NVIDIA GeForce RTX 3090 Ti?
In the US the Framework Desktop Ryzen AI Max+ 395 64GB costs $1,899 at eBay (used) and the NVIDIA GeForce RTX 3090 Ti $1,999 at Amazon: the Framework Desktop Ryzen AI Max+ 395 64GB is $100 cheaper.

More comparisons

Framework Desktop Ryzen AI Max+ 395 64GB vs NVIDIA GeForce RTX 3090 Ti for local AI (US) · readygpu