BBrainOutput

Qwen2.5 72B vs Qwen3 235B-A22B (MoE)

Size, context window, license, approximate VRAM and the minimum local hardware each model needs — computed from our catalog and compatibility engine, not benchmarks.

Qwen2.5 72BQwen3 235B-A22B (MoE)
Parameters72B235B total / ~22B active (MoE)
Context window128K tokens128K tokens
LicenseQwen LicenseApache-2.0
~VRAM @ 4-bit (Q4_K_M)~44 GB~130 GB
~VRAM @ 8-bit (Q8_0)~78 GB~235 GB
Minimum deviceApple Mac mini (M4 Pro)Apple Mac Studio (M2 Ultra)
Recommended deviceSupermicro 8x H100 SuperServerSupermicro 8x H100 SuperServer
DeploymentHybridCloud
CapabilitiesTools, Code, Reasoning, Multilingual, Long contextTools, Reasoning, Code, Multilingual, Long context

Highlighted cells mark the lighter / longer / more permissive side per row, for local deployment. Informational rows have no winner.

Bottom line

Qwen2.5 72B (~72B) is lighter than Qwen3 235B-A22B (MoE) (~235B), so it runs on more modest hardware, while Qwen3 235B-A22B (MoE) trades a larger footprint for more capacity. At 4-bit, Qwen2.5 72B needs about 44GB versus ~130GB, a meaningful gap when choosing a GPU. Both target a 128K context window. Qwen3 235B-A22B (MoE)'s Apache-2.0 license is the more permissive of the two for commercial use. Minimum viable hardware differs: Qwen2.5 72B starts on a Apple Mac mini (M4 Pro), Qwen3 235B-A22B (MoE) on a Apple Mac Studio (M2 Ultra). Figures are approximate working-set estimates, not benchmarks — verify the exact release before committing hardware.

Pick Qwen2.5 72B if…

Pick Qwen2.5 72B if you want the lighter footprint and cheaper hardware.

Pick Qwen3 235B-A22B (MoE) if…

Pick Qwen3 235B-A22B (MoE) if you have the memory to spare and want the larger model, or you want the more permissive Apache-2.0 license.

Full profile
Qwen2.5 72B

Flagship tier — similar footprint to Llama 70B; 48GB+ single card, a big Mac, or multi-GPU.

Full profile
Qwen3 235B-A22B (MoE)

Datacenter / multi-GPU or cloud. Mixture-of-experts: large total memory, but only ~22B params activate per token.

Run the winner on hardware you control

Pick the model that fits your footprint, then turn the right machine into a private AI Business OS — no per-seat data leaving your premises.