Yes—Qwen-Image 2.1 has been run locally in ComfyUI on a 48 GB Apple Silicon Mac, but the published results describe one specific M5 Pro setup, not every Mac with 48 GB of unified memory. In Kevin Mullin’s 2026 report, a still-life generation had a warm median time of 143.5 seconds at 1024 × 1024 and 343.5 seconds at 1536 × 1536. Images could look convincing, but exact placement and poster text were inconsistent. ComfyUI documents native 2048 × 2048 output, editing, RGBA transparency and up to 10 reference images; those capabilities do not guarantee a particular Mac’s speed or a precise result.
What the M5 Pro test actually establishes
Kevin Mullin reports running Qwen-Image 2.1 in ComfyUI on an Apple M5 Pro MacBook Pro with 48 GB unified memory, 18 CPU cores and 20 GPU cores. The reported software environment was macOS 27.0, ComfyUI 0.37.0, PyTorch 2.12.1 and the MPS backend. The image model and text encoder used INT8 ConvRot files, and the VAE used BF16. These are the author’s reported configuration details, not an independently verified reproduction. Kevin Mullin’s test report
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The test workflow used 25 sampling steps, Euler, the simple scheduler, CFG 1, batch size one and an empty negative prompt. Mullin reports no LoRA, upscaler, prompt enhancement or manual retouching. The ComfyUI template’s 25-step setup is distinct from Qwen’s reference Diffusers example, which specifies 40 inference steps; their outputs and timings should not be treated as directly comparable. QwenLM’s repository
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Reported timing and sample
For the report’s still-life task, the warm median was 143.5 seconds at 1024 × 1024 and 343.5 seconds at 1536 × 1536. These are single-configuration measurements from one M5 Pro system, not general benchmarks or promises for other prompts, tasks, Mac chips, memory configurations or software versions. The author describes 20 local generations: four baseline images, four transparent assets, four edits, three posters, four higher-resolution images and one synthetic reference. Kevin Mullin’s test report
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The available figures do not establish performance across other 48 GB Macs or a controlled comparison among quantizations. When evaluating another setup, compare the chip and memory, model-weight precision, ComfyUI and backend versions, sampling settings, task and resolution, and what counts as a usable result. A timing from a different workflow is not an apples-to-apples comparison.
What Qwen and ComfyUI document
ComfyUI announced native Qwen-Image-2.1 support on September 20, 2026. Its announcement describes a 7-billion-parameter image generation and editing model with one checkpoint for both tasks, RGBA output, native 2048 × 2048 generation and support for up to 10 reference images. These are documented product capabilities, not measured performance or success rates on the tested Mac. ComfyUI’s announcement
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QwenLM’s repository records the release and ComfyUI support on that date and includes compatible weights and example text-to-image and editing workflows. Its Diffusers example uses 40 inference steps, rather than the 25 used in Mullin’s ComfyUI report. QwenLM’s repository
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Real examples: convincing images are not always usable assets
Mullin reports that visual appeal did not reliably mean the image met the brief. In a 1024 × 1024 “mug beside notebook” placement check, one of four seeds passed. In the exact-poster-text test, one of three attempts passed; the other attempts included duplicate text. These small counts describe those tasks in the author’s session, not a general accuracy rate. Kevin Mullin’s test report
Higher resolution can change the composition
In the report, a same-seed generation at 1536 × 1536 produced a new composition rather than an upscale, and object placement could flip. Native high-resolution generation is therefore not equivalent to enlarging a known-good image or preserving its layout. If composition must stay fixed, inspect the result rather than assuming that a larger output will retain it. Kevin Mullin’s test report
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Inspect transparent edges and text
A transparent asset’s preview can look clean while its alpha channel contains edge residue. Mullin recommends checking both the edges and alpha before treating an RGBA result as production-ready. For text-heavy posters, check the actual lettering and repetitions against the brief; the report’s attempts show that exact text should not be assumed. Kevin Mullin’s test report
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Judge the time to a usable deliverable, not just the first attractive image. Mullin’s practical advice is: “Test one complete asset workflow. Generate it, make one specific revision, place it in a real layout, and count every attempt.” That is an evaluation method, not a result from a controlled comparison. Kevin Mullin’s test report
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- Try a representative task—such as a product image, a targeted edit, a transparent asset or a poster—using the settings you would actually use.
- Make a specific revision, then check whether the requested change happened without losing required details.
- Put the result in its intended layout and inspect placement, lettering and alpha edges where relevant.
- Count retries and record elapsed time to a usable result, not only the time for a single generation.
The cited M5 Max report concerns a different machine and separate Q8/Q4 conditions. It does not establish how the M5 Pro setup compares with an M5 Max or support a general performance ranking. A fair comparison needs the hardware, weights and precision, workflow settings, task, resolution and success criteria to be stated for both runs. Kevin Mullin’s test report
Downloading model weights does not, by itself, establish permission for a particular commercial use. Check the license attached to the exact weights you intend to use and assess it against your use case.
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