- Nvidia’s flagship GPU delivers dominance while other models hardly move on
- Intel Arc Gpus Show Promise in AI, hindered by shaking editing support
- AMD positions between NVIDIA levels with inconsistent results across software
Content creation workflows have increasingly become dependent on GPUs with requirements ranging from real-time video editing to offline reproduction and AI-assisted tools.
A recent Puget system Benchmarks, comparing the latest consumer class cards from NVIDIA, AMD and Intel have shown a complex landscape.
In this sector, raw performance, application support and cost -effectiveness tell every different stories.
Performance trends for rendering engines
Benchmarks run over blender, V-ray, Redshift and Octane highlights Nvidia’s continued strength.
While blender now supports Intel and AMD hardware, most rendering engines remain tied to CUDA and RTX, leaving non-nvidia GPUs for a disadvantage.
GeForce RTX 5090 consistently scored highest with margins of over 20% against RTX 4090 in certain tests.
However, the rest of Nvidia’s 50 series often appeared on a par with their 40 -series predecessor.
AMD entered the charts with the Radeon RX 7900 XTX, which placed between the middle of the NVIDIA cards.
Despite promising results in specific engines remained Intel clustered at the lower end, which suggests that although Nvidia dominates supported software, the door is not fully closed to alternatives.
In professional editing tools such as Premiere Pro, After Effects and Davinci Resolve, the results were mixed.
Nvidia hardware leads in GPU-dependent tasks, especially with effects-heavy projects.
AMDS RADEON RX 9070 XT showed strong results in certain codec types that surpassed newer NVIDIA cards in some Langgop workloads, yet it fought in 3D-powered pipelines where Nvidia maintained a broad lead.
Intel’s ARC setup offered decent competition at the entry level, especially when paired with its Openvino Toolkit.
However, instability in resolve benchmarks pointed to growing pain in optimization.
These discrepancies make it more difficult to recommend Intel GPUs for reliable production, although their presence suggests a evolving role in specific workloads.
AI-focused tests, such as MLPERF client, added another dimension, which here delivered Intel’s ARC GPUs unexpectedly strong performance with leading times for first token generation.
Nvidia regained dominance in sustained token flow, with the RTX 5090 dragging ahead by almost 30% compared to 4090.
In Unreal Engine Benchmarks, Nvidia also led in general, although the AMDS 9070 X occasionally matched RTX 5070 Ti.
Intel cards consistently drew but demonstrated award-adjusted competitiveness.
This suggests that Intel’s ARC setup could serve as cheap GPUs for experimental AI or secondary systems despite limited mainstream resolution.
For creators who are focused on reliability in reproduction and editing, Nvidia continues to have the strongest position, especially with its flagship GPU.
Outside of top-end results, performance improvements over previous generations are uneven.
AMD offers competitive opportunities in some workflows and is still an alternative to those who are considering graphics cards for video editing at specific price levels.
Despite hanging in most professional tools, Intel has shown surprising results in AI-Inferens Benchmarks and still provides viable low-cost input points.
The overall picture suggests that while Nvidia sets the standard, both AMD and Intel offer niches where their GPUs can serve creators seeking alternatives.
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