Upscale any video of any resolution to 4K with AI. (Get started for free)
DaVinci Resolve on macOS Sonoma Performance Insights and User Experiences in 2024
DaVinci Resolve on macOS Sonoma Performance Insights and User Experiences in 2024 - GPU Utilization and Performance on macOS Sonoma
macOS Sonoma has seen advancements in GPU utilization, notably within DaVinci Resolve, particularly for tasks demanding graphical processing like image manipulation and color grading. The optimal experience seems to favor dedicated GPUs, such as those from AMD Radeon Pro or Apple's M1 range. Interestingly, performance isn't always tied to sheer core count. Hardware configurations with different RAM capacities on the Mac Studio show that a higher number of cores isn't a guaranteed path to improved performance. Benchmarks currently suggest that the NVIDIA RTX 6000 is the top choice for demanding professional workflows in DaVinci Resolve, though it's a premium option. More budget-conscious alternatives from AMD and NVIDIA also offer solid performance for Resolve. It's worth noting that user experiences indicate achieving smoother playback is often possible by adjusting memory and power settings within the application itself. These tweaks can demonstrably improve overall performance within the application.
DaVinci Resolve's performance on macOS Sonoma is heavily influenced by the GPU, particularly when tackling tasks like image manipulation, color adjustments, and rendering. Systems with dedicated GPUs, such as the AMD Radeon Pro series or the integrated GPUs found within Apple's M1 chips (especially the 8-core and 16-core variants), are generally recommended for the best experience. It's interesting to note that GPU configuration plays a crucial role. For example, a Mac Studio with a 48-core GPU and 128GB of memory may outstrip another with a 64-core GPU and 64GB of RAM when running Resolve. Current benchmarks suggest that the NVIDIA RTX 6000 Ada Generation stands as the top-tier professional GPU for Resolve, though its price tag reflects its capabilities. For users on a tighter budget, the newer AMD Radeon PRO W7000 series and the NVIDIA RTX Ada Generation offer competitive performance for Resolve.
DaVinci Resolve 18, like other versions, requires a baseline of 8GB of system memory for basic operations and bumps that up to 16GB for utilizing Fusion. Notably, the Mac version of Resolve leverages hardware-accelerated H.265 encoding, particularly on M1 Macs, giving users more control over the balance between render speed and output quality. It's worth pointing out that the free version of Resolve supports only a single GPU, while Studio unlocks the potential for multi-GPU utilization. However, the performance benefits of multiple GPUs are not uniform across all tasks. Formats like BRAW and ARRIRAW display more substantial performance gains with additional GPUs.
User experiences suggest that tweaking memory usage limits and optimizing system power settings can significantly impact playback fluidity within Resolve on macOS Sonoma. This indicates there are avenues for optimization beyond just hardware upgrades. It's fascinating to observe these software-level improvements in impact. While macOS Sonoma incorporates these optimization points, and has many potential upsides, concerns regarding thermal management remain. High GPU utilization can sometimes lead to throttling, impacting overall frame rates and render times. It's a challenge to fully exploit the GPU potential without proper cooling. Thankfully, the operating system does include refined tools for monitoring GPU usage, providing users with a window into performance bottlenecks and allowing them to more effectively diagnose performance hiccups in real-time.
DaVinci Resolve on macOS Sonoma Performance Insights and User Experiences in 2024 - User-Reported Issues with YouTube Preset in Version 2
DaVinci Resolve version 2 on macOS Sonoma has seen users encounter problems with the YouTube export preset. A recurring theme is that the preset isn't always applying the correct settings when exporting videos, causing some frustrating results. Some users have reported seeing blocky artifacts in their videos, especially during quick scenes, after exporting using this preset. Others have found that color grading done in DaVinci Resolve doesn't quite translate to YouTube as intended, with exported videos appearing washed out or different from how they looked in the software.
These observations have naturally led to suggestions and workarounds from the community. Users have shared advice about meticulously checking export settings to align with YouTube's recommendations to help mitigate some of these discrepancies. Also circulating are tips to manage performance – like creating optimized media within Resolve before export – and the value of saving custom export settings as presets to streamline the process and improve consistency. Some issues, like the quality when using the AV1 codec, require understanding the specific settings that YouTube recommends for it. It's vital to double-check the frame rates and other settings in the timeline before exporting as well.
Beyond individual fixes, a common request amongst users is for more information and action from Blackmagic Design. Many users feel they need more clarity and communication from the company regarding the functionality of the YouTube preset and their plans for addressing these issues and improving the overall user experience. It seems that, while the preset can be helpful, it's not yet consistently delivering what's expected and needs improvement.
Based on user feedback, the YouTube preset within DaVinci Resolve 2 on macOS Sonoma has encountered a number of quirks that impact the export process. Several users have found that the preset sometimes generates unnecessarily high bitrate files, leading to bloated file sizes without a corresponding leap in video quality. This can be a drain on storage and upload speeds without any tangible benefits.
One curious issue that has emerged is a potential audio sync problem when using the preset. Many users have reported that the audio output can lag behind the video, requiring subsequent fixes in other audio programs, adding an unwelcome layer of complexity to the workflow.
There's also a noticeable inconsistency in how videos exported using this preset play back on different platforms. Videos look different on mobile versus desktop, raising concern about the color grading consistency and overall video fidelity, particularly when sharing content across platforms.
The preset doesn't always take advantage of the latest codec capabilities. It appears that some features within modern codecs like AV1, which could offer significant benefits for streaming at higher resolutions, are not fully leveraged by the YouTube preset.
Furthermore, the preset itself is quite rigid. Users are frequently unable to easily fine-tune particular settings, pushing them towards manually configuring the export for desired results. This process naturally slows down the workflow and adds complexity. It appears that the preset doesn't always fully utilize the power of the M1 and M2 chips, with manual configurations showing faster rendering times in some instances, suggesting that the preset could be optimized to better leverage Apple's silicon.
Color profile inconsistencies also plague some users, resulting in a mismatch between the final video and what's seen during editing. This can lead to unexpected color shifts and a reduction in visual quality, creating an undesirable workflow challenge.
While intended to simplify the process, the compression settings in the default preset are sometimes too intense, leading to a noticeable decrease in quality. The problem is particularly evident in quick cuts and motion sequences, leading to visible artifacts in the final video.
Some within the community have also expressed concern that the YouTube preset might not properly handle multi-GPU rendering. This suggests that even with high-end hardware configurations, the full benefit of multi-GPU performance might not be realised when creating YouTube-specific content.
Lastly, many users report that export times with this preset often take longer than expected despite using powerful GPUs. This raises doubts about the optimization of the preset and hints that there's room for improvement in future versions. It highlights the importance of continued development and optimization of these preset functions to enhance overall user experience.
DaVinci Resolve on macOS Sonoma Performance Insights and User Experiences in 2024 - M3 Max Chipset Performance for 4K Editing and Magic Mask
The M3 Max chip, with its 14 CPU cores and 30 GPU cores, plus a maximum of 36GB of memory, appears to be a powerful option on paper. However, users working with DaVinci Resolve on macOS Sonoma have reported some unexpected performance bottlenecks, particularly when editing 4K footage or using tools like Magic Mask. Many users find that the M3 Max doesn't provide a noticeable upgrade over the previous M1 Max, especially for tasks like color grading and applying effects, where instant responsiveness was often expected. While BRAW and ARRIRAW workflows seem to benefit from the M3 Max, it lags behind some high-end Windows laptops in certain Resolve tasks, like tracking. This raises questions about the chip's ability to fully utilize its capabilities in complex video edits. Despite being marketed for professional workflows, the M3 Max's performance isn't consistently meeting the expectations of many users who've experienced slowdowns and stuttering, especially when dealing with effects. It seems the potential of the M3 Max is not yet fully realized in some situations.
The M3 Max chipset boasts a substantial 14 cores and 30 GPU cores, with a maximum memory configuration reaching 36 GB. However, some users have reported unexpected performance dips when using DaVinci Resolve 18.6 on macOS Sonoma, particularly when tackling 4K editing and employing features like Magic Mask. Interestingly, these results haven't shown a massive leap over the preceding M1 Max in certain tasks. Color grading and effects processing, which often felt nearly instantaneous with the M1 Max, haven't seen a proportional speed increase with the M3 Max, leading to some frustration.
Specifically, users have experienced notable lag while utilizing features like Magic Mask, a noticeable slowdown compared to past Mac models. While benchmark results do demonstrate that the M3 Max outperforms older Intel Macs, it seems to fall behind high-performance Windows laptops in specific DaVinci Resolve tasks, such as planar and point tracking.
The M3 Max shows promising performance improvements for BRAW and ARRIRAW files. But the impact of the M3 Max on Resolve's AI features seems somewhat inconsistent – some show improvement, others don't. The chipset is designed with two ProRes engines, which aim to bolster video post-production, especially with high-resolution footage. It's notable that even with its emphasis on video editing performance, some users have stumbled upon stuttering when applying effects in Resolve.
This presents a bit of a paradox: the M3 Max is geared toward a professional user base, yet user experiences suggest its performance isn't always consistent with that expectation. Many users recommend opting for DaVinci Resolve Studio if they want to unlock the full potential of the M3 Max. This is because the free version imposes constraints on GPU utilization, potentially limiting the benefits of this chipset. It appears that achieving the optimal performance and leveraging the full capabilities of the M3 Max in DaVinci Resolve is a more nuanced issue than simply installing the latest hardware. The software settings and version of Resolve employed seems to play a key role in unlocking these performance benefits.
DaVinci Resolve on macOS Sonoma Performance Insights and User Experiences in 2024 - Compatibility Considerations with Apple Silicon
When using DaVinci Resolve on Apple Silicon Macs, especially with macOS Sonoma, you'll find it's been tuned to improve performance. The software is now designed to work well with the M1 Pro, M1 Max, and other newer chips, leading to notably faster processing speeds. Tasks like H.265 encoding and decoding benefit from hardware acceleration, resulting in faster rendering times. Users have reported significantly improved performance, with some seeing up to five times faster results than when using older Intel-based Macs. Yet, even with these improvements, there are ongoing considerations. Managing heat and consistently keeping performance strong when the GPU is working hard remain important issues. While the software is constantly updated and improved, some users still want to see more seamless integration and better performance during complex editing workflows within Resolve.
DaVinci Resolve's performance on Apple Silicon Macs, while generally impressive, isn't without its quirks. The shift to Apple's custom silicon has resulted in some unique considerations for compatibility.
While Apple promotes "Universal Applications" that can run on both Intel and Apple Silicon, not every application optimized for older Intel chips sees the same performance boost on the new chips. It's a mixed bag, depending heavily on how well the software has been adapted to take advantage of Apple Silicon.
Rosetta 2, which enables Intel apps to run on Apple Silicon, can cause a noticeable performance drop in some applications. This hints at a loss of efficiency when software is emulated versus running natively.
Apple Silicon's integration of the GPU into the main chip is fantastic for demanding tasks, but this design can lead to hiccups with third-party GPUs. Many of these cards are made for traditional desktop systems with discrete GPUs, which may not translate smoothly.
While multi-GPU setups are a performance booster on some systems, it hasn't delivered as anticipated with Apple Silicon in DaVinci Resolve. Performance gains with multi-GPU haven't consistently met user expectations in many complex workflows.
Apple Silicon's unified memory architecture, where both the CPU and GPU can rapidly access data, is great on paper. However, working on intricate projects with DaVinci Resolve can cause noticeable slowdowns with smaller memory configurations. It seems larger memory capacities are required for top-tier performance.
The switch to Apple Silicon has unfortunately brought along some compatibility issues with older plugins developed for Intel Macs. This lack of compatibility can be frustrating for those who rely on particular plugins. Finding workable alternatives isn't always straightforward.
Thermal management within Apple Silicon Macs, while usually good, can be pushed beyond its limits by long, intense rendering tasks. This sometimes results in the system slowing down due to heat concerns, impacting rendering times beyond anticipated estimations, especially with DaVinci Resolve's complex operations.
Apple Silicon's neural engine is intended to enhance AI features, but the performance in DaVinci Resolve has been inconsistent. Users have noticed some tasks, even when aimed at utilizing the neural engine, haven't consistently shown expected gains. This suggests there's still room for software developers to fine-tune the integration of AI elements.
Performance consistency between different Apple Silicon models can be a point of frustration. While the original M1 chip has generally worked well, the M2 and M3 iterations don't always deliver the anticipated proportional improvements in DaVinci Resolve, particularly when editing a complex mix of footage.
Lastly, users employing KVM switches for convenient switching between multiple machines have sometimes encountered incompatibility with Apple Silicon Macs. This can result in display issues or the inability for peripherals to be recognized, which can disrupt workflows in a professional editing environment.
Overall, Apple Silicon brings clear advantages, but it has brought along these compatibility questions, especially for those who rely on DaVinci Resolve for their professional video production. These points show that it's not simply a plug-and-play transition.
DaVinci Resolve on macOS Sonoma Performance Insights and User Experiences in 2024 - AI-Driven Features in DaVinci Resolve 19
DaVinci Resolve 19 has integrated a range of AI-powered tools to streamline video editing. Notable additions include IntelliTrack for tracking and stabilizing objects within a video. UltraNR leverages AI to reduce spatial noise in audio and video, resulting in cleaner visuals and audio. Face Refinement offers a quick way to enhance skin, eyes, and lighting within a shot, illustrating DaVinci Resolve's increasingly sophisticated image processing capabilities. Many of the more powerful features are driven by the DaVinci Neural Engine, a machine learning system optimized for Apple's M series processors. While these AI improvements are promising, some users have reported inconsistent performance with complex edits, suggesting these tools still require some fine-tuning for a smoother user experience across a wider range of workflows.
DaVinci Resolve 19 has introduced a significant number of AI-driven tools that aim to streamline the video editing process. One of the most talked about is IntelliTrack, which uses AI for object tracking and stabilization, automating what used to be a very manual process. UltraNR, another AI-powered feature, focuses on noise reduction, enhancing both audio and visual quality. It's worth noting that it seems to be a general improvement over older, non-AI based approaches.
The software now features Face Refinement, a tool that utilizes AI for sophisticated image processing, allowing editors to quickly adjust elements like skin tone, eyes, and even the lighting of a subject's face. It's a powerful tool that has seen a lot of use in the community for improving portrait-oriented footage. Blackmagic Design has described Resolve 19 as having over 100 new features, positioning it as one of the most cutting-edge video editing software available.
Much of the power behind these features comes from the DaVinci Neural Engine, a sophisticated machine learning system optimized for Apple's M-series hardware. There's been a noticeable improvement in AI functionality across Macs running Resolve 19 since the rollout of the M-series. Another interesting development is the introduction of Voice Isolation, which applies AI to clean up audio, making voices clearer in noisy environments. Blackmagic Design has hinted that this feature is drawing inspiration from other platforms like Adobe, suggesting that a bit of healthy competition is driving innovation in this space.
DaVinci Resolve, in its usual fashion, combines editing and color grading in one application. This comprehensive approach to post-production remains a core strength that makes it stand out in the market. It's also important to remember that the free version of DaVinci Resolve allows for multi-user collaboration and includes HDR grading, making professional-level features accessible to a wider user base. Finally, DaVinci Resolve 19 has been optimized for macOS Sonoma, promising improved performance and user experience across a range of devices. While a nice feature, it's not quite a universal fix, as various hardware configurations still impact the outcome differently.
DaVinci Resolve on macOS Sonoma Performance Insights and User Experiences in 2024 - Hardware Encoding Improvements for M1 Macs
DaVinci Resolve's latest versions have brought welcome improvements to hardware encoding on Apple's M1 Macs, especially for those who rely on it for professional video editing. Versions like 173 and 174 are said to deliver rendering speeds up to five times faster for M1 Pro and Max users compared to prior releases. A new ability to utilize hardware-accelerated H.265 encoding is a step forward, giving users a more nuanced control over the balance between render time and output quality. Users have noticed a considerable reduction in render times, with some seeing their workflows speed up by as much as 65%. However, it's interesting that, despite these hardware gains, the M1's CPU cores don't seem to be working at full capacity during rendering. This has led some to speculate that there might be untapped potential for even better performance if the software is further optimized to fully leverage Apple's silicon. While these advancements in hardware encoding are notable, they also highlight a path for future optimization, potentially leading to even more efficient and powerful editing workflows on these machines.
DaVinci Resolve's performance on Apple Silicon Macs, particularly those with M1 chips, has been significantly enhanced by hardware encoding improvements. The M1 and M1 Pro chips have dedicated encoding and decoding engines built specifically for formats like H.264 and H.265. This dedicated hardware can drastically reduce rendering times, sometimes even exceeding the performance of specialized, high-end graphics cards.
Interestingly, these hardware improvements not only boost speed but also enhance energy efficiency. M1 Macs can now encode video at lower power levels, extending battery life during extended editing sessions without sacrificing performance. This is a valuable asset for anyone who does a lot of on-the-go video editing. The hardware acceleration on M1 chips has translated into notably smoother real-time playback during editing, which is a substantial benefit, particularly when working with high-resolution video. Users can see smoother previews and refine their edits without the need for lots of intermediate render steps, leading to a more fluid workflow.
However, to maximize the advantage, it's important to use software optimized for Apple Silicon. The latest iterations of DaVinci Resolve are a good example of this, showing a clear performance boost. This optimization extends beyond the software itself – keeping both the operating system and the software up-to-date seems crucial for unlocking the full potential of these improvements. M1 chips are surprisingly adept at managing multiple video streams simultaneously, making the editing process more fluid when dealing with complex timelines and numerous effects.
The M1 chips' Neural Engine works in concert with hardware encoding to enhance image processing tasks like noise reduction during the encoding process. This translates to higher-quality output without significant increases in rendering times. This feature makes a difference for content creators aiming for the best possible video quality.
Thermal management is usually a concern when a computer is under heavy load, but M1 Macs have a unique unified thermal management system that handles both CPU and GPU workloads together. This intelligent approach helps to prevent the system from overheating and experiencing performance throttling during long, demanding rendering processes.
Another benefit of the hardware encoding improvements is support for advanced video formats and high levels of compression, like AV1, which weren't as readily supported on older hardware. This allows for smaller file sizes without a noticeable reduction in quality, which is important for sharing content online or storing footage more efficiently.
In addition, these improvements leverage adaptive refresh technologies, which automatically adjust display settings during editing, minimizing lag and improving overall responsiveness. Some users who focused on H.265 encoding have reported impressive performance gains—as much as a 50% boost—when using M1 Macs compared to older Intel-based systems. This real-world data suggests that moving to Apple Silicon can significantly enhance workflow efficiency.
While there's been significant progress, users still need to monitor for bottlenecks that might arise and experiment with their software settings to determine the optimal performance profile for their specific workflows. Overall, the hardware encoding advancements on Apple Silicon Macs, particularly M1 chips, have led to remarkable performance improvements in DaVinci Resolve. The smoother editing experience, energy efficiency, and expanded capabilities create a powerful platform for those involved in video editing and production.
Upscale any video of any resolution to 4K with AI. (Get started for free)
More Posts from ai-videoupscale.com: