At CYFRON SOFTWARE TRADING, we’re always watching for tools that align with our philosophy: clean design, practical implementation, and efficient development workflows. A new entrant to the AI development landscape has recently caught our attention—Sonic, a coding-focused large language model (LLM) that’s been quietly making waves for its impressive speed and accuracy.
We recently observed a comparison between Sonic and GPT-5 on three common front-end tasks: translating a Figma design into HTML/CSS, animating text with GreenSock (GSAP), and building a scroll-triggered animation. The outcomes speak directly to what developers and product teams value most—speed, usability, and fidelity to visual design.
In the first task, Sonic converted a Figma layout into HTML and CSS in just 34 seconds, delivering code with minimal layout inaccuracies. GPT-5, while capable, took longer and produced more structural issues, including misaligned column widths and incorrect tag implementation. For teams under tight deadlines or iterating rapidly through prototypes, this time-saving could be pivotal.
The second test involved creating staggered text animations using GSAP. Sonic had a slight clipping issue but otherwise executed a visually coherent animation with accurate timing. GPT-5 avoided the clipping, but sacrificed character spacing consistency—a reminder that when generative tools handle interfaces, visual nuance matters. Sonic’s output was cleaner and quicker, making it more in line with our expectations for plug-and-play animation code.
The third and final prompt involved a scroll-triggered animation effect. Here too, Sonic produced smooth, elegant transitions that closely followed the request (fade-in from a starting Y = 200px and opacity set to zero). GPT-5 was functional, but its version felt less deliberate, lacking the fluidity developers look for when integrating animations into modern websites or web apps.
Across all three trials, Sonic came out ahead—particularly in performance. It also offers developers a substantial 256K token context window, which opens the door to more sophisticated workflows like multi-file component synthesis or context-aware code completions. For design-driven development, that token ceiling could allow an entire UI flow to be considered in a single generation.
While it’s important to note that only three prompts were used in the evaluation, early indications suggest Sonic is not just faster but often more precise in execution than GPT-5 for front-end tasks. That combination—speed and accuracy—can help developers eliminate friction between design intent and implementation, which is ultimately what builds lasting, high-quality digital experiences.
We believe that tools like Sonic can augment how front-end engineers, product designers, and interface builders work together. It doesn’t replace creative decision-making, but it smooths the path from prototype to code, letting teams focus more on purpose and less on boilerplate.
Sonic is free to use at the moment, and it’s worth trialing in workflows where responsiveness and semantic accuracy are key. At CYFRON, we’ll be watching how it evolves—and sharing insights on how such tools can support our mission: delivering software that feels intentional, elegant, and simple to use.
We recently observed a comparison between Sonic and GPT-5 on three common front-end tasks: translating a Figma design into HTML/CSS, animating text with GreenSock (GSAP), and building a scroll-triggered animation. The outcomes speak directly to what developers and product teams value most—speed, usability, and fidelity to visual design.
In the first task, Sonic converted a Figma layout into HTML and CSS in just 34 seconds, delivering code with minimal layout inaccuracies. GPT-5, while capable, took longer and produced more structural issues, including misaligned column widths and incorrect tag implementation. For teams under tight deadlines or iterating rapidly through prototypes, this time-saving could be pivotal.
The second test involved creating staggered text animations using GSAP. Sonic had a slight clipping issue but otherwise executed a visually coherent animation with accurate timing. GPT-5 avoided the clipping, but sacrificed character spacing consistency—a reminder that when generative tools handle interfaces, visual nuance matters. Sonic’s output was cleaner and quicker, making it more in line with our expectations for plug-and-play animation code.
The third and final prompt involved a scroll-triggered animation effect. Here too, Sonic produced smooth, elegant transitions that closely followed the request (fade-in from a starting Y = 200px and opacity set to zero). GPT-5 was functional, but its version felt less deliberate, lacking the fluidity developers look for when integrating animations into modern websites or web apps.
Across all three trials, Sonic came out ahead—particularly in performance. It also offers developers a substantial 256K token context window, which opens the door to more sophisticated workflows like multi-file component synthesis or context-aware code completions. For design-driven development, that token ceiling could allow an entire UI flow to be considered in a single generation.
While it’s important to note that only three prompts were used in the evaluation, early indications suggest Sonic is not just faster but often more precise in execution than GPT-5 for front-end tasks. That combination—speed and accuracy—can help developers eliminate friction between design intent and implementation, which is ultimately what builds lasting, high-quality digital experiences.
We believe that tools like Sonic can augment how front-end engineers, product designers, and interface builders work together. It doesn’t replace creative decision-making, but it smooths the path from prototype to code, letting teams focus more on purpose and less on boilerplate.
Sonic is free to use at the moment, and it’s worth trialing in workflows where responsiveness and semantic accuracy are key. At CYFRON, we’ll be watching how it evolves—and sharing insights on how such tools can support our mission: delivering software that feels intentional, elegant, and simple to use.