Higgsfield AI is debuting a 95-minute fully AI-generated film at Cannes called "Hell Grind" that reportedly cost $500,000 to make, $400,000 of which was spent on compute alone. The project took just two weeks to produce and is intended to showcase the startup's AI production tools. But it also underscores the current limits of AI filmmaking: thousands of detailed prompts, endless iteration, high costs, and plenty of traditional filmmaking judgment were still required. The Wall Street Journal reports: What might surprise viewers is how much technical film know-how was needed to create the movie, said Adil Alimzhanov, a content lead at Higgsfield who also worked on it. "You have to understand camera composition, which shots are changed. Like you can't have two close-ups back to back, you have to start with an establishing shot," he said. "You still need those filmmaking skills." Higgsfield, which was valued at $1.3 billion in its latest funding round earlier this year, crossed $400 million in annual revenue run rate in May. It doesn't make the actual video-generation models, relying instead on existing tools like Google's Veo 3. But it does provide the tooling on top to make sure that the visuals are consistent across all the incoming generations.
The core of the movie-making process here was prompting the AI models and getting clips back, Alimzhanov said. Each prompt would generate about 15 seconds of footage. Those 15 seconds needed to be generated a number of times, with tweaks to the prompt to get the best possible version. The first 25 minutes of the movie required 16,181 initial video generations, which ended up as 253 final shots. One of the biggest difficulties in making longer-form films with AI is maintaining consistency across the outputs. AI models can be unpredictable, and a feature-length film can't have scenes that look completely different from one moment to the next.
Because of that, every prompt had to be extremely long and detailed. Each one would typically start with a prefix that defined requirements like style (8k IMAX, photorealistic), lighting (natural light only, "contre-jour" backlight, camera on shadow side) and the type of camera it should look like it was being shot on ("cine lens," 180-degree shutter motion blur). The lighting was key to avoiding the AI sheen that typically gets branded as "slop," said Alimzhanov. AI-generated video tends to over-light scenes in an unnatural way. That prefix would also have to remind the AI to obey the laws of physics with wording like: "gravity and inertia respected -- mass has real weight, correct contact shadows, no floating props." The individual prompts were, on average, 3,000 words each.
One aspect of what Higgsfield has built, and sells to clients, is an AI tool that generates these complex, detailed prompts. Users can enter a page from the original script, and the Higgsfield tool will return with a prompt that could be thousands of words long, designed to create production-quality outputs. And all that prompting is how the company racked up a $400,000 AI compute bill on the project. Co-founder and CEO Alex Mashrabov, however, noted that working with "cloud" providers, like Nebius and CoreWeave, rather than big hyperscalers, helped it keep costs from going even higher. You can watch the trailer for Hell Grind on YouTube and judge the results for yourself.
The core of the movie-making process here was prompting the AI models and getting clips back, Alimzhanov said. Each prompt would generate about 15 seconds of footage. Those 15 seconds needed to be generated a number of times, with tweaks to the prompt to get the best possible version. The first 25 minutes of the movie required 16,181 initial video generations, which ended up as 253 final shots. One of the biggest difficulties in making longer-form films with AI is maintaining consistency across the outputs. AI models can be unpredictable, and a feature-length film can't have scenes that look completely different from one moment to the next.
Because of that, every prompt had to be extremely long and detailed. Each one would typically start with a prefix that defined requirements like style (8k IMAX, photorealistic), lighting (natural light only, "contre-jour" backlight, camera on shadow side) and the type of camera it should look like it was being shot on ("cine lens," 180-degree shutter motion blur). The lighting was key to avoiding the AI sheen that typically gets branded as "slop," said Alimzhanov. AI-generated video tends to over-light scenes in an unnatural way. That prefix would also have to remind the AI to obey the laws of physics with wording like: "gravity and inertia respected -- mass has real weight, correct contact shadows, no floating props." The individual prompts were, on average, 3,000 words each.
One aspect of what Higgsfield has built, and sells to clients, is an AI tool that generates these complex, detailed prompts. Users can enter a page from the original script, and the Higgsfield tool will return with a prompt that could be thousands of words long, designed to create production-quality outputs. And all that prompting is how the company racked up a $400,000 AI compute bill on the project. Co-founder and CEO Alex Mashrabov, however, noted that working with "cloud" providers, like Nebius and CoreWeave, rather than big hyperscalers, helped it keep costs from going even higher. You can watch the trailer for Hell Grind on YouTube and judge the results for yourself.
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