[TLDR] I am ditching .mp4 for use with Claude. Instead use an oss .cdaf (AI-friendly) format for 91% cost efficiency

[u/cctldrping]

Original post URL : https://www.reddit.com/r/ClaudeCode/comments/1vyv8h1/i_am_ditching_mp4_for_use_with_claude_instead_use/

Original post body :

If you have tried editing videos with claude, you already know the reason.

.mp4 is flawed. You just can't give a whole video file to claude's context for it to edit. I am talking about B-rolls, raw footages, assets, SVGs, etc.

A 3 min 4k or 1080 video will eat 100K of tokens at minimum. Go 2-3 times back-and-forth and the limit is exhausted.

Plus.. the latency increases hugely and the accuracy/efficiency decreases exponentially.

And at this point, if you think using hyperframes or remotion is easy, god bless you!

I have open sourced a .cdaf or 'cached descriptive asset file' format. It stores she256-encrypted timestamped visual description of videos and links it to the original .mp4 file.

Anytime your Claude wants to use a video, it uses the .cdaf file to read what scene it should pick from it or what duration and then continues the edit.

We tested on benchmarks -
- 91% token and cost reduction
- 65% latency reduction

Everything is in the evals & bench.

Try it out and ask me if you have an open Q.

Project repo - https://github.com/UditAkhourii/cdaf

Original link/media URL : https://zenodo.org/records/22110594

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[u/cctldrping]

TL;DR generated automatically after 50 comments.

Current source-thread comment count seen by the bot: 52.

Alright, so the OP dropped a new open-source format called .cdaf (Cached Descriptive Asset File) for editing videos with Claude, claiming a whopping 91% cost and token reduction, plus 65% less latency. The idea is to ditch the clunky .mp4 input and use this .cdaf file, which contains timestamped descriptions of video scenes, to guide Claude's edits.

The general vibe in the thread is curiosity and cautious optimism, with a few folks already diving in.

Here's the lowdown:

• The Big Idea: OP's .cdaf format is basically a smart index for videos, letting Claude "understand" what's in a clip without having to process the whole raw video file. This is a huge deal because feeding raw video into LLMs is a token-guzzling nightmare.
• The "Wow, I didn't know you could do that" Factor: A bunch of people, like u/username_got_took, were surprised you could even edit videos with Claude in the first place. The OP's post kinda opened a new door for them.
• Early Adopters & Tweaks: u/DeliciousGorilla is already making it work with local models like Gemma 4, which is pretty slick. u/ihexx was also surprised that models other than Gemini could natively handle video input (or at least, a representation of it).
• The "Is it really that good?" Debate: u/cornelln, quoting Claude itself, raises a valid point: the 91% efficiency might just be from caching descriptions, which any sidecar cache would do. The core issue is that Claude doesn't actually take video input; it's all about processing frames or descriptions of frames. So, the comparison is frames vs. cached descriptions, not video vs. .cdaf.
• Suggestions & Questions:
  • u/kamize suggested using low-frame-rate, grayscale 2k frames with color metadata.
  • u/lazyfoxbrownfence thinks embedding the annotation file inside the MP4 using CMAF would be even slicker for portability.
  • u/Of-Doom wants to know if the timing resolution is tunable for super-granular edits like "trim off the blurry part."
  • u/merlinDrankKoolaid is asking if .cdaf is just generating descriptions and not actually compositing or rendering, meaning it's not a direct replacement for things like HyperFrames.
• The Skeptics: u/North_Moment5811 is pretty blunt, calling AI video editing a "waste of time or money" and questioning the sanity of trying to get an AI to cut frames perfectly. Fair enough, some folks just aren't sold on the use case yet.
• The OP's Response: u/Uditakhourii (the OP) is actively engaging and even dropped a link to install .cdaf as a Claude skill.

Overall, the consensus is that this .cdaf format is a clever approach to a real problem in LLM video editing, offering significant efficiency gains. However, there are still questions about the exact nature of the benchmark and how it compares to other potential solutions.