We benchmarked Codex alone against Codex routed through Edgee's compression gateway on the same repo, with the same model, under the same workflow. The result: Codex + Edgee used 49.5% fewer input tokens, improved cache hit rate from 76.1% to 85.4%, and reduced total session cost by 35.6%. This post breaks down why context compression makes Codex more efficient, more frugal, and materially cheaper to run without sacrificing useful output.
That's it! And it works the same with Claude Code.
The results:
As a gateway, Edgee can optimize the requests that are sent to OpenAI, remove noise and waste, and cut input token usage almost in half.
We ran a controlled benchmark (see the video): same repo, same model (gpt-5.4), same task sequence. One session with plain Codex, one with Codex routed through Edgee.
Input tokens: −49.5%
Total cost: −35.6%
Cache hit rate: from 76.1% to 85.4%
The cache hit rate improvement is the part I find most interesting. By sending leaner prompts, @OpenAI cache is hit more often, so the savings compound beyond just the compression ratio.
Here's what makes this different from other token compression tools: we pull token counts directly from the OpenAI API usage fields. No character-based estimates. The numbers are what you're actually billed for.
Really interesting concept. Token compression plus routing in one layer feels powerful. How do you decide what gets compressed without affecting output quality?
35.6% is an oddly specific number, which makes me trust it more than "save up to 50%." What's actually being compressed, prompt-side context pruning, response caching, or something closer to semantic dedup across a session? Asking because I've been eyeing my own API bill lately and the honest breakdown matters.
Very cool product ! I'm using it for 3 weeks and it's very efficient. A game changer to controle API costs.
Coolest launch of the day!! Btw what kinds of transformations are you applying like semantic compression, deduplication, summarization or something else???
That's a very specific figure — I like that. Is that an average across user sessions or a median? And what does the distribution look like — are most users clustered around that number or is it more bimodal between light and heavy usage?
About Edgee Codex Compressor on Product Hunt
“Use Codex at 35.6% lower costs”
Edgee Codex Compressor launched on Product Hunt on April 12th, 2026 and earned 161 upvotes and 14 comments, placing #5 on the daily leaderboard. We benchmarked Codex alone against Codex routed through Edgee's compression gateway on the same repo, with the same model, under the same workflow. The result: Codex + Edgee used 49.5% fewer input tokens, improved cache hit rate from 76.1% to 85.4%, and reduced total session cost by 35.6%. This post breaks down why context compression makes Codex more efficient, more frugal, and materially cheaper to run without sacrificing useful output.
Edgee Codex Compressor was featured in Software Engineering (42.3k followers) and Developer Tools (511k followers) on Product Hunt. Together, these topics include over 71.8k products, making this a competitive space to launch in.
Who hunted Edgee Codex Compressor?
Edgee Codex Compressor was hunted by fmerian. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Reviews
Edgee Codex Compressor has received 2 reviews on Product Hunt with an average rating of 5.00/5. Read all reviews on Product Hunt.
Want to see how Edgee Codex Compressor stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
fmerian
Hey PH 👋
We're launching the Codex Compressor today.
But first, what is Edgee?
Edgee is an AI Gateway for Coding Agents, and it helps you save tokens. It's really simple to use, you only need two command lines:
A first one to install Edgee CLI with curl or brew
And a simple edgee launch codex
That's it! And it works the same with Claude Code.
The results:
As a gateway, Edgee can optimize the requests that are sent to OpenAI, remove noise and waste, and cut input token usage almost in half.
We ran a controlled benchmark (see the video): same repo, same model (gpt-5.4), same task sequence.
One session with plain Codex, one with Codex routed through Edgee.
Input tokens: −49.5%
Total cost: −35.6%
Cache hit rate: from 76.1% to 85.4%
The cache hit rate improvement is the part I find most interesting. By sending leaner prompts, @OpenAI cache is hit more often, so the savings compound beyond just the compression ratio.
Here's what makes this different from other token compression tools: we pull token counts directly from the OpenAI API usage fields. No character-based estimates. The numbers are what you're actually billed for.
⭐️ Please, give a star to our brand new OSS repository, we need support ;)
And don't hesitate to try, it's free!
Happy to answer any questions here all day. 🙏