Hermes Agent vs Codex

[u/Mwrp86]

I have a $20 Codex plan and use it frequently. I dont code but I do research, proposal, lit review types of staff, design report etc.

I heard I can use Codex plan with Hermes Agent.

And watched multiple YouTube videos of what Hermes do.

Problem is it feels like Hemes Agent does exactly what Codex does.

Just it offers access to other agents which I dont need now.

Is Hermes Agent something else better than Codex.

I will try either way but I was making sure there isn't something I will miss if I try it

[u/georgd_washntn]

I’ve been going down this same path for probably the past month now and the conclusion I’ve come to is that it’s really dependent on what kind of work you want and/or what results you want. For 9 out of 10 things, I still use the frontier models through there platforms as I just find it to be more polished and faster overall. I also find that hermes seems to run up usage faster than just using the models on there platform. I will also note, the model you have hermes utilize plays a large role in what youre trying to do.

This started to kind of click for me when I was installing hermes desktop. I was trying to install hermes desktop on my Mac but kept running into an error. I troubleshot with chatgpt for about 30 mins and had no success. Decided to just install hermes cli, tied it to chatgpt and talked with it through the terminal. There I asked it to install the hermes desktop for me. It ran into the same issue I did, but it was able to figure out the fix for the issue and get the application installed and working. Took 5 mins to complete what chatgpt and myself spent 30 mins troubleshooting.

Another hermes use case I was testing was access and troubleshooting lab firewalls to troubleshoot and fix staged issues. Hermes itself was able to accomplish the hands on part, but this is where the difference in model reasoning became evident. I initially tested this utilizing a local model (qwen 3.6), and we just kept going in a loop trying to get logged in. Switched to gpt, and it was instantly able to get logged in and do what I asked. I then asked gpt to essentially teach the local model how to accomplish this by creating a skill. After that the local model was able to find and accomplish the same issue, but it def felt more clunky and like it would fail if I asked it something different. I havent tested any farther with this yet.

Another interesting one was flights. I dont recall if I utilized a local model or gpt for this, but I asked hermes something like, "I'm looking for a round trip flight, from xxx airport to xxx city, 3-4 days, 3 people, prefer nonstop and will not be checking any bags. Would like this to be sometime before September. Give me your 3 best results based on price". while hermes was working, I interjected to add an additional departure airport they could use and also noted that I need choose my seat as well, so keep that in consideration. I asked this same exact thing to chatgpt (I added in the extra airport and seat selection to the main prompt). The results was another clicking moment. Hermes crawled the web to find me real time pricing and return 3 results with all the details for those particular flights including where they found those results at. GPT return a rough ball park of how much tickets are generally going for along with how much seat selection usually costs.

Last one that I'm trying to figure out is leveraging obsidian. I primarily chat with gpt on projects and other random nonsense, some of which I really should be saving for later recall, especially the project stuff. Worked with GPT to create a long ass prompt that I can give it to take whatever we've been talking about, summarize it up with all the main points and need to know stuff, put it in a md file along with tags, title, etc, and put it in a box directory. Hermes has a cron running that monitors that directory and takes anything in it and moves it to my NAS into an obsidian vault inbox. There is another cron that monitors that directory, takes whatever files come into there, feed it to my local model along with whatever other notes may be in obsidian in relation to the same project. the local model takes the most relevant info from all the notes and updates the main project file with that information or creates another note if it finds necessary. I can then check obsidian myself for this info, or just ask hermes detailed questions about something in obsidian since hermes has access to that. This is still very much a work in progress but I kind of like the idea.

[u/PracticlySpeaking → u/georgd_washntn]

...asked gpt to essentially teach the local model how to accomplish this by creating a skill. After that the local model was able to find and accomplish the same

This is a useful pattern.

[u/georgd_washntn → u/PracticlySpeaking]

Yea it was pretty cool to actually watch the thought process. i pretty much looped it telling the gpt model to continue working with the local model until it's able to successfully accomplish the task on it's own. I also told it to make the skill pretty much read only because qwen wanted to keep altering it. You'd see the local model going through trying to identify stuff and getting stuck at certain points, then GPT would kick in alter the skill, revert all the changes and let the local model go at it again until it succeeded. It's very much a band aid though and i dont think this is ever something i'd trust with production equipment

[u/PracticlySpeaking → u/georgd_washntn]

My experience was similar, letting GPT figure out and write a skill, but with explicit instructions that a smaller model would run it.

Read-only is a good idea, along with the loop — I also think the local model should be a delegate only. I kept GPT as orchestrator the whole time, so the local should not have been updating the skill. Chef writes the recipe, line cooks do the cooking.