Codex vs DeepSeek Harness vs Hermes: The Real-World Answer Is There's No Best Agent, Only the Right Seat

A foot may fall short; an inch may excel.
— Qu Yuan, “Bu Ju” (Warring States period)

What this is about

“Which agent is best?” may be the most-asked question right now. A late-August hands-on video answers it without benchmarks — by throwing three tools into the real work of running a forum: building a theme, fixing bugs, daily maintenance, fending off an attack. The answer isn’t a name; it’s a seating chart. Which connects straight to yesterday’s piece: to manage a crew of agents, draw the org chart first.

Three tools, three temperaments

Codex: official, a year-plus old, closed source, the most mature product. In the test it built a forum theme end to end — planned six steps itself, done in twenty-odd minutes; it handles five or six bugs dumped at once, and you can drag screenshots straight in. Its flaw: paired with a local model it over-edits — asked to remove rounded corners, it also flattened the user avatars nobody asked about.

Hermes: Python-based, the least flashy and the steadiest. Left alone without manual updates, it runs three weeks to a month without an error. When the forum came under attack, the host never touched the keyboard — Hermes blocked the attack, restored data, and quietly finished the tagging job every moderator had been avoiding.

DeepSeek Harness: open source, fastest-growing ecosystem (a hundred thousand stars in short order), and the prettiest codebase of the three. It also crashed in the field: one bug it simply couldn’t fix, until the host pushed the code to GitHub and let Codex clean up. The diagnosis is telling — some of its built-in tools it doesn’t know how to call; it can process images, yet insists on being given an image URL.

The host’s verdict, plainly: recommend Codex today, use Hermes for daily scripts and maintenance, and DeepSeek Harness — grand prospects, not yet a finished product — is for spare time.

The real savings aren’t in the tool, they’re in the seating

The most stealable move in the video is the cost structure. The token-heavy grunt work — reading code, long development runs — goes to a local Qwen3.8 27B (driven by one AMD 7900 XT, 128K context), free beyond electricity; only what the local model can’t handle goes to cloud DeepSeek V4 Flash to finish. A full day of moderate development plus ops: about 30 RMB. The same load on premium V4 Pro: 100+ a day. His own math: two months of that gap buys a 4090.

He’s honest about the price: the local model is slow (ten minutes on Flash versus half an hour locally) and a notch less sharp (the over-editing incident was the local model’s). So this isn’t “local is cheap, use local for everything” — it’s cheap first, expensive to finish. The same arithmetic as my RunPod piece, except he’s turned the answer into a daily routine.

One more detail I keep thinking about: the prettiest codebase of the three was the only one that crashed in real work. Elegant architecture and getting things done are different things — judge a tool by whether it finishes the job, not by how it reads. Same as reading company financials: the prettiest slide deck isn’t necessarily the profitable company.

One thing to take with you

The day I watched this I re-seated my own tool list: next to each AI tool I wrote down one of two words — “develop” or “on duty.” Development needs smart, because I’ll see its mistakes; duty needs steady, because when it fails I won’t be there. One of my tools was listed in both columns — that’s the hazard. You could spend five minutes today doing the same: one tool, one seat; the one that fits neither, don’t rush to use.

Sources

• Lunchuizhe, “Codex, DeepSeek Harness, or Hermes — which agent is best? Qwen3.8 27B / DeepSeek V4 Flash in real development,” uploaded 2026-08-23: youtu.be/NsTn8-Pewtc
• Yesterday’s piece: What Is Graph Engineering? Two Diagrams for a Team of Agents
• Earlier: Local LLMs: Buy the Card or Rent It? RunPod at NT$24 an Hour

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