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Real head-to-head · same prompt, one shot

Hermes MoA vs DeepSeek V4 Pro

A panel of frontier models, merged by a chair. The model doesn't matter — the system does. vs DeepSeek's flagship tier — benched head-to-head against its own cheap Flash.

Hermes MoA · contextVaries (per-panel)
DeepSeek V4 Pro · context1M tokens
Hermes MoA · pricePanel + aggregator calls (via OpenRouter)
DeepSeek V4 Pro · priceAPI · pro tier
Hermes MoA · vendorHermes · Mixture of Agents
DeepSeek V4 Pro · vendorDeepSeek

What I tested — same prompt, two models

I run the same fixed prompt set through every new model the day it drops — same string, one shot, single HTML file out — and I score the result 0–10 on whether it ran, how close it hit the brief, and how good it looked. Below is what came out when I gave the exact same prompts to Hermes MoA and DeepSeek V4 Pro, side by side, on 47 shared tasks inside the Agent Operating System.

Both models were given identical prompts inside the Agent Operating System — no help, no iteration, no "best of N" tricks. I run each prompt once, save the HTML file the model produces, and score it 0–10 on whether it ran, how close it hit the brief, and how good it looked. The scoring is mine. The verdicts below are pulled from my source comparison guides at agentos.guide where I publish every score and the reasoning behind it.

Hermes MoA · Run from the Mixture tab in the Hermes Agent OS. On this bench the panel built each demo and the aggregator merged the best of every draft.

DeepSeek V4 Pro · Benched on all 50 GoldieBench tasks via api.deepseek.com with the same pipeline as the Flash 0731 run, then published as a live side-by-side: goldiebench.com/vs-live/deepseek-flash-vs-pro.html loads both builds of every task in twin panes.

Side-by-side on 50 shared tasks

Click any cell to play that model's actual one-shot attempt. Medals are derived from my 0–10 scores per task (highest = 🥇, second = 🥈, third = 🥉).

Task ↓
Hermes MoA
DeepSeek V4 Pro
Game
🥇Hermes MoA on Arcade
DeepSeek V4 Pro on Arcade
Game
Hermes MoA on Crypt
DeepSeek V4 Pro on Crypt
Game
🥈Hermes MoA on Dogfight
DeepSeek V4 Pro on Dogfight
Game
🥇Hermes MoA on Doom
DeepSeek V4 Pro on Doom
🥈Hermes MoA on Dragonflight
DeepSeek V4 Pro on Dragonflight
Hermes MoA on Dragonrealm
DeepSeek V4 Pro on Dragonrealm
Game
Hermes MoA on Flightsim
DeepSeek V4 Pro on Flightsim
Game
Hermes MoA on Game
DeepSeek V4 Pro on Game
Game
Hermes MoA on Gtadrive
DeepSeek V4 Pro on Gtadrive
Game
Hermes MoA on Gtafoot
DeepSeek V4 Pro on Gtafoot
🥉Hermes MoA on Neonblaster
DeepSeek V4 Pro on Neonblaster
Game
Hermes MoA on Neoncity
DeepSeek V4 Pro on Neoncity
Game
Hermes MoA on Neonracer
DeepSeek V4 Pro on Neonracer
Hermes MoA on Nordiccrypt
DeepSeek V4 Pro on Nordiccrypt
Game
Hermes MoA on Outrun
DeepSeek V4 Pro on Outrun
Game
Hermes MoA on Parachute
DeepSeek V4 Pro on Parachute
Game
🥇Hermes MoA on Pool
DeepSeek V4 Pro on Pool
Game
Hermes MoA on Racing
DeepSeek V4 Pro on Racing
Game
Hermes MoA on Raycaster
DeepSeek V4 Pro on Raycaster
Game
🥉Hermes MoA on Rpg
DeepSeek V4 Pro on Rpg
Game
Hermes MoA on Skyrim
DeepSeek V4 Pro on Skyrim
Hermes MoA on Twilightvale
DeepSeek V4 Pro on Twilightvale
Game
Hermes MoA on Voxelcraft
DeepSeek V4 Pro on Voxelcraft
Page
Hermes MoA on Aipbpromo
DeepSeek V4 Pro on Aipbpromo

Strengths & weaknesses I logged

Hermes MoA

Strengths

  • On GoldieBench, the MoA panel's galaxy edged solo Opus 4.8 — 8.6 vs 8.5 — with a denser 24k-particle spiral (the system beats the model)
  • Two gold + one silver across its first three one-shot builds (galaxy, fireworks, arcade)
  • Vendor-agnostic — swap any OpenRouter model into a panel or aggregator slot without touching the workflow

Trade-offs

  • Latency is the panel's slowest draft plus the aggregator pass — ~110–140s per single-file build vs a solo model's one call
  • Costs more per task than any single model (every panel slot + the aggregator are separate calls)
  • Only 3 of 42 bench tasks run so far — a representative slice, not the full board

DeepSeek V4 Pro

Strengths

  • Flagship reasoning tier on the same official API and 1M context as Flash
  • Ran the identical 50-prompt set as V4 Flash 0731 — a clean same-vendor A/B
  • Reasoning-first: thinks before writing every build

Trade-offs

  • Unranked — builds are on the bench but not yet scored by the Opus vision judge
  • Slower and pricier per build than Flash — the whole question is whether that buys quality

Pricing & context — the spec sheet

Spec Hermes MoA DeepSeek V4 Pro
VendorHermes · Mixture of AgentsDeepSeek
Context windowVaries — the sum of the panel models' contexts (Opus 4.8 + GPT-5.5)1,000,000-token context window
PricePanel + aggregator calls (via OpenRouter)API · pro tier
Pricing detailHermes Mixture of Agents dispatches one prompt to a configurable panel of frontier models in parallel, then a named aggregator reads every draft and writes one better final answer. Default panel: Claude Opus 4.8 + GPT-5.5, aggregated by Opus 4.8 — all via the OpenRouter key. Unlike a black-box ensemble, every slot is yours to swap from the Mixture tab in the Agent OS.DeepSeek's flagship tier, benched on `deepseek-v4-pro` via api.deepseek.com — the exact same 50 one-shot prompts, skill-infused game prompt and pipeline as the V4 Flash 0731 run, so the two runs are directly comparable side by side. DeepSeek's own line on the 0731 Flash refresh is that its post-training now beats the older V4-Pro-Preview — this run tests the current Pro against that claim.
Release2026-06-282026-07
Bench coverage47/47 scored · avg 8.17/100/50 scored · avg —

The verdict — which should you pick?

Not enough scored shared tasks yet for a head-to-head average. The live demos for both are on the matrix above — play them and form your own opinion.

If you only run one of these inside your stack, the head-to-head average above is the call. If you can run both, my honest play is to wire Hermes MoA and DeepSeek V4 Pro both into the Agent Operating System and dispatch each from the kanban by task type — high-stakes single prompts where ensemble quality beats single-model speed → Hermes MoA, checking whether deepseek's pro tier is worth the premium over flash 0731 → DeepSeek V4 Pro. That's the same setup I run for the 4,000+ founders inside the AI Profit Boardroom.

FAQ — Hermes MoA vs DeepSeek V4 Pro

Which is better, Hermes MoA or DeepSeek V4 Pro?

On Goldie Bench, Hermes MoA averages no scored verdicts yet across the shared tasks, with 4 gold, 9 silver, 4 bronze overall. DeepSeek V4 Pro averages no scored verdicts yet, with 0 gold, 0 silver, 0 bronze. Not enough scored shared tasks yet to call a winner.

How much does Hermes MoA cost vs DeepSeek V4 Pro?

Hermes MoA: Hermes Mixture of Agents dispatches one prompt to a configurable panel of frontier models in parallel, then a named aggregator reads every draft and writes one better final answer. Default panel: Claude Opus 4.8 + GPT-5.5, aggregated by Opus 4.8 — all via the OpenRouter key. Unlike a black-box ensemble, every slot is yours to swap from the Mixture tab in the Agent OS. DeepSeek V4 Pro: DeepSeek's flagship tier, benched on `deepseek-v4-pro` via api.deepseek.com — the exact same 50 one-shot prompts, skill-infused game prompt and pipeline as the V4 Flash 0731 run, so the two runs are directly comparable side by side. DeepSeek's own line on the 0731 Flash refresh is that its post-training now beats the older V4-Pro-Preview — this run tests the current Pro against that claim.

What's the context window for Hermes MoA vs DeepSeek V4 Pro?

Hermes MoA has a Varies — the sum of the panel models' contexts (Opus 4.8 + GPT-5.5) context window. DeepSeek V4 Pro has a 1,000,000-token context window context window.

When should I pick Hermes MoA over DeepSeek V4 Pro?

Pick Hermes MoA for: High-stakes single prompts where ensemble quality beats single-model speed; Squeezing frontier-plus output from models you already have while Fable 5 / GPT-5.6 are still in preview; Production agents that want a configurable panel + vendor-redundancy on every call. The trade-off is the weaknesses we logged on the bench: Latency is the panel's slowest draft plus the aggregator pass — ~110–140s per single-file build vs a solo model's one call; Costs more per task than any single model (every panel slot + the aggregator are separate calls); Only 3 of 42 bench tasks run so far — a representative slice, not the full board.

When should I pick DeepSeek V4 Pro over Hermes MoA?

Pick DeepSeek V4 Pro for: Checking whether DeepSeek's pro tier is worth the premium over Flash 0731; Hard single-shot builds where extra reasoning depth may pay off. The trade-off is the weaknesses we logged on the bench: Unranked — builds are on the bench but not yet scored by the Opus vision judge; Slower and pricier per build than Flash — the whole question is whether that buys quality.

How does Goldie Bench score Hermes MoA vs DeepSeek V4 Pro?

Every demo on this page was built by Julian Goldie inside the Agent Operating System — same fixed prompt for both models, one shot, single HTML file out. Each result gets a 0–10 score on whether it ran, how close it hit the brief, and how good it looked. The highest score on each task gets gold; second gets silver; third gets bronze. See methodology for full provenance.

The same stack Julian uses

Run this stack yourself.

Every demo on this bench was built inside the Agent Operating System — one prompt, one shot, single HTML file out. The Agent OS, the prompts, the templates, the weekly walkthroughs and 4,000+ founders shipping with it every day all live inside the AI Profit Boardroom.

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