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

Hermes MoA vs Kimi K2.7 · Fast

A panel of frontier models, merged by a chair. The model doesn't matter — the system does. vs Fast mode — top speed, minimal thinking.

Hermes MoA · contextVaries (per-panel)
Kimi K2.7 · Fast · context256K tokens
Hermes MoA · pricePanel + aggregator calls (via OpenRouter)
Kimi K2.7 · Fast · priceFlat plan (no per-token bill)
Hermes MoA · vendorHermes · Mixture of Agents
Kimi K2.7 · Fast · vendorMoonshot AI

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 Kimi K2.7 · Fast, side by side, on 42 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.

Kimi K2.7 · Fast · Wired into Agent OS as the snappy default — first-pass attempts, agent chatter, live demos.

Side-by-side on 42 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
Kimi K2.7 · Fast
Game
🥇Hermes MoA on Arcade
Kimi K2.7 · Fast on Arcade
Game
Hermes MoA on Crypt
Kimi K2.7 · Fast on Crypt
Game
🥈Hermes MoA on Dogfight
Kimi K2.7 · Fast on Dogfight
Game
🥇Hermes MoA on Doom
Kimi K2.7 · Fast on Doom
🥈Hermes MoA on Dragonflight
Kimi K2.7 · Fast on Dragonflight
Hermes MoA on Dragonrealm
Kimi K2.7 · Fast on Dragonrealm
Game
Hermes MoA on Game
Kimi K2.7 · Fast on Game
🥈Hermes MoA on Neonblaster
Kimi K2.7 · Fast on Neonblaster
Game
Hermes MoA on Neoncity
Kimi K2.7 · Fast on Neoncity
Game
Hermes MoA on Neonracer
Kimi K2.7 · Fast on Neonracer
Hermes MoA on Nordiccrypt
Kimi K2.7 · Fast on Nordiccrypt
Game
Hermes MoA on Outrun
Kimi K2.7 · Fast on Outrun
Game
🥇Hermes MoA on Pool
Kimi K2.7 · Fast on Pool
Game
Hermes MoA on Racing
Kimi K2.7 · Fast on Racing
Game
Hermes MoA on Raycaster
Kimi K2.7 · Fast on Raycaster
Game
🥈Hermes MoA on Rpg
Kimi K2.7 · Fast on Rpg
Game
🥉Hermes MoA on Skyrim
Kimi K2.7 · Fast on Skyrim
Hermes MoA on Twilightvale
Kimi K2.7 · Fast on Twilightvale
Game
Hermes MoA on Voxelcraft
Kimi K2.7 · Fast on Voxelcraft
Page
Hermes MoA on Landing
Kimi K2.7 · Fast on Landing
Page
🥉Hermes MoA on Webos
Kimi K2.7 · Fast on Webos
Sim
Hermes MoA on Blackhole
Kimi K2.7 · Fast on Blackhole
Sim
🥇Hermes MoA on Boids
Kimi K2.7 · Fast on Boids
Sim
🥇Hermes MoA on Cloth
Kimi K2.7 · Fast on Cloth

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

Kimi K2.7 · Fast

Strengths

  • Lowest latency of the three Kimi modes for short builds
  • Same 256K context as Quality mode
  • Best when you need agent-loop responsiveness over polish

Trade-offs

  • Skips deeper reasoning passes — bronze-tier on tasks needing planning
  • Julian explicitly does not assign scores to Kimi modes on the standalone bench

Pricing & context — the spec sheet

Spec Hermes MoA Kimi K2.7 · Fast
VendorHermes · Mixture of AgentsMoonshot AI
Context windowVaries — the sum of the panel models' contexts (Opus 4.8 + GPT-5.5)256,000 tokens
PricePanel + aggregator calls (via OpenRouter)Flat plan (no per-token bill)
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.Same flat-rate plan as standard Kimi K2.7 — Fast mode is a runtime toggle, not a separate model. Vendor: Moonshot AI (moonshot.ai).
Release2026-06-282026-06
Bench coverage42/42 scored · avg 8.38/100/42 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 Kimi K2.7 · Fast 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, snappy iteration inside agent loops → Kimi K2.7 · Fast. That's the same setup I run for the 3,600+ founders inside the AI Profit Boardroom.

FAQ — Hermes MoA vs Kimi K2.7 · Fast

Which is better, Hermes MoA or Kimi K2.7 · Fast?

On Goldie Bench, Hermes MoA averages no scored verdicts yet across the shared tasks, with 12 gold, 8 silver, 4 bronze overall. Kimi K2.7 · Fast 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 Kimi K2.7 · Fast?

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. Kimi K2.7 · Fast: Same flat-rate plan as standard Kimi K2.7 — Fast mode is a runtime toggle, not a separate model. Vendor: Moonshot AI (moonshot.ai).

What's the context window for Hermes MoA vs Kimi K2.7 · Fast?

Hermes MoA has a Varies — the sum of the panel models' contexts (Opus 4.8 + GPT-5.5) context window. Kimi K2.7 · Fast has a 256,000 tokens context window.

When should I pick Hermes MoA over Kimi K2.7 · Fast?

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 Kimi K2.7 · Fast over Hermes MoA?

Pick Kimi K2.7 · Fast for: Snappy iteration inside agent loops; Short prompts where Quality mode would over-think; Live demos where latency matters more than the last 5% of polish. The trade-off is the weaknesses we logged on the bench: Skips deeper reasoning passes — bronze-tier on tasks needing planning; Julian explicitly does not assign scores to Kimi modes on the standalone bench.

How does Goldie Bench score Hermes MoA vs Kimi K2.7 · Fast?

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 3,600+ founders shipping with it every day all live inside the AI Profit Boardroom.

3,600+founders
258documented wins
38countries
$59/momonthly