BenchRank
#27 in AI Development PlatformsUpdated 2026-08

Hermes Agent

by Hermes Agent · Open-source desktop agent with shared memory across chat platforms

BenchRank score

56.7 — BenchRank score out of 100

Screenshots of Hermes Agent

Homepage · Hermes Agent

Homepage of Hermes Agent

Overview

Hermes Agent is an MIT-licensed agent from Nous Research, installed as a native app on macOS, Windows or Linux or through a terminal script. It connects to Telegram, Discord, Slack, WhatsApp, Signal, email and the CLI with a single shared memory. It also schedules tasks in natural language, runs isolated subagents, searches the web, and executes code in local, Docker, SSH, Singularity or Modal sandboxes.

Best for
Individuals wanting an open-source desktop agent they can reach from chat apps and the terminal
Pricing
No prices are shown; the site lists Free, Plus, Super and Ultra tiers, with all paid tiers including monthly credits and access to 300+ models.
Runs on
macOSWindowsCLI

Strengths and trade-offs

Strengths

  • MIT licensed, with native builds for macOS, Windows and Linux
  • One agent and one memory across Telegram, Discord, Slack and CLI
  • Five sandbox backends: local, Docker, SSH, Singularity and Modal
  • Subagents, scheduling and browser automation are built in

Trade-offs

  • No prices published for the Plus, Super or Ultra tiers
  • Version 0.19.1, so pre-1.0 and subject to change
  • Model access beyond the free tier depends on paid Nous Portal credits

How Hermes Agent markets itself

A structured read of the promise, proof and page design on Hermes Agent’s captured homepage.

Homepage capture

“THE AGENT THAT GROWS WITH YOU”

  • Angle: Outcome / benefit-led
  • Hero: Illustration

Pricing

Published plans and prices from Hermes Agent’s own pricing page.

How this score is made up

Each dimension is scored out of 100 and combined into the headline score using fixed weights.

  • MCP support

    Whether an agent can drive the product through the Model Context Protocol, and how much setup that takes.

  • API quality

    Public API surface: machine-readable spec, official SDKs, documented auth, errors, rate limits and versioning.

  • Documentation

    Publicly reachable docs — coverage, freshness, code samples and machine readability.

  • Agent friendliness

    How readable the site is to an automated client: llms.txt, structured data, server-rendered content, crawler access.

  • Changelog

    A public, dated record of what shipped and when — the clearest signal that a product is still alive.

  • Marketing site structure

    Whether the site answers a buyer's questions: clear positioning, the pages that matter, and accessibility.

  • Page speed

    How fast the site loads for real visitors: Chrome UX Report 75th-percentile LCP, INP and CLS, with a Lighthouse mobile run standing in where a site has too little traffic for field data.

  • Operational trust

    Status page and incident history, security disclosure, compliance and data-processing documentation.

Measured, but not part of the score

Useful to know, but not a mark for or against the product — so these do not affect the ranking.

  • Openness

    Source availability, self-hosting, data export and open standards. Scored and shown, but not part of the composite — paid SaaS is not worse for being paid SaaS.

  • Maintenance

    Release cadence and repository activity. Scored and shown, but not part of the composite — it is only measurable for open repositories.

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Where this comes from

The Hermes Agent pages BenchRank reads when it scores the product — its documentation, release notes, status and security pages, and its repository where there is one.

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