Prime vs Hermes vs Pi (2026): Which Open-Source Coding Agent Actually Learns From You?

They all say the same sentence: "I'll learn from you."

Prime Agent, Hermes, and Pi — the three open-source agent harnesses people reach for most in 2026 — have all put self-improvement on the label. But read the fine print and they mean four different things. Pick the wrong one and you'll spend weeks rewiring your workflow to match the agent. Pick the right one and it pays you back every single day.

This is a practical comparison for anyone about to install one of them. I dug into the architecture, the memory, the self-improvement claims, and — with a well-earned grain of salt — the real benchmark numbers, so you can stop reading launch-day marketing and start choosing with your eyes open.

One honest caveat up front: benchmarks shift with every model and every benchmark. The numbers below are reported in third-party comparisons, not controlled tests. Read them as a compass, not a scoreboard.

The three one-liners

• Pi — the minimalist. A lean, terminal harness with powerful defaults and almost nothing built in. You add sub-agents, planning, and orchestration through a package catalog. It bends entirely to you.
• Hermes — the learner. Nous Research's self-hosted agent with a built-in learning loop. It turns your corrections and recurring workflows into persistent memory and self-created skills. It bends to neither — it remembers.
• Prime Agent — the recursive engine. Prime Intellect's harness treats context as a variable and delegates to sub-agents like function calls inside a Python REPL. It bends to the task.

Here's the part most comparisons skip: Prime is built on Pi. They share DNA. The real question isn't which is "best" — it's which philosophy matches how you actually work.

What each one really is

Pi: control through minimalism

Pi (pi.dev, source at github.com/earendil-works/pi) is a minimalist, open-source, terminal-based coding agent you run on your own machine. Its whole philosophy is restraint. On its own site, in its own words: "Pi ships with powerful defaults but skips features like sub-agents and plan mode. Ask Pi to build what you want, or install a package that does it your way."

That last sentence is the product. Pi refuses to bake in assumptions about how you work. Instead it ships an extensible core plus a package catalog where you install exactly the behavior you want — Claude Code-like sub-agents, fleet orchestration, live widgets — and nothing you don't.

The payoff is model freedom. Pi connects to 15-plus providers: Anthropic, OpenAI, Google Vertex, Azure, Amazon Bedrock, Cloudflare, xAI, Groq, and local models. Custom endpoints drop into ~/.pi/agent/models.json with no code. That same flexibility is what makes it cheap: run capable open models through a ~$10/month subscription route and it's arguably the cheapest capable open-model agent on the market.

Hermes: the agent that remembers

Hermes Agent (Nous Research, github.com/nousresearch/hermes-agent) is an open-source, self-hosted agent whose headline trait is a built-in learning loop. Its tagline — and it's not hype — is that it's "the only agent with a built-in learning loop": repeated corrections and durable workflow lessons become compact memory entries or procedural skills that improve over time.

Under the hood that means a four-layer memory system with a consent-aware design — the agent learns from you, but with an approval layer in front of what it stores. It also ships a messaging gateway (Telegram and friends) and runs code in sandboxed environments, which is why it's a favorite for local, long-running workflows. Where Pi strips features away, Hermes adds a memory layer on top.

Prime Agent: context as a variable

Prime Agent (Prime Intellect, github.com/PrimeIntellect-ai/prime-agent) is a coding and research agent for general, long-running work, built around two abstractions: the Recursive Language Model (RLM) and a self-improving Continual Harness.

The RLM is the interesting part. Instead of one flat prompt, Prime treats context as a variable and turns sub-agent delegation into function calls inside a persistent Python REPL. The model can spawn sub-LLMs, hand them tasks, and even let them evaluate its work — recursive sub-agents coordinate through direct agent-to-agent communication, all inspectable through an "Agents View." Prime inherits Pi's model freedom and layers a recursive, self-refining engine on top.

Head-to-head

Three open-source harnesses, one shared question: whose workflow should the agent bend to? Here's how they compare across the features that affect daily work.

Reading the table: Only Prime runs inside a persistent Python REPL — and it goes further, giving every sub-agent its own kernel. OS is a wash: all three are cross-platform. Self-improvement and long-term memory are built into Hermes and Prime but absent from Pi, which prefers a skill-file system you build up. Sub-agents and planning are native to Prime only; Pi calls them "sessions" and Hermes is strictly single-agent. Hermes is the only one with a messaging gateway for connected, multi-user setups.

What the benchmarks actually say

These are third-party, model-dependent figures. Different models and different task sets move the numbers a lot — but the ordering is a useful signal.

• On a composio "best harnesses" comparison, Pi-based configs led the pack (22 of 25 tasks on one test), with Hermes completing 20 of 25.
• On SWE-bench-style tasks, Pi reportedly scored 18/19, ahead of Claude Code and Codex, which tied around 12/18.
• On a DeepSeek V4 Flash harness comparison, Pi led at 66.7% (20 of 30), with Prime Agent at 62.5%.
• Prime's own testing claims it surpasses Codex and Claude Code in autonomous mode across frontier models — treat that as the vendor's pitch, not an independent result.

The through-line: Pi is a benchmarking favorite across independent comparisons, and Prime is the strongest pick for parallel, recursive work where its sub-agent architecture earns its keep. Hermes rarely tops raw benchmark tables, but its memory loop is a different game entirely — one benchmarks don't measure well.

How to choose

Choose Pi if you want control and cheap open models. It's the best pick when you like a lean default and enjoy layering features yourself, or when you run multiple providers and want to keep costs down. It's also the natural starting point — Prime is built on it.

Choose Hermes if you have repeated, long-running workflows and want the agent to remember how you work. Its learning loop and persistent memory pay off over days and weeks, not minutes. It's the agent that gets better the more you use it — and it runs self-hosted, where your data stays yours.

Choose Prime Agent if you're tackling large, parallel, long-running tasks — research, big refactors, multi-part builds. Its recursive sub-agents and Python-REPL architecture shine when a job is too big for a single pass, and it bundles research alongside coding.

The short version

All three are open-source, and all three share a philosophy of bending to your workflow — they simply disagree on the direction. Pi bends entirely to you. Hermes remembers you. Prime bends to the task, recursively.

• Want control and low cost? Pi.
• Want an agent that learns and remembers? Hermes.
• Want recursive power for big tasks? Prime Agent.

They're all free to try. The right answer depends less on benchmark tables and more on how you actually like to work — so pick the one that bends the right way.

Sources

• Pi Coding Agent · GitHub · Providers doc
• Hermes Agent — Nous Research · Docs · Persistent Memory
• Prime Agent — Prime Intellect · Blog · Recursive Language Models
• 8 Best AI Agent Harnesses in 2026 — Composio · Best Agent Harness for DeepSeek V4 Flash — Composio