TECHNICAL EVALUATION • AGENTIC RUNTIMES

OpenHands AI Agent Features vs Devin vs Manus: Which Agent Should You Use in 2026?

By Abdullah Zulfiqar • Lead Benchmark Evaluator

Verified 26 September 2026 • 14 min read

When evaluating openhands ai agent features vs devin vs manus, the most critical mistake developers make is assuming these three tools compete in the same product category. They do not. OpenHands is an extensible, open-source execution runtime that turns frontier LLMs into autonomous coding agents inside your local containers. Devin is a turnkey, commercial AI software engineer built for engineering teams who want tickets converted into tested GitHub pull requests without managing infrastructure. Manus is a multimodal, general-purpose autonomous workflow agent engineered for browser navigation, wide research, document synthesis, and rapid prototyping rather than deep repository maintenance.

If you pick the wrong tool for your technical stack, you will either drown in infrastructure configuration when you wanted instant team ticket resolution, or hit opaque quota walls when you needed an unconstrained local debugging environment. Below is the empirical, side-by-side technical breakdown based on direct evaluation across all three platforms, re-verified with live pricing, ownership records, and SWE-bench Verified leaderboard figures as of 26 September 2026.

OpenHands AI Agent Features vs Devin vs Manus: Side-by-Side Table

Here is how OpenHands, Devin, and Manus compare across 21 core engineering parameters, including licensing, self-hosting autonomy, LLM interoperability, quota structures, and enterprise data controls.

How much do OpenHands, Devin and Manus cost?

OpenHands is completely free to run locally with your own LLM API keys, Devin starts at $20 per month for individual cloud sessions, and Manus operates on a monthly credit pool starting at $20.

Understanding the economic structure of these three agents requires looking past sticker prices. OpenHands operates on a transparent “infrastructure plus raw tokens” model, Devin uses subscription tiers with unreleased numeric quota ceilings, and Manus meters usage through task-based credit deductions.

Pricing Notice: On 14 April 2026, Cognition completely overhauled Devin’s pricing, retiring the legacy $20 base plan with Agent Compute Units (ACUs) and the rigid $500/month Team plan. Many outdated comparison articles still cite $500/month for Devin; that tier no longer exists. Furthermore, Cognition does not publish the exact numeric sizes of its daily or weekly quotas, which refresh asynchronously.

To demonstrate what these pricing structures look like in daily practice, let’s examine a realistic scenario: a solo developer executing 20 substantive development tasks per month (such as fixing an edge-case bug, adding a REST endpoint with tests, or migrating an ORM schema).

Assuming each medium repository task requires an average of 120,000 context tokens and 4,000 generated completion tokens across iterative agent execution loops:

• OpenHands (Claude 3.5 Sonnet BYOK): Software cost is $0. Using Anthropic API rates ($3.00/M input, $15.00/M output), each task costs: (120,000 × $0.000003) + (4,000 × $0.000015) = $0.36 + $0.06 = $0.42 per task. For 20 tasks, your total monthly cost is $8.40. If you use Claude 3.7 Sonnet with extended thinking tokens averaging $1.20 per complex task, your monthly bill is approximately $24.00. See our guide on the best Claude model for coding for token consumption benchmarks.
• Devin (Pro Plan): Base cost is $20.00/month. The included agent quota comfortably covers 20 moderate tasks spread across the month. However, if you execute 10 tasks in a single weekend, you will likely exhaust your weekly quota cap, forcing you to wait for quota refresh or incur extra usage at Cognition’s API pass-through billing.
• Manus (Basic Plan): Base cost is $20.00/month for 4,000 credits. A simple web app or wide research task consumes approximately 150 to 250 credits. 20 tasks require between 3,000 and 5,000 credits. On the Basic tier, you will exhaust your 4,000 credits around task 16 or 17, requiring a top-up or the $40/month Plus plan.

Autonomy and workflow — what each agent actually does when you give it a task

When assigned a task, OpenHands executes tool calls inside an isolated Docker sandbox, Devin builds an internal reproduction repo in an AWS cloud sandbox, and Manus decomposes multi-tab browser sessions into structured deliverables.

The core divergence between these platforms is how they perceive and interact with your computer environment. Let’s trace the execution steps each agent takes when handed an engineering assignment.

Benchmarks: SWE-bench, OpenHands Index and GAIA

OpenHands achieves up to 73.8% on SWE-bench Verified when paired with frontier agent frameworks, while Devin SWE-2 remains private/unranked, and Manus claims an 86.5% Level 1 GAIA score in multimodal tasks.

A primary point of confusion in online discussions is comparing coding benchmark scores with general assistant benchmark scores. SWE-bench Verified measures whether an AI agent can resolve a real-world, multi-file GitHub issue in an actual Python repository. GAIA measures whether an agent can answer complex multimodal questions requiring web browsing, audio processing, and spreadsheet extraction. These benchmarks operate on entirely different scales and cannot be directly compared.

For live benchmark leaderboards across foundational coding models, explore our comprehensive AI coding benchmarks hub.

Manus AI GAIA benchmark score

The widely discussed manus ai gaia benchmark score stems from Manus’s March 2025 public unveiling, where the company reported scores of 86.5% on Level 1, 70.1% on Level 2, and 57.7% on Level 3 of the GAIA evaluation set.

These scores must be contextualized with extreme technical caution. First, they are self-reported launch claims from March 2025 and have not been independently reproduced on a frozen, public benchmark run. Second, GAIA measures general-purpose multimodal assistance—such as downloading a PDF, summarizing financial ratios, and answering multi-modal trivia—not writing complex multi-file production software. If you evaluate Manus expecting the 73.8% software engineering problem-resolution of OpenHands, you will be disappointed: Manus is an executive assistant and researcher, not a repository maintainer.

Privacy, data control and self-hosting

OpenHands delivers total data sovereignty through local Docker containers, Devin offers enterprise VPC isolation with US SOC-2 Type II attestation, and Manus routes data through proprietary cloud infrastructure.

For engineering leaders with strict IP compliance, customer data protection mandates, or air-gapped security policies, execution architecture is an absolute dealbreaker:

• OpenHands (Local & On-Premises): Code never leaves your hardware unless you choose to send prompts to a cloud LLM. Because OpenHands connects directly to local inference engines via Ollama or vLLM, you can run a 100% offline, air-gapped coding agent with zero data leakage risk. Learn how to configure local inference in our guide on how to run LLMs locally.
• Devin (Managed Cloud Sandbox): Code is pulled into an ephemeral AWS VM. Cognition maintains US SOC-2 Type II certification and promises enterprise customers that customer code is never used to train proprietary foundation models. Enterprise clients can deploy Devin inside their own dedicated VPC with SAML/OIDC single sign-on.
• Manus (Proprietary Multi-Tenant Cloud): Manus runs entirely across multi-tenant cloud worker clusters. You cannot self-host Manus, and all browsing data, credentials, and generated documents pass through its central infrastructure.

Which one should you choose?

Select OpenHands if you need codebase privacy and model flexibility, Devin if you want an autonomous teammate integrated with Jira, or Manus if your tasks require browser navigation and non-coding output.

Recommendations by Developer Persona:

1. Solo Indie Developer: Pick OpenHands. You get unmetered coding sessions at raw API cost without paying a $20/month subscription floor or hitting mysterious weekly quotas.
2. Startup Engineering Team of 5: Pick Devin. Devin’s native Jira, Linear, and Slack hooks enable asynchronous ticket resolution and automated PR generation without spending engineering hours configuring container orchestration.
3. Enterprise with Compliance / Air-Gapped Code: Pick OpenHands. Its MIT licence, VPC support, and ability to connect to on-premise Ollama instances guarantee proprietary code never crosses perimeter firewalls.
4. Non-Technical Founder: Pick Manus. It excels at synthesizing pitch slides, competitive market research, and functional proof-of-concept web prototypes without requiring terminal or Git literacy.
5. Technology Researcher / Product Analyst: Pick Manus. Its Browser Operator automates complex multi-tab information gathering across public internet repositories and outputs structured executive summaries.

Scorecard: editorial rating across six dimensions

Our editorial scorecard rates each agent across six core dimensions: cost transparency, control and privacy, coding depth, ease of setup, non-coding versatility, and team collaboration.

Timeline: how the three agents got here

The competitive landscape between OpenHands, Devin, and Manus shifted dramatically across multiple pivotal milestones from early 2024 through September 2026:

Alternatives worth comparing

Depending on your development setup, several other agentic coding harnesses are worth benchmarking alongside OpenHands, Devin, and Manus:

• Claude Code: Anthropic’s official terminal-native agentic coding tool. It operates directly inside your terminal, requiring zero Docker configuration. Read our in-depth Claude Code review and alternatives for complete CLI benchmarks.
• Cursor: An AI-first code editor fork of VS Code with powerful inline completions, background agent modes, and multi-file editing. Compare it in our Cursor and Claude Code alternatives.
• Aider: The gold standard for lightweight, git-integrated pair programming in the terminal. Excellent for fast CLI edits without container overhead.

Devin vs Claude Code

When contrasting devin vs claude code (often searched as devin ai vs claude code), developers are choosing between a managed cloud teammate and a local terminal-native power tool.

Devin operates as an autonomous, remote engineer in its own cloud VM: it accepts an issue from Jira or Slack, independently searches the codebase, and submits a finished GitHub pull request with tests. Claude Code, by contrast, runs directly in your local terminal session: it requires you to initiate commands, review bash tool calls, and supervise multi-file refactoring steps.

Verdict: Choose Claude Code if you want lightning-fast terminal agent workflows on your local machine with direct Anthropic API token billing. Choose Devin if you want tickets automatically picked up from Jira and converted into ready-to-merge pull requests while your team sleeps.

OpenHands vs Devin

The core contrast in openhands vs devin comes down to control versus turnkey convenience. OpenHands gives you total control over the execution stack: you can inspect every line of Python orchestrator code, swap in local open-weights models through Ollama, and run everything inside your own Docker daemon with zero data egress. Devin, on the other hand, trades code transparency for effortless workflow automation: you get pre-configured sandboxes, native Slack and Linear issue tracking, and automated video replays without managing Docker volumes or local containers.

Devin vs Manus

In evaluating devin vs manus, the deciding factor is your primary deliverable. Devin is an autonomous software engineer designed exclusively for codebases, unit tests, and GitHub pull requests. It does not browse consumer web pages or format corporate slide decks. Manus is a general-purpose workflow agent designed to operate browser tabs, scrape multi-page internet documents, and assemble presentations. If your goal is resolving a Python traceback, Devin is the proper tool; if your goal is compiling a 30-page market research deck with live web data, Manus is purpose-built for the job.

Manus AI vs Claude

Comparing manus ai vs claude is comparing an agentic harness to a frontier foundation model. Claude (by Anthropic) provides foundational reasoning, semantic understanding, and code generation through its model API. Manus is an agent application that uses frontier models—including Claude and OpenAI architectures—as its internal reasoning engine while providing the browser operator, DOM interaction tools, and Python execution environments necessary to carry out multi-step internet workflows.

Frequently Asked Questions