SWE-agent Pricing & Plans 2026

Name: SWE-agent
Brand: SWE-agent
Availability: InStock

Complete pricing guide for SWE-agent. Compare all plans, analyze costs, and find the perfect tier for your needs.

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🆓Free Tier Available

⚡No Setup Fees

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Open Source (self-hosted)

Free

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Pricing sourced from SWE-agent · Last verified March 2026

Is SWE-agent Worth It?

✅ Why Choose SWE-agent

• Fully open-source under MIT license with an active community and ongoing research — over 17k GitHub stars and frequent releases from the Princeton NLP and Stanford teams
• Model-agnostic architecture supports GPT-4o, Claude (Sonnet/Opus), DeepSeek, and local LLMs via Ollama or any OpenAI-compatible endpoint, avoiding vendor lock-in
• State-of-the-art benchmark performance on SWE-bench (real GitHub issues) and on cybersecurity benchmarks like NYU CTF via the EnIGMA mode
• Sandboxed Docker execution through SWE-ReX with scalable backends for AWS, Modal, and Kubernetes, enabling safe batch processing of many issues in parallel
• Well-documented Agent-Computer Interface (ACI) with custom edit/search commands and linter feedback that meaningfully reduces LLM formatting errors on long tasks
• Dual-purpose utility: same codebase handles software engineering (bug fixes, feature patches) and offensive security tasks (CTF, vulnerability discovery)

⚠️ Consider This

• API costs add up quickly when using frontier models like GPT-4o or Claude Opus — a single SWE-bench run can consume significant tokens per issue
• Initial setup is heavier than consumer tools: requires Docker, API key configuration, and YAML-based agent configs rather than a one-click install
• No hosted UI out of the box — the primary interfaces are CLI, Python API, and an optional web demo, which is less accessible to non-developers
• Python-centric benchmarking and tooling; while the agent can edit any language, its evaluation harness and examples lean heavily on Python repositories
• Autonomy means it can make sweeping edits in a loop — without careful sandboxing and review, runs can waste compute or produce low-quality patches

What Users Say About SWE-agent

👍 What Users Love

✓Fully open-source under MIT license with an active community and ongoing research — over 17k GitHub stars and frequent releases from the Princeton NLP and Stanford teams
✓Model-agnostic architecture supports GPT-4o, Claude (Sonnet/Opus), DeepSeek, and local LLMs via Ollama or any OpenAI-compatible endpoint, avoiding vendor lock-in
✓State-of-the-art benchmark performance on SWE-bench (real GitHub issues) and on cybersecurity benchmarks like NYU CTF via the EnIGMA mode
✓Sandboxed Docker execution through SWE-ReX with scalable backends for AWS, Modal, and Kubernetes, enabling safe batch processing of many issues in parallel
✓Well-documented Agent-Computer Interface (ACI) with custom edit/search commands and linter feedback that meaningfully reduces LLM formatting errors on long tasks
✓Dual-purpose utility: same codebase handles software engineering (bug fixes, feature patches) and offensive security tasks (CTF, vulnerability discovery)

👎 Common Concerns

⚠API costs add up quickly when using frontier models like GPT-4o or Claude Opus — a single SWE-bench run can consume significant tokens per issue
⚠Initial setup is heavier than consumer tools: requires Docker, API key configuration, and YAML-based agent configs rather than a one-click install
⚠No hosted UI out of the box — the primary interfaces are CLI, Python API, and an optional web demo, which is less accessible to non-developers
⚠Python-centric benchmarking and tooling; while the agent can edit any language, its evaluation harness and examples lean heavily on Python repositories
⚠Autonomy means it can make sweeping edits in a loop — without careful sandboxing and review, runs can waste compute or produce low-quality patches

Pricing FAQ

What is SWE-agent and who built it?

SWE-agent is an open-source autonomous coding agent created by researchers at Princeton University and Stanford University. It was introduced in a NeurIPS 2024 paper and takes a GitHub issue as input, then uses an LLM to navigate the repository, edit files, and run tests to propose a fix. The same system, configured as EnIGMA, can also tackle offensive cybersecurity challenges.

Which language models can I use with SWE-agent?

SWE-agent is model-agnostic. It officially supports GPT-4o and other OpenAI models, Anthropic's Claude family (including Sonnet and Opus), DeepSeek, and any OpenAI-compatible endpoint — which means you can point it at local models served via Ollama, vLLM, or LM Studio. Model selection is handled in the agent config file.

Is SWE-agent free to use?

Yes. The SWE-agent codebase is fully open-source under the MIT license and free to self-host. The only costs are the LLM API fees you incur when using commercial models like GPT-4o or Claude; running it with a local model is free apart from compute.

How is SWE-agent different from tools like Devin or Cursor?

Devin is a closed, hosted autonomous agent with a managed UI and subscription pricing; Cursor is an interactive IDE with AI assistance. SWE-agent is an open-source, self-hostable agent framework focused on autonomously resolving issues end-to-end. It is research-grade software — you bring your own model and infrastructure, and you get full transparency into the agent's prompts, tools, and trajectories.

Can SWE-agent run safely on my codebase?

SWE-agent executes all commands inside Docker containers via its SWE-ReX runtime, which isolates file and network access from the host. For additional safety on private repos, you can use ephemeral sandboxes on Modal or AWS, and you should always review generated patches before merging — especially for long autonomous runs.

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More about SWE-agent

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Is SWE-agent Worth It?

✅ Why Choose SWE-agent

• Fully open-source under MIT license with an active community and ongoing research — over 17k GitHub stars and frequent releases from the Princeton NLP and Stanford teams
• Model-agnostic architecture supports GPT-4o, Claude (Sonnet/Opus), DeepSeek, and local LLMs via Ollama or any OpenAI-compatible endpoint, avoiding vendor lock-in
• State-of-the-art benchmark performance on SWE-bench (real GitHub issues) and on cybersecurity benchmarks like NYU CTF via the EnIGMA mode
• Sandboxed Docker execution through SWE-ReX with scalable backends for AWS, Modal, and Kubernetes, enabling safe batch processing of many issues in parallel
• Well-documented Agent-Computer Interface (ACI) with custom edit/search commands and linter feedback that meaningfully reduces LLM formatting errors on long tasks
• Dual-purpose utility: same codebase handles software engineering (bug fixes, feature patches) and offensive security tasks (CTF, vulnerability discovery)

⚠️ Consider This

• API costs add up quickly when using frontier models like GPT-4o or Claude Opus — a single SWE-bench run can consume significant tokens per issue
• Initial setup is heavier than consumer tools: requires Docker, API key configuration, and YAML-based agent configs rather than a one-click install
• No hosted UI out of the box — the primary interfaces are CLI, Python API, and an optional web demo, which is less accessible to non-developers
• Python-centric benchmarking and tooling; while the agent can edit any language, its evaluation harness and examples lean heavily on Python repositories
• Autonomy means it can make sweeping edits in a loop — without careful sandboxing and review, runs can waste compute or produce low-quality patches

What Users Say About SWE-agent

👍 What Users Love

✓Fully open-source under MIT license with an active community and ongoing research — over 17k GitHub stars and frequent releases from the Princeton NLP and Stanford teams
✓Model-agnostic architecture supports GPT-4o, Claude (Sonnet/Opus), DeepSeek, and local LLMs via Ollama or any OpenAI-compatible endpoint, avoiding vendor lock-in
✓State-of-the-art benchmark performance on SWE-bench (real GitHub issues) and on cybersecurity benchmarks like NYU CTF via the EnIGMA mode
✓Sandboxed Docker execution through SWE-ReX with scalable backends for AWS, Modal, and Kubernetes, enabling safe batch processing of many issues in parallel
✓Well-documented Agent-Computer Interface (ACI) with custom edit/search commands and linter feedback that meaningfully reduces LLM formatting errors on long tasks
✓Dual-purpose utility: same codebase handles software engineering (bug fixes, feature patches) and offensive security tasks (CTF, vulnerability discovery)

👎 Common Concerns

⚠API costs add up quickly when using frontier models like GPT-4o or Claude Opus — a single SWE-bench run can consume significant tokens per issue
⚠Initial setup is heavier than consumer tools: requires Docker, API key configuration, and YAML-based agent configs rather than a one-click install
⚠No hosted UI out of the box — the primary interfaces are CLI, Python API, and an optional web demo, which is less accessible to non-developers
⚠Python-centric benchmarking and tooling; while the agent can edit any language, its evaluation harness and examples lean heavily on Python repositories
⚠Autonomy means it can make sweeping edits in a loop — without careful sandboxing and review, runs can waste compute or produce low-quality patches

SWE-agent Pricing & Plans 2026

Choose Your Plan

Open Source (self-hosted)

Is SWE-agent Worth It?

✅ Why Choose SWE-agent

⚠️ Consider This

What Users Say About SWE-agent

👍 What Users Love

👎 Common Concerns

Pricing FAQ

What is SWE-agent and who built it?

Which language models can I use with SWE-agent?

Is SWE-agent free to use?

How is SWE-agent different from tools like Devin or Cursor?

Can SWE-agent run safely on my codebase?

Ready to Get Started?

More about SWE-agent

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SWE-agent Pricing & Plans 2026

Choose Your Plan

Open Source (self-hosted)

Is SWE-agent Worth It?

✅ Why Choose SWE-agent

⚠️ Consider This

What Users Say About SWE-agent

👍 What Users Love

👎 Common Concerns

Pricing FAQ

What is SWE-agent and who built it?

Which language models can I use with SWE-agent?

Is SWE-agent free to use?

How is SWE-agent different from tools like Devin or Cursor?

Can SWE-agent run safely on my codebase?

Ready to Get Started?

More about SWE-agent

Compare SWE-agent Pricing with Alternatives

Devin Pricing

Aider Pricing

OpenHands Pricing

GitHub Copilot Pricing

Cursor Pricing