Feynman vs Opencode: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Feynman and Opencode — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
Feynman
Companion
Open-source AI research agent that reads papers, ranks literature, drafts research and plans experiments from the terminal or a local workbench.
Key features
- Cited Research Briefs: Asking a research question returns a synthesized brief where each claim is tied to the paper or web source it came from, rather than an unsourced summary.
- PaperRank Scoring: Ranks papers on a topic with transparent evidence for citations, methodology, reproducibility and provenance so reading order is a decision you can inspect.
- Paper Access Resolver: Resolves a single DOI, arXiv ID, OpenAlex ID, PMID, PMCID or title against OpenAlex, arXiv/alphaXiv, DOI and Europe PMC, with optional full-text fetching.
- Local Science Workbench: `feynman serve` opens a standalone app with projects, sessions, chat, notebooks, compute, artifact previews and provenance in one place.
- Claim Auditing and Replication: Compares a paper's stated claims against what its code actually does, and generates replication plans with compute targets and gated experiment steps.
- Local and Hosted Models: Works with hosted providers via OAuth or API key and with local runtimes including LM Studio, Ollama, vLLM and a LiteLLM proxy.
- Skills-Only Install: The research skill library can be installed on its own into Claude, Codex or OpenCode projects without the terminal app or bundled runtime.
- Science Artifacts: Reports, data files, spreadsheets, notebooks, LaTeX, chemistry sketches and genomes are browsable together with versions, lineage and execution logs.
Best for
- Deciding What to Read: Ranking a fresh literature pile on a topic by reproducibility and methodology instead of citation count alone.
- Writing a Literature Review: Producing a review that separates where the field agrees from where questions remain open, with citations attached.
- Verifying a Paper's Claims: Auditing whether the results a paper reports are supported by the code and data it released.
- Planning a Replication: Turning a published finding into a concrete replication plan with a compute target and staged experiment steps.
- Running Deep Research Passes: Launching a multi-agent deep dive on a topic that synthesizes findings and verifies them before reporting.
- Keeping Research Local: Running the whole pipeline against a local model so unpublished work and private data never leave the machine.
- Adding Research Skills to a Coding Agent: Installing the skills bundle into an existing Claude or Codex project to get research workflows without a second app.
Opencode
opencode-ai / OpenCode
OpenCode is an open-source, terminal-first coding agent that provides AI-driven coding assistance, debugging, and workflow automation.
Key features
- Terminal TUI Interface: A full-featured terminal user interface and CLI for interacting with AI models, designed for keyboard-driven workflows and Neovim/terminal users.
- Provider-Agnostic Model Support: Configure and use multiple model providers out of the box (OpenAI, Claude/Anthropic, Google/Vertex, OpenCode Zen, OpenRouter or local models) to choose based on cost, capability, or privacy.
- Desktop & Multi-Platform Distribution: Official desktop builds for macOS (Apple Silicon & Intel), Windows, and Linux (.deb/.rpm/AppImage), plus CLI installers and Homebrew tap for easy installation.
- LSP & Editor Integration: Out-of-the-box Language Server Protocol support and integrations to work alongside existing editor and terminal toolchains (tmux, Neovim, shells).
- Non-Interactive & Automation Mode: Support for non-interactive operation and scripting to automate coding tasks, CI workflows, and reproducible agent runs.
- Configuration Persistence & Custom Commands: Persistent model and configuration selections, support for custom commands, named arguments, and file-path completion to tailor workflows.
- Privacy & Local Model Support: Can be configured to run with local models to keep code and data on-premises and avoid vendor lock-in.
- Go-based CLI with Terminal User Interface (TUI) for interactive coding assistance
- Desktop builds: macOS (arm64/x64), Windows x64, Linux (.deb, .rpm, AppImage)
- Provider-agnostic model integrations (OpenCode Zen, OpenAI, Claude, Google, OpenRouter, local models)
- Out-of-the-box LSP support and terminal-focused workflows (tmux, iTerm, Neovim-friendly)
- Configurable via environment variables and configuration files (~/.config/opencode or .opencode, opencode.json, command Markdown files)
- Command/agent definitions stored in config directories (supports placeholders, agent/model overrides)
- Packaged distribution options: Homebrew tap, native release binaries, npm package wrapper (opencode-ai)
- Extensible agent invocation patterns and customizable hotkeys/hotkey conflicts handling
- MIT license, community contributions via GitHub, extensive release history and desktop installers
Best for
- In-terminal code generation and editing: Generate, modify, and apply code changes directly from a TUI/CLI without leaving the terminal.
- Interactive debugging and code fixes: Ask the agent to analyze stack traces, propose fixes, and apply patches inside the project workspace.
- Automated CI/automation tasks: Run OpenCode in non-interactive mode to automate code transformations, linting fixes, or bulk refactors in CI pipelines.
- Provider switching and cost management: Quickly switch between providers (OpenAI, Claude, Vertex, local) to balance speed, capability, and cost for different tasks.
- Local-model development and privacy workflows: Use local models for sensitive codebases to keep data on-premises while leveraging model assistance.
- Desktop and cross-platform usage: Use the GUI-capable desktop builds on macOS/Windows/Linux when terminal environments are not preferred.
- Interactive code generation, completion, and refactoring directly in the terminal
- Code review automation and generation of reviewer-style reports using saved command agents
- Debugging assistance and reproduction guidance integrated into CLI workflows
- Using local or third-party model providers in offline or provider-agnostic setups
- Embedding agent-driven developer tooling into terminal-based developer environments and CI/CD scripts