DeepSeek vs Gemini
Which should you use? A side-by-side look at what each one does, who it suits, what it costs, how hard it is to set up, and where each falls short.
Open source · MIT
An open-source agent harness built on a plugin-first design, run from a local Web UI.
AI tool · Freemium
Google's AI assistant with multimodal input (text, images, audio, video) and integration with Google Workspace.
Our verdict
DeepSeek Harness (dsh) is an open-source developer tool for building and extending agent systems through plugins, run locally and still in developer preview with breaking changes expected. Gemini is a general AI assistant from Google that accepts text, images, audio and video and works with Google Workspace apps like Gmail, Docs and Drive. They serve different purposes, so the choice depends on whether you are a developer wanting a customizable tool or a person wanting a ready-to-use assistant.
Pick DeepSeek if you are a developer who wants to experiment with an extensible agent harness and are comfortable running a command-line dev tool.
Pick Gemini if you want a ready-to-use AI assistant for everyday tasks, especially if you already use Google Workspace or need help with images and video.
| Key difference | DeepSeek | Gemini |
|---|---|---|
| Type | Open-source developer tool for building agent harnesses | General AI assistant for everyday questions and tasks |
Written with AI from both products' catalogue entries · updated 2026-10-29
Who each one is for
Choose DeepSeek if you need…
- Developers who want to experiment with an agent harness they can extend with plugins
- Developers already interested in the Cordis plugin model
- People comfortable running a local dev tool from the command line
- Plugin authors who want to publish to the dsh-plugin topic
Choose Gemini if you need…
- Google Workspace users
- Multimodal questions about images and video
- Research with Google Search grounding
Side-by-side
| DeepSeek | Gemini | |
|---|---|---|
| Type | Dev tool | AI assistants · General assistants |
| Price | Free and open source (hosted plans: freemium) | Freemium |
| Licence | MIT | — |
| GitHub stars | 269k | — |
| Setup difficulty | Intermediate | — |
| How you get it | Install with a package manager | — |
| Platforms | Web, iOS, Android, API | Web, iOS, Android, API |
| Works with | — | Google Workspace, Chrome |
| Main language | TypeScript | — |
| Last code update | 7 days ago | — |
| Hands-on tested by us | — | Not yet |
| Last checked | — | 2026-10-29 |
What each one is
DeepSeek
DeepSeek Harness (dsh) is an open-source agent harness from DeepSeek AI, built so that nearly every part is a plugin. It runs on Cordis, a plugin framework the README links to, and can be started as a local Web UI. The README describes it as being in developer preview, so the interface and APIs may change.
Gemini
Google's AI assistant with multimodal input (text, images, audio, video) and integration with Google Workspace. Best fit if you live in Google's ecosystem, and strong with video and image input. Feature availability varies by country, account type and plan.
Best for
DeepSeek
- Developers who want to experiment with an agent harness they can extend with plugins
- Developers already interested in the Cordis plugin model
- People comfortable running a local dev tool from the command line
- Plugin authors who want to publish to the dsh-plugin topic
Gemini
- Google Workspace users
- Multimodal questions about images and video
- Research with Google Search grounding
Strengths
DeepSeek
- Built on a stated everything-is-a-plugin architecture
- Can be started quickly with a single npx command, per the README
- Documentation, a Discord community and GitHub Discussions are linked from the README
Gemini
- Multimodal input
- Deep research reports
- Gmail, Docs and Drive integration
- Custom Gems
Not ideal for
DeepSeek
- Users who need a stable production system, since the README warns of compatibility-breaking changes during developer preview
- Anyone who has not read the SAFETY.md notice, which the README asks users to review before running it
- Non-technical users looking for a finished consumer app; the README assumes Node.js or a repository checkout
Gemini
—
Trade-offs
DeepSeek
- The README explicitly says it is in developer preview with breaking changes expected
- The README is truncated and gives limited detail on features and models supported
- Requires understanding of Node.js or pnpm and a local dev workflow
Gemini
—
Getting started
DeepSeek
Run from npm
npx @deepseek-ai/dsh webClone the repository
git clone https://github.com/deepseek-ai/deepseek-harness.gitFrequently asked questions
Should I use DeepSeek or Gemini?
DeepSeek Harness (dsh) is an open-source developer tool for building and extending agent systems through plugins, run locally and still in developer preview with breaking changes expected. Gemini is a general AI assistant from Google that accepts text, images, audio and video and works with Google Workspace apps like Gmail, Docs and Drive. They serve different purposes, so the choice depends on whether you are a developer wanting a customizable tool or a person wanting a ready-to-use assistant. Pick DeepSeek if you are a developer who wants to experiment with an extensible agent harness and are comfortable running a command-line dev tool. Pick Gemini if you want a ready-to-use AI assistant for everyday tasks, especially if you already use Google Workspace or need help with images and video.
What is the difference between DeepSeek and Gemini?
DeepSeek: An open-source agent harness built on a plugin-first design, run from a local Web UI. Gemini: Google's AI assistant with multimodal input (text, images, audio, video) and integration with Google Workspace. DeepSeek suits developers who want to experiment with an agent harness they can extend with plugins, while Gemini suits google workspace users.
Are DeepSeek and Gemini free?
DeepSeek: Free and open source (hosted plans: freemium). Gemini: Freemium.
What are other alternatives to DeepSeek and Gemini?
Other options people compare them with include LangChain, CrewAI, Our Free Model, Claude, ChatGPT.
Keep comparing
Built from our catalogue entries for both products: open-source details come from each project's README (AI-assisted, refreshed weekly) and GitHub data; AI-tool details are editorial. Spotted something wrong? Let us know from either product's page.