Claude vs Gemini vs DeepSeek: Choosing an AI Assistant
A practical comparison of Claude, Gemini, and DeepSeek on real work tasks, data handling, and access, with guidance on keeping your work portable when different models suit different jobs.
Updated 5 min read
Claude, Gemini, and DeepSeek are three capable AI assistants that approach the same work differently. Claude and Gemini are US-based commercial products with established consumer apps and developer APIs. DeepSeek is a Chinese open-weight model that can be run through its own website, hosted via third-party providers, or self-hosted on your own infrastructure. Choosing between them depends on the task, the data involved, and who controls the infrastructure. A tool like fenbs keeps your project work outside any single AI app, so the choice of model does not cost you the project history.
For a comparison of just Claude and Gemini, see Claude vs. Gemini. For a version that adds OpenAI, see Claude vs. Gemini vs. OpenAI. For coding tools specifically, see Claude vs. Gemini for coding.
| Claude | Gemini | DeepSeek | |
|---|---|---|---|
| Made by | Anthropic (US) | Google (US) | DeepSeek (China) |
| Access | claude.ai; Anthropic API | gemini.google.com; Google AI API | deepseek.com; API; self-hostable open weights |
| Data handling | US-based; see Anthropic privacy policy | US-based; see Google privacy policy | Chinese jurisdiction on hosted service; open weights allow self-hosting |
| Context window | Up to 200 K tokens on current models | Up to 1 M tokens on Gemini 1.5 Pro and later | Depends on model version; check deepseek.com |
| Coding tasks | Strong; Claude Code available | Capable; Gemini CLI available | Strong on coding benchmarks; popular for self-hosted coding use |
| Multimodal input | Text and images | Text, images, audio, video | Text and code focus; check current docs |
| Pricing | Free tier + paid plans; see anthropic.com | Free tier + paid plans; see google.com/gemini | Free tier + API pricing; see deepseek.com |
Where each assistant is strongest
Claude performs well on long, structured text tasks, complex reasoning, and instruction-following. It is a natural fit for legal and analytical work, detailed writing, and code review that needs careful explanation. Claude Code is available as a coding assistant for developers who want it integrated into a terminal workflow.
Gemini's native multimodal support makes it the first choice when a task involves images, audio, or video alongside text. Its tight integration with Google Workspace is useful for people who live in Docs, Sheets, or Gmail. Gemini CLI brings the same model to command-line workflows. The context window on Gemini 1.5 Pro reaches one million tokens, which matters for very large document sets.
DeepSeek's open-weight models (released under permissive licenses) perform well on coding benchmarks and have become popular with developers who want a capable model they can run on their own hardware, avoiding sending code to a commercial cloud provider. DeepSeek R1 and later versions also do well on reasoning tasks.
Data handling: where your prompts go
Claude and Gemini are both US-based services. Your prompts are processed on US infrastructure and governed by US privacy law. Both Anthropic and Google have enterprise options with additional data-handling commitments; read their current policies before sending sensitive material.
DeepSeek's hosted service (deepseek.com) is based in China. Prompts sent to that service are processed on Chinese infrastructure and subject to Chinese jurisdiction. For many personal or low-sensitivity tasks, that is a straightforward trade-off. For professional work involving client data, proprietary code, or regulated information, check your organization's policies before using the hosted service.
DeepSeek's open weights change the calculation. If you self-host the model on your own servers, you control the infrastructure and no data leaves your environment. That makes it an option for organizations that need a capable model with strict data-residency requirements, provided they have the engineering capacity to run and maintain it.
Picking one for common tasks
Writing, analysis, and research: All three handle standard writing and research tasks. Claude's instruction-following is a strength for structured content. Gemini's Google Search grounding (available in some products) is useful for research-heavy work. DeepSeek is competitive but less differentiated for pure writing tasks.
Coding: DeepSeek has attracted developers looking for a self-hostable option or a lower-cost API for code generation. Claude Code and Gemini CLI are the other two's main coding tools, each with terminal integration. The right choice depends on whether you need self-hosting, a specific IDE integration, or a particular coding assistant feature. Compare Gemini CLI vs Claude Code for the tool comparison.
Long documents: Gemini's million-token context window is the largest of the three. Claude's 200,000-token window is large enough for most documents. DeepSeek's context limit varies by model; check the current documentation.
Keep the project when you switch models
When a different assistant suits a different task, fenbs keeps the work in one place. Connect Claude Code or Gemini CLI over MCP, and either reads the same projects, decisions, and Where we left off. Try DeepSeek for a coding task and return to Claude for document review without rebuilding the project brief each time.
Create a free accountFree for one person · No credit card · Works with Claude, ChatGPT, Cursor and more
Using more than one assistant on the same project
It is common to use Claude for writing, DeepSeek for code, and Gemini for research in the same week on the same project. The friction is not switching the tool — it is carrying the context. Every new session starts blank unless you give it what it needs.
A shared record outside any model keeps that friction low. Write the goal, the approved decisions, and where things stand. The next assistant — whatever model it uses — starts from that record rather than from a summary you reconstruct from memory.
How to do this with fenbs
- Create a free account and add a project for the work.
- Write the project goal, key decisions, and current tasks. Note which model you used for each task and why.
- Record decisions about which model to use for which kind of work in Decisions and rules, so the choice is consistent and easy to revisit.
- Connect Claude or a Gemini-powered tool over MCP from Integrations. DeepSeek products are not currently listed as a direct integration; connect whichever assistant supports MCP and is available to you.
- Before switching models mid-project, save progress on the current task so the next session has a clear starting point.
When to not switch models
Switching models adds overhead: new interface, possibly different prompt conventions, and context to re-establish. If your current model handles the task adequately, the case for switching is usually cost or a specific missing feature, not a general improvement. Test on a representative sample before migrating a whole workflow.