Pay for ChatGPT if you need one tool that handles files, screenshots, voice, and browsing without surprises. Route bulk work to DeepSeek if cost per call decides whether a feature ships.
DeepSeek publishes its weights, so you can serve the model yourself and stop paying per token — the one argument here that ChatGPT has no answer to.
For one person sending a few hundred messages a month the price gap is noise; pick on capability, not on the invoice.
| Dimension | ChatGPT | DeepSeek |
|---|---|---|
| Free tier | Free account with a daily cap on the main model, limited reasoning-mode calls, and uploads included. The cap is revised often, so read it on the day you sign up. | Web and mobile apps are free with no meaningful daily cap, and the reasoning model is available there. The most generous free tier in this comparison by a distance. |
| Pricing | Free, a consumer Plus tier, a higher Pro tier, plus separately billed API usage at published per-token rates. Check the official pricing page for current numbers. | API pricing is the lowest of the major providers per token, with off-peak discounts historically applied to some models. Consumer apps stay free; check the official pricing page. |
| Long documents | Long context with project persistence: PDFs, spreadsheets, and multi-file code, subject to per-file caps and a total size limit per conversation. | 128K-class context with no project library; uploads are a paste-and-ask flow. Fine for one long file, awkward for a set of related documents you keep coming back to. |
| Coding | Strong across languages, with an agent mode that executes code and iterates, plus the widest set of third-party editor and IDE integrations. | Very strong on algorithmic and math-heavy code, and it shows the reasoning so you can find the wrong step yourself. Weaker on repo-scale refactors; you paste files in by hand. |
| Web/research | Search with citations, plus a deep-research mode that turns many sources into a structured report. The default when the answer has to be sourced. | Search exists but is the weakest part of the product: thinner results and less consistent citations. Do not pick it for research work. |
| Best for | Individuals and teams who want a general assistant with multimodal input and a mature tool ecosystem behind it. | Developers shipping LLM features on a budget, and anyone who wants to self-host for data-control or offline reasons. |
Choose ChatGPT when the input is not text. A photo of a whiteboard, a scanned invoice, a 40-page PDF, a voice note from a meeting — these are the cases where the ecosystem matters more than the token price, because the cheap API expects you to build that pipeline yourself. It is also the easier sell inside a company: admin controls, data-exclusion settings, retention options, and an enterprise agreement your legal team can actually read, with no jurisdiction argument attached. The product surface is broader too — Projects, connectors, a desktop app, a mobile app that is not an afterthought. If you are buying one seat for one person and you need it working on Monday morning, this is the one that will not cost you a week of setup.
Choose DeepSeek when cost per token is the constraint, or when you need the weights in hand. Its API has been the cheapest credible option among frontier-adjacent models, and off-peak discounts have made batch jobs close to free; if you are running classification over a million rows, that difference is the project. Open weights answer the other objection outright: serve it on your own hardware and no data leaves your network, which is often the only way a regulated buyer says yes. The reasoning model is genuinely good at math and step-by-step logic and shows its work, so a wrong turn is visible. The cost is tooling — no first-party IDE agent, thin multimodal support, a smaller integration surface, and more glue code for you to write and maintain. None of that matters if you are calling it from your own backend behind an API key and a retry wrapper.
The usual split is DeepSeek for volume, ChatGPT for the last mile. Prototype against the cheap API, then run a sample of the same prompts through ChatGPT; where quality holds, keep the cheap route, and escalate only the calls that fail. Both expose OpenAI-compatible endpoints, so swapping one for the other is usually a base URL and an API key, which makes that comparison cheap to run. Keep the ChatGPT seat for image, document, and voice work, and put anything that repeats a million times on the other side of the line. Do not run both consumer apps daily — that is how you end up with two half-finished threads and no notes.
DeepSeek's pitch is cost: a free web tier and cheap API for reasoning-heavy work. ChatGPT's is surface area: tools, images, voice, integrations. For maths, logic and code generation on a budget, DeepSeek is the value pick; for everything needing retrieval or multimodality, ChatGPT.
| Free tier | Yes | Yes |
|---|---|---|
| Checked price | Free $0; Go $8/mo; Plus $20/mo; Pro $100 / $200 / $500/mo; Business $20/seat/mo billed annually ($25 monthly, 2 seats minimum) (checked 2026-10-29) | Web and app free; API list price deepseek-flash CNY 1 / 2 per million input tokens (off-peak / peak) and CNY 4 / 8 output; deepseek-v4-pro CNY 4.5 / 9 input and CNY 13.5 / 27 output (checked 2026-10-29) |
| Context window | 1,050,000 tokens on GPT-6 Astra (922K max input, 128K max output); GPT-6.1 Sol inside ChatGPT Work defaults to 500K (checked 2026-10-29) | 1M tokens of context; up to 384K tokens of output (checked 2026-10-29) |
| Where it breaks | Blocked in mainland China without a proxy or VPN | Almost no multimodal support for images or audio |
Prices and limits above were read from each vendor's own page on 2026-10-29; they change without notice, so treat them as the shape of the deal rather than a quote. The practical way to choose: run one real task through both free tiers today — one document you actually care about — and keep whichever needed fewer corrections.
Yes. The weights are published, so you can serve them on your own GPU or a rented one and no data leaves your network. The catch is that you own the operations: quantization, batching, and uptime become your problem, and a small deployment can cost more per month than the API it replaces.
DeepSeek’s API, by a wide margin, on published per-token rates — check the official pricing page for current numbers. For a side project making a few thousand calls a month either bill is small; the consumer subscriptions are where the recurring cost actually sits.
On images, documents, and tool use, yes, clearly. On pure reasoning and math the gap is small, and DeepSeek’s visible chain of thought makes it easier to catch a bad step. Test both on your own prompts before assuming either way.