DeepSeek Alternatives

ChatGPT is the broadest replacement for the DeepSeek app. DeepSeek gives you a strong model in a chat window. ChatGPT gives you that plus search on every plan, file analysis, image generation, deep research and agents, in the same conversation. If you went to DeepSeek for its reasoning, Plus opens OpenAI's advanced reasoning models; if you went for the price, the Free plan already includes search, and Go costs $8 a month in the US.

ChatGPT has six individual plans: Free, Go at $8, Plus at $20, and three Pro tiers at $100, $200 and $500 a month that differ by usage, with the fastest responses kept for eligible tiers. Go may include ads; Plus is the plan most former DeepSeek users compare against. The trade-off is cost per use: nothing in ChatGPT's consumer plans matches DeepSeek's API rates, and the weights are not yours to download. Our ChatGPT review covers each plan, and ChatGPT alternatives helps if you hesitate; to train a team on it, see our ChatGPT training ranking.

Claude, from Anthropic, is the pick for people who used DeepSeek for its reasoning on hard problems, long documents and code. It reads large files and many sources at once and writes structured, readable output, and Claude Code, included from Pro, turns that into an agent that works in your terminal and repository. For a developer who was calling DeepSeek's model through a coding tool, that is a close like-for-like move among the closed labs.

Pro costs $17 a month with annual billing ($200 billed up front) or $20 billed monthly. Max costs $100 a month for five times Pro's usage, and Ultra $200 for ten times Pro's weekly usage, with $100 and $200 of monthly API credits. Every plan has limits: most accounts reset on a rolling five-hour window, and paid plans add a weekly limit, which heavy users hit before anything else. For a team, the Standard seat is $20 a month billed annually or $25 monthly, and Enterprise is $20 per seat plus usage at API rates, billed annually with a 20-seat minimum. Our Claude review details each plan, and Claude alternatives lists other options; our Claude Code review covers the coding agent alone.

Gemini is the alternative for people who want DeepSeek's long context and low entry price without leaving a big Western provider. The free plan lists Deep Research among its features, with the Flash-Lite model and 15 GB of storage across Gmail, Drive and Photos. Google AI Plus costs $4.99 a month for double the free plan's usage limits, the cheapest paid entry among the closed labs on this page.

Google AI Pro, at $19.99 a month, opens the Pro model and a one million token context window, the same order of size as DeepSeek's 1M context, so a folder of PDFs or a long codebase fits in one question. Ultra starts at $99.99 a month for five times AI Pro's limits, and a $199.99 tier gives twenty times. The bundle is the other argument: storage and Gemini inside Gmail and Docs come with the plan, so if you already pay Google for space, the AI part may cost little more. The weak points are support, reached through Google's general channels, and a free tier on the lightest model. For a company, Gemini Enterprise's Business edition starts at $21 per seat per month. Our Gemini review covers the plans, and Gemini alternatives compares its rivals; to call it from an automation, see the Google Gemini chat model node for n8n.

Qwen, from Alibaba Cloud, is the most natural swap if what you liked about DeepSeek was the combination of open weights and cheap tokens. Alibaba states that all its open-weight Qwen3 models are licensed under Apache 2.0, a standard open source license that lets you use, modify and ship them commercially. You can run them locally with llama.cpp or Ollama, or call them on Alibaba Cloud Model Studio, and there is a free Qwen Chat for everyday questions. To call Qwen from an automation, see the Qwen Cloud chat model node for n8n.

On the API, qwen-flash costs $0.05 per million input tokens and $0.40 per million output tokens for requests up to 256K tokens, in the International deployment; on short requests, qwen3.7-flash is cheaper still, at $0.03 in and $0.13 out up to 32K tokens per request, then $0.10 and $0.40 up to 256K. qwen-plus-latest costs $0.40 in and $1.20 out on the same tier, non-thinking. Two billing details matter. Pricing is tiered by the size of each request, and all tokens in a request are billed at the tier it falls into, so one 300K-token prompt costs more per token than three small ones. And the free quota exists only in the Singapore region; other regions have none. The limit is the same as DeepSeek's on one point: Qwen is a Chinese lab too, so self-hosting is what changes the data question, not the brand.

Mistral is the alternative for people who leave DeepSeek over where their data goes but still want open-weight models and moderate prices. The Paris-based lab sells a consumer app, now branded Vibe (also known as Le Chat), and an API on its own infrastructure, with in-region inference and the option to run on premises or in your own cloud. Its open-weight models, such as Mistral 7B, are under Apache 2.0 for research and individual use, but Mistral says commercial deployments require a Mistral license with separate terms, so budget for it before you ship a product on them.

The Free plan gives access on web and mobile with limited messages and web searches, basic image generation and more than 100 connectors. Pro costs $14.99 a month excluding taxes, with more messages and searches, all-day coding in the CLI, IDE or web, chat and email support, and $15 a month of API credits; verified students pay $5.99. Team costs $24.99 per user a month, with up to 30 GB of storage per user, domain verification and data export. On the API, Mistral Large costs $0.50 per million input tokens and $1.50 per million output tokens, between DeepSeek's flash and v4-pro peak rates, and batch processing cuts the price by 50%. The limit is raw capability on the hardest reasoning tasks, where the US labs still lead. To get a team started, see our Mistral training ranking, and to call it from a workflow, the Mistral Cloud chat model node for n8n.

Grok, from SpaceX Super Intelligence (formerly xAI), is the alternative for people whose main complaint about DeepSeek is refusals. xAI says it built Grok to answer almost anything, and it searches both the web and posts on X, so a question about a launch, a market move or a breaking story comes back with what people are saying now.

Grok's plans are Free at $0, Plus at $8 a month, Premium at $30, Super at $100 and Ultra at $200, with team plans on Premium at $30 per seat, Super at $100 and Ultra at $200. Premium gives four times Plus's usage, and the plans bundle X features such as posting and analytics, so part of the price pays for things that have nothing to do with the model. Prices exclude taxes such as VAT, and you must cancel at least 24 hours before renewal to avoid another charge. Paid plans include access to the Grok API, but API calls are billed separately at standard model rates and do not draw from the plan's usage. To train a team on it, see our Grok training ranking. The weak points are support and sourcing: posts on X are fast but unverified, so treat a real-time answer as a lead to check. Our Grok review details each tier, and Grok alternatives lists other options.

Kimi, from Moonshot AI, is the alternative developers reach for when they used DeepSeek's API inside coding agents and want a second model that handles tools and long tasks. Its API platform bills model inference pay-as-you-go, with no subscription plan, separate from the Kimi membership and Kimi Code products, so you pay only for the tokens you send and receive.

What you pay depends on when you sign up. A new account gets the K3 series, with a 1M-token context: the flagship kimi-k3.1-pro costs $2.00 per million input tokens and $10.00 per million output tokens, with cached input at $0.20, and kimi-k3 costs $3.00 in and $15.00 out; both support batch inference at 60% of the standard price. The cheaper K2 models, kimi-k2.6 at $0.95 in and $4.00 out and the kimi-k2.7-code coding model, are closed to newly registered users and set to retire by the end of 2026, so do not budget a switch on them. On the K3 series, cache writes are billed separately by how long the cache lives (five minutes or one hour), which changes the math for agents that reuse a long system prompt. The limit: Kimi is another Chinese lab, so it does not solve a data-residency question, and its output prices sit above DeepSeek's even off-peak. To wire it into a workflow, our Moonshot Kimi chat model node for n8n shows the setup.