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DeepSeek vs Qwen
A plain-English comparison to help you choose between them.
An open-weights head-to-head where deployment path, not raw capability, decides. Pick Qwen when you are standing up a new self-hosted deployment: its Apache-2.0 open-weight line is the current default for that job, actively maintained, with a clean path from local prototyping on Ollama to production serving on vLLM. Pick DeepSeek when the hosted lane matters: a free capable chat assistant and the lowest-cost frontier-grade API in the class, with its own open weights as the private fallback. Many stacks simply run both and route by task.
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Side by side
- Summary
DeepSeek is the price disruptor at the frontier: a free, capable chat assistant, an API priced far below the western frontier labs, and open-weight model releases that anyone can download and run. Successive model generations have kept it genuinely competitive on reasoning and coding, not merely cheap.
The open weights are the strategic fact. Organisations that cannot send data to a Chinese-hosted service can still use the models by self-hosting them on their own infrastructure, which splits the privacy question from the capability question.
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For cost-sensitive builders and self-hosters it is a serious default; for regulated data on the hosted service, the jurisdiction question is the one to answer first.
- Best for
- A free, genuinely capable chat assistant
- The lowest-cost frontier-grade API for builders
- Open weights you can download and self-host
- Reasoning and coding strength per pound spent
- Privacy-critical use via self-hosted deployment
- Cost
- Freemium (Free tier + paid plans)
- Ease
- Openness
- Runs privately (self-hostable)
- Data
- The hosted service processes data under Chinese jurisdiction, which rules it out for sensitive work; self-hosting the open weights removes that concern entirely.
- Summary
Qwen is Alibaba's model line, and the part this guide recommends is the open-weight family: the models you download and serve on your own hardware. One clarification matters up front: the closed-weight flagship is API-only while a Max-class model has also been released with open weights under a custom licence, and the open-weight line is what this page describes.
A paid hosted API also exists, running on Alibaba Cloud, and for some organisations that carries a jurisdiction question. Self-hosting the open weights removes it entirely, because data governance stays in your hands rather than with any provider.
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The ceiling is worth naming plainly. On ambiguous specs and sustained multi-agent work the closed frontier models still win, so the working pattern is not Qwen instead of a frontier model but Qwen as the daily driver, with a retained frontier seat for the hardest problems. No tool is best for everyone; this one is best when you want to own the model layer.
- Best for
- The current default for new self-hosted coding work
- Apache-2.0 open weights, free to download and run
- Coding agents on infrastructure you control
- Local prototyping with Ollama, production with vLLM
- An actively maintained open-weight coding line
- Cost
- Freemium (Free tier + paid plans)
- Ease
- Openness
- Runs privately (self-hostable)
- Data
- Qwen's hosted API runs on Alibaba Cloud, which carries a jurisdiction question for some organisations. Self-hosting the open weights removes it: the model runs on your own infrastructure, so data governance stays entirely in your hands.
Pricing
- DeepSeek
Free·Custom
Prices as of August 2026.
- DeepSeek Chat
- Free
- Pay as you go
- Price on applicationusage billed at API rates
- Qwen
Free
Prices as of August 2026.
- Free
- Free
By area
Where each one pulls ahead, area by area.
| Area | DeepSeek | Qwen |
|---|---|---|
| By job | ||
| Software development | the same weights are also reachable on an API cheap enough that no infrastructure has to exist before anybody finds out whether the model is good enough | the line is tuned for agentic coding rather than for general work, so what it is strongest at is the thing a development team actually runs it for |
| By task | ||
| Coding & software development | DeepSeek — when coding AI spend matters, or you want strong open weights you control | Qwen pairs a self-hosted daily driver with a retained frontier seat, so the split is planned rather than discovered |
| Private, local & self-hosted | DeepSeek is here for the weights, and the hardware bill is simply the cost of using them | Qwen serves concurrent users at production throughput with vLLM, which is the step from one person's deployment to a team's |
Common questions
Which weights should a new self-hosted project start with?
Qwen, as the current default for new self-hosted coding and agentic work, with DeepSeek the natural second open-weight option on the same serving stack. That ordering reflects maintenance cadence and tooling fit rather than a capability gulf, and it can shift with releases. Verify licence terms per model release before anything enters a product, on both families.
What about the hosted options?
DeepSeek's hosted lane is the stronger consumer offer: free chat that holds up on reasoning and coding, plus an API that undercuts the western labs at volume. Qwen's paid hosted API runs on Alibaba Cloud, and one clarification matters: its flagship arrives closed-weight and API-only, though a Max-class model has also been released with open weights under a custom licence. Both hosted routes carry a jurisdiction question that self-hosting removes entirely.
Do either replace a frontier subscription?
For the hardest work, not yet, and both families' honest positioning says so: on ambiguous specifications and sustained multi-agent work the closed frontier models still win. The working pattern is a daily driver you own or rent cheaply, with a retained frontier seat for the problems that resist it. What these two change is the cost of everything below that line.
Related comparisons
Read the full guides
Where to start
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Tool facts last checked August 2026