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DeepSeek vs GLM (Z.ai)
A plain-English comparison to help you choose between them.
Two open Chinese frontier families, sold as different products. Pick DeepSeek when you want the broadest cheap capability: a free chat assistant that holds up on reasoning and coding, the lowest-cost frontier-grade API for builders, and open weights for fully private deployment. Pick GLM when the job is specifically coding inside a client you already run: its Coding Plan feeds open-weight models into tools such as Claude Code on a flat subscription from around $18 per month, with a 1M-token context for large codebases.
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.
- Best for
- A free, genuinely capable chat assistant
- The lowest-cost frontier-grade API for builders
- Open weights you can download and self-host
- 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
GLM is Z.ai's coding-first model family, sold less as a new tool than as a change to what powers the one you already have.
- Best for
- Flat-rate coding subscription from around $18 a month
- MIT-licensed GLM-5.2 open weights you can self-host
- A 1M-token context for large-codebase work
- Cost
- Freemium (Free tier + paid plans)
- Ease
- Openness
- Runs privately (self-hostable)
- Data
- GLM's hosted API is served from China, a jurisdiction point to weigh before routing real code or prompts through it. Self-hosting the open weights removes that question entirely: the model runs on infrastructure you control, and nothing leaves it.
Common questions
They sound similar, so what actually differs?
The product shape. DeepSeek is a generalist offer: chat app, volume API and open weights, with coding as one strength among several. GLM is coding-first and unusually clear about it: the plan exists to power the coding client you already use, changed with a configuration edit rather than a migration. Choose by whether you are buying an assistant or restructuring a coding line item.
Which self-hosts better?
Both publish open weights, and both make self-hosting the answer to the jurisdiction question. DeepSeek's frontier-scale weights need serious hardware, with laptops running only the distilled variants. GLM's MIT-licensed weights with a 1M-token context are likewise a serious deployment rather than a laptop experiment. Either way, verify licence terms per release and treat production serving as real infrastructure work.
Is there a shared caveat to both?
Two. Both hosted services are served from China, so organisations with data-residency rules should either self-host or keep regulated material out; the weights split privacy from capability in both cases. And on ambiguous specifications and sustained agentic work, the closed frontier models still win, so the honest pattern for either is a daily driver with a retained frontier seat for the hardest problems.
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Tool facts last checked July 2026