Z.ai (GLM)
Z.ai (GLM) is GLM models with an unusually cheap flat-rate coding plan. We compare it in LLM APIs. It is 3rd of 9 on $/M output ($2.2 /M tok). The trade-off is being marked No on Zero retention, where Amazon Bedrock records Yes.
What is Z.ai (GLM)?
- Z.ai (GLM), GLM models with an unusually cheap flat-rate coding plan.
- - Zhipu's GLM series, sold internationally as Z.ai, targets coding and agentic workloads
- Flagship weights released under MIT
- Most disruptive product is the flat-rate coding subscription, not the token price
- Widely mirrored by routers, how most Western teams reach it.
- Built by Zhipu AI.
- Founded 2019.
- Open source under MIT.
- We track it in 1 comparison, LLM APIs.
- Every claim below is a cell in a table you can open and check rather than an impression.
- Across those rosters it sits against 17 other tools, and what follows is where it visibly separates from them.
Where it wins.
- $/M output, $2.2 /M tok, 3rd of 9.
- $/M input, $0.6 /M tok, 3rd of 9.
- Each of those is ranked against the whole roster on its category page, not against a hand-picked subset.
- A first place here means first of everything we list.
Where it gives ground.
- Zero retention, No. Amazon Bedrock
records Yes. - Context window, 200,000 tokens, 11th of 12. Anthropic
records 1,000,000 tokens. - Audio in/out, No. OpenAI
records Partial.
- None of these disqualify it on their own.
- They are the fields to check against your own requirements before you commit, because they are the ones where a competitor genuinely does better.
- Provenance. 20 of 27 tracked fields carry a value for Z.ai (GLM), and 1 of those cite a document you can open.
- Last verified 2026-01-15.
- Every figure keeps its own provenance, measured by us, claimed by the vendor, inferred, or community-reported, and we would rather print a dash than a guess.
- Its nearest neighbour in our data is Qwen
. - Z.ai (GLM) is ahead on Open weights (Yes against Partial) and $/M input ($0.6 /M tok against $2.5 /M tok).
- Qwen takes Context window (1,000,000 tokens against 200,000 tokens) and MCP support (Partial against No).
- That pattern repeats across the rest of the roster, see Z.ai (GLM) alternatives for the other rivals, each compared the same way.
At a glance
- Company
- Zhipu AI
- Founded
- 2019
- Licence
- MIT (open source)
- Fields we track
- 20 of 27
- Last verified
- 2026-01-15
Z.ai (GLM) in LLM APIs
Ranked against 18 tools across 27 sourced fields. Open the full LLM APIs table.The flat-rate coding plan is genuinely disruptive, turning all-day agent use into a fixed cost; quality trails only on hard reasoning.
Where it lands in this roster
- $/M output
- $2.2/M tok3rd of 9 Inferredverified 2026-01-15
- $/M input
- $0.6/M tok3rd of 9 Inferredverified 2026-01-15
- Zero retention
- No10th of 12 Inferredverified 2026-01-15
- Context window
- 200,000tokens11th of 12 Inferredverified 2026-01-15
- Tool use
- Yes1st of 18 Community-reportedverified 2026-01-15
- Pinnable versions
- Yes1st of 18 Inferredverified 2026-01-15
- OpenAI-compat API
- Yes1st of 18 Inferredverified 2026-01-15
- MCP support
- No6th of 18 Inferredverified 2026-01-15
When to use Z.ai (GLM)
Z.ai (GLM) is the right call in these situations, each one drawn from a field we actually record.
- Driving a coding agent all day on a predictable monthly cost.
- Cheap high-volume code completion and refactoring.
- Self-hosting an MIT-licensed coding model.
- $/M output is your binding constraint. Z.ai (GLM) records $2.2 /M tok, 3rd of 9 in the LLM APIs roster. We define that field as pay-as-you-go list price per million output tokens for the named flagship model, including reasoning or thinking tokens where those are billed as output.
- $/M input is your binding constraint. Z.ai (GLM) records $0.6 /M tok, 3rd of 9 in the LLM APIs roster. We define that field as pay-as-you-go list price per million input tokens for the named flagship model, uncached, at the standard context tier.
When not to use Z.ai (GLM)
Reach for something else when any of the following is a requirement rather than a nice-to-have.
- Zero retention. Z.ai (GLM) records No on the LLM APIs table. Amazon Bedrock records Yes on the same field. If that is a hard requirement rather than a preference, start elsewhere.
- Context window. Z.ai (GLM) records 200,000 tokens, 11th of 12 in the LLM APIs roster. Anthropic records 1,000,000 tokens on the same field. If that is a hard requirement rather than a preference, start elsewhere.
- Audio in/out. Z.ai (GLM) records No on the LLM APIs table. OpenAI records Partial on the same field. If that is a hard requirement rather than a preference, start elsewhere.
- We publish this block because a comparison that only lists what a tool is good at is marketing.
- Every figure above sits on the same page as its source, and the field definitions are on the category tables if you want to check how we measured them.
Options compared alongside Z.ai (GLM)
Everything below shares at least one comparison category with Z.ai (GLM), ordered by how much overlap there is. For the reasoning on each, which fields it wins, which it loses, see Z.ai (GLM) alternatives.
Sources and gaps
What we don't know.
- 7 of the 27 fields we track for Z.ai (GLM) are still blank: Max output, TTFT p50, Output tok/s, $/M cache read, Batch discount, Cache TTL and Notice period.
- Those render as dashes rather than as zeroes or assumptions, because an empty cell and a bad cell are not the same thing and only one of them is honest.
- If you know any of these figures and can point at a document, tell us.
- huggingface.co/zai-org/GLM-4.6Open weights · Vendor-claimed · verified 2026-01-15