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Z.ai (Zhipu) · language model

GLM 4.5: pricing, context and benchmarks

GLM 4.5 is Z.ai (Zhipu)'s model released on July 25, 2025. It costs $0.6 per million input tokens and $2.2 per million output tokens, with a 131.1K-token context window. No independent score has been published for it so far.

Mid-range costOpen weightsReasoningTool calling

What you need to know about GLM 4.5

Z.ai (Zhipu), based in China, put GLM 4.5 online on July 25, 2025. It accepts text as input and produces text. Its context window reaches 131,072 tokens, larger than 29 % of the models in the registry, and it can write up to 98,304 tokens in one go.

It has been available for about 15 months, long enough for its prices and scores to have settled.

GLM 4.5 pricing

On OpenRouter, GLM 4.5 costs $0.6 per million input tokens and $2.2 per million output tokens. Counting three tokens read for every token written, its average price is $1 per million, more expensive than 59 % of paid models (1.3 times the median of $0.76).

A concrete example: a task that sends 2,000 tokens (about 1,500 words) and receives a 500-token answer costs $0.0023. At 1,000 tasks a day, budget $69 a month. The price calculator redoes this with your own volumes.

Tokens already sent and cached are billed at $0.11 per million.

Performance and benchmarks

Epoch AI does not yet publish a capabilities index for GLM 4.5. We therefore show no made-up performance rating: only price, context and features count towards its score.

Features, privacy and local use

  • It supports tool calling, so it can drive an AI agent, call APIs or MCP servers.
  • It can answer in an enforced JSON format (structured outputs).
  • It is a reasoning model: it "thinks" before answering, which helps on hard tasks but uses more output tokens.
  • Its knowledge stops at December 2024.

Its weights are open and downloadable from Hugging Face (mit licence): you can run it on your own machines without sending your data to a third party. With 358,337,791,296 billion parameters, it needs about 200,236,844,623 GB of memory at 4-bit quantisation. Check with the VRAM calculator. It was downloaded 113,824 times on Hugging Face last month.

Other Z.ai (Zhipu) models

Average price per million tokens (3 input for 1 output).
ModelReleasedAvg. priceECI
GLM 5.3 PrimeSep 23, 2026$4.3—
GLM 5.3 FlashXSep 18, 2026$0.59—
GLM 5.3 FlashAug 26, 2026$0.24153.1
GLM 5.3Aug 18, 2026$0.41156
GLM 5.2Jun 16, 2026$1.78151.9
GLM 5.1Apr 7, 2026$2.15149.8
GLM 5V TurboApr 1, 2026$1.9—
GLM 5 TurboMar 15, 2026$1.9—

Verdict

Computed score: 52/100, from public data (performance, price, context, features).

Strengths

  • Open weights: self-hostable, your data stays with you.
  • Agent-ready: tool calling and structured JSON output.

Limitations

  • No independent score published: performance cannot be verified.
  • Text only: reads neither images nor files.

Avoid if…

  • your tasks are mostly simple: a non-reasoning model will cost less;
  • you want to host it on a single consumer computer (≈ 200,236,844,623 GB needed at 4-bit).

Frequently asked questions

How much does GLM 4.5 cost?

$0.6 per million input tokens and $2.2 per million output tokens on OpenRouter (checked October 25, 2026). A task with 2,000 tokens read and 500 written costs $0.0023.

How big is GLM 4.5's context window?

131,072 tokens, roughly 98,000 words, with a maximum of 98,304 output tokens.

Can GLM 4.5 run locally?

Yes, its weights are published under the mit licence. Expect about 200,236,844,623 GB of memory at 4-bit.

Is GLM 4.5 suitable for an AI agent?

Technically yes: it supports tool calling and structured outputs. Then check its cost for your volume.

What are the alternatives to GLM 4.5?

The closest models on price and performance are Aion-2.0, Kimi K2 0711, and Hermes 3 405B Instruct.

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Neutrality. No affiliate links. No vendor pays to be reviewed, rated or ranked. Reviews are directed by François Chollet, neutral and factual, and every data point is dated and sourced. How we score