GLM-4.5

GLM-4.5 is Z.AI's mixture-of-experts flagship foundation model, purpose-built for agent-based applications spanning reasoning, coding, and agentic tasks.

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input · usd / 1m tok

$0.60

output · usd / 1m tok

$2.20

context window

128ktokens

modalities · in → out

pricing

base api ratesusd per 1m tokens

input: $0.60
output: $2.20
cache read: $0.11

providers

Z.AI hosts GLM-4.5. Impossibl routes your request intelligently and handles failover automatically when a provider is down.

Z.AI

specifications

takes text in, gives text outzai/glm-4.5

creatorZ.AI
model typeText generation
context window128,000 tokens
maximum outputnot published
input
takes text in, gives text out
outputtext
tool callingnot verified
releasedjul 28, 2025
endpoint/v1/chat/completions

unknown means the public catalog does not establish that fact. a model's documented capabilities can differ from what a particular api supports. see the model documentation for integration details.

try it · your prompt, this model, live

# responses API
import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["IMPOSSIBL_API_KEY"],
    base_url="https://api.impossibl.com/v1",
)

resp = client.responses.create(
    model="zai/glm-4.5",
    input="▌",
)
print(resp.output_text)

edit the prompt, then run

# responses API
import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["IMPOSSIBL_API_KEY"],
    base_url="https://api.impossibl.com/v1",
)

resp = client.responses.create(
    model="zai/glm-4.5",
    input="▌",
)
print(resp.output_text)

edit the prompt, then run

benchmarks

intelligence index

12.8#92 of 108 models on the gateway

omniscience-27.4#67 of 84
gpqa78.2%#60 of 80
humanity’s last exam13.0%#67 of 87

GPQA78.2%
LiveCodeBench73.8%
AIME 202573.7%
AA-LCR52.7%
IFBench44.1%
Tau243.0%
Terminal-Bench Hard22.0%
Humanity’s Last Exam13.0%
CritPt0.0%

Intelligence Index12.77
Omniscience Index-27.38
intelligence index (API)12.8

view source ↗all source data and breakdowns (json) ↗

each configuration is listed separately; these evaluations describe the tested model configuration, and performance and costs can differ on impossibl. unmeasured scores are omitted and api values keep their source units. last checked 2026-10-14. some source data could not be refreshed; retained results may be older.

compare GLM-4.5 with other models

frontier labs and open weights, best-ranked firstusd / 1m tok · in / out

anthropic/claude-opus-5-5$4.00 / $20.00compare →
openai/gpt-6-astra$10.00 / $50.00compare →
meta/muse-wonder$4.00 / $20.00compare →
xiaomi/mimo-v2.6-pro$0.435 / $0.87compare →

impossibl models --all →

frequently asked questions

What is GLM-4.5?

GLM-4.5 is Z.AI's mixture-of-experts flagship foundation model, purpose-built for agent-based applications spanning reasoning, coding, and agentic tasks. Z.AI reports doubled parameter efficiency over prior models and one-click compatibility with the Claude Code framework.

How much does GLM-4.5 cost?

GLM-4.5 costs $0.60 per million input tokens and $2.20 per million output tokens through the Impossibl API. Cache reads cost $0.11 per million tokens. All rates are in USD.

view the pricing table ↑

What is the context length of GLM-4.5?

GLM-4.5 has a 128,000-token context window through the Impossibl API.

What inputs and outputs does GLM-4.5 support?

GLM-4.5 accepts text as input. GLM-4.5 returns text.

How do I use GLM-4.5 through an API?

GLM-4.5 is available through the Impossibl API. Use zai/glm-4.5 as the model identifier with /v1/chat/completions. The quickstart explains how to create an API key and send your first request.

follow the api quickstart →

When was GLM-4.5 released?

Z.AI released GLM-4.5 on July 28, 2025.

Creator release announcement ↗

this page describes GLM-4.5 as listed by the impossibl public api. prices and availability come from that catalog, refreshed here every five minutes. this is an impossibl offering, not a comparison of independent hosting-provider quotes. model descriptions and release dates, where available, use the creator sources linked under the answers above.

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