identity

open weights
TensorX Ltd. logo

glm-5.2TensorX Ltd.

in /1M$1.50input tokens
out /1M$4.50output tokens
context1.0M1.0M out
median ttft1.11smeasured
api
chat
hosting
EU
model lab
Z.AI
weights
open
added
June 2026
model id
tensorx/glm-5.2

capabilities 4/8

visionreasoningtoolscachingweb searchjson schemacomputer useimage gen

11 providers serve glm-5.2. This page is one of them. Compare all endpoints

pricing

no markup
input
$1.50
output
$4.50
cache write
-
cache read
$0.38

worked cost

Estimated cost for three request volumes
volumecost
100K in + 10K out$0.20
1M in + 100K out$1.95
10M in + 1M out$19.50

Requesty charges what the upstream provider charges, with no markup and no per-request fee. Prompt caching and smart routing cut the effective cost further on repeated context. Gateway pricing

provider price, passed throughper 1M tokens

measured

through Sep 12
median ttft
1.11s
median tok/s
124.0
blended /1M
$0.66
cache hit
79.5%
answered
99.40%

Weekly aggregates from production traffic routed through Requesty to this endpoint. A metric with no qualifying sample is left out rather than filled in. Compare against the other providers

benchmarks

artificial analysis
Benchmark scores, each normalised to 100
evalScore as a share of 100/100
τ²-Bench99.1
GPQA Diamond89.5
Coding Index68.8
SciCode51.2
Terminal-Bench Hard50.8
Humanity's Last Exam41.1
Intelligence Index38.6
7 evalsmean62.7

Scores from Artificial Analysis and public leaderboards, normalised to 100. Bar colour is the band, not the rank: green 80 and up, blue 55 and up, amber 30 and up. Benchmarks measure narrow skills, so test on your own workload before committing. Released 2026-06-16.

policy

data terms
retention
none
trains on prompts
no
hosted in
EU

Terms are the provider's, not Requesty's: routing a request here puts it under them. TensorX Privacy Policy

Need every request to stay in one jurisdiction? EU hosting routes only through EU-hosted providers.

quickstart

openai compatible
tensorx/glm-5.2

this id pins the tensorx ltd. deployment, with no routing and no failover. the managed id on the canonical page routes across all 11 providers instead

main.py
from openai import OpenAI client = OpenAI(    api_key="YOUR_REQUESTY_API_KEY",    base_url="https://router.requesty.ai/v1",) response = client.chat.completions.create(    model="tensorx/glm-5.2",    messages=[        {"role": "user", "content": "Explain quantum computing in one paragraph."},    ],) print(response.choices[0].message.content)

Change the base url to https://router.requesty.ai/v1, use your Requesty key, set the model to the id above. Existing OpenAI SDK code needs no other edit, and the same key reaches every other model in the catalog. Browse all models

notes

reference

GLM 5.2 is the latest Z.ai flagship model for long horizon coding, reasoning, and agentic workflows. It improves on GLM 5.1 with a 1M token context window, stronger engineering task performance, multiple thinking effort levels, and architectural changes that reduce long context inference cost while improving speculative decoding. Released under the MIT license, it is designed for sustained work over large repositories, complex tool use, and multi step technical tasks.

questions 6

How much does glm-5.2 cost?
glm-5.2 is priced at $1.50 per million input tokens and $4.50 per million output tokens when accessed via Requesty. Prompt caching is supported, which can cut effective input cost by up to 90% on repeated context. Requesty charges exactly what the upstream provider charges, we don't add markup.
What is the context window of glm-5.2?
glm-5.2 has a context window of 1.0M tokens, with a maximum output of 1.0M tokens per response. That is roughly 1,398 words of input you can fit in a single prompt.
How does glm-5.2 perform on benchmarks?
glm-5.2 scores 99.1% on τ²-Bench, 89.5% on GPQA Diamond, 68.8% on Coding Index. The benchmarks pane shows every published result, each normalised to 100.
What can glm-5.2 do?
glm-5.2 supports tool calling, extended reasoning, prompt caching, structured outputs (JSON schema). You can call it through any OpenAI-compatible client by pointing base_url to Requesty.
How do I use glm-5.2 with the OpenAI SDK?
Install the OpenAI SDK, set base_url to "https://router.requesty.ai/v1", set your API key to your Requesty key, and set the model to "tensorx/glm-5.2". The quickstart pane shows Python, JavaScript and cURL snippets.
Can I run glm-5.2 through Requesty?
Yes. glm-5.2 runs through Requesty's OpenAI-compatible API, served from TensorX Ltd.. You do not host the model yourself: point base_url at Requesty, set the model to "tensorx/glm-5.2", and requests are routed to the upstream provider with automatic failover. The same key gives you 600+ other models too.

more from tensorx ltd. 8

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deepseek-v4-pro-08131.0M$1.75
deepseek-v4-flash-07311.0M$0.25
kimi-k31.0M$3.00

call glm-5.2 through one endpoint

One key for this endpoint and 600+ other models. No markup on provider prices, automatic failover when a provider degrades, and prompt caching built in. Methodology

glm-5.2tensorx ltd.in $1.50 /1Mout $4.50 /1Mctx 1.0Mttft 1.11shosted EU11 providers serve this model