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glm-5.2:flex

GLM-5.2 is Z-AI's latest flagship model for long-horizon tasks. It marks a substantial leap in long-horizon task capability over its predecessor GLM-5.1 and, for the first time, delivers that capability on a **solid 1M-token context**.

ReasoningTool callingCachingJSON schema
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Specifications

Context window1M tokens
Max output128K tokens
API typechat
AddedAug 17, 2026
Model ID
Data retentionNo
Used for trainingNo
Provider location🇺🇸 US
Privacy policyDeepInfra Privacy Policy→

Benchmarks

Released 2026-06-16
Coding Indexcoding
68.8%

Artificial Analysis Coding Index — a composite of coding evaluations including LiveCodeBench, SciCode and Terminal-Bench.

GPQA Diamondreasoning
89.5%

Graduate-level physics, chemistry & biology questions designed to resist Googling.

Intelligence Indexreasoning
52.6%

Artificial Analysis Intelligence Index — a composite of multiple evaluations measuring overall model capability.

Scores are sourced from official model cards, Artificial Analysis, and public leaderboards. Benchmarks measure specific skills and do not capture every aspect of model quality. Always test on your own workload.

Pricing

Prices updated August 18, 2026
Input / 1M
$0.60
Output / 1M
$1.92
Cache write
N/A
Cache read / 1M
$0.11
Estimated cost
100K input + 10K output$0.0792
1M input + 100K output$0.79
10M input + 1M output$7.92

Requesty charges exactly what the upstream provider charges, no markup, no per-request fees. Prompt caching and smart routing can reduce effective cost by 30-80%.

Quickstart

Drop-in compatible with the OpenAI SDK. Change the base URL, swap in your Requesty API key, and set the model to deepinfra/glm-5.2:flex.

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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="deepinfra/glm-5.2:flex",
    messages=[
        {"role": "user", "content": "Explain quantum computing in one paragraph."},
    ],
)

print(response.choices[0].message.content)

Other DeepInfra Inc. models

glm-5.2
262K ctx$0.75/1M
Coding 69
qwen3.8
262K ctx$2.00/1M
deepseek-ai/DeepSeek-V4-Pro:flex
1.0M ctx$1.04/1M
Coding 69
phi-4:flex
16K ctx$0.06/1M
XiaomiMiMo/MiMo-V2.5-Pro:flex
1.0M ctx$0.80/1M
Coding 60
deepseek-ai/DeepSeek-V4-Flash:flex
1.0M ctx$0.07/1M
Coding 69

Frequently asked questions

How much does glm-5.2:flex cost?
glm-5.2:flex is priced at $0.60 per million input tokens and $1.92 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:flex?
glm-5.2:flex has a context window of 1M tokens, with a maximum output of 128K tokens per response. That's roughly 1,333 words of input you can fit in a single prompt.
How does glm-5.2:flex perform on benchmarks?
glm-5.2:flex scores 99.1% on τ²-Bench, 89.5% on GPQA Diamond, 68.8% on Coding Index. See the full benchmark chart above for results across MMLU Pro, GPQA Diamond, SWE-Bench Verified, HumanEval, MATH, AIME, MMMU, and LiveBench.
What can glm-5.2:flex do?
glm-5.2:flex 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:flex 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 "deepinfra/glm-5.2:flex". The Quickstart above shows Python, JavaScript and cURL snippets.
Can I run glm-5.2:flex through Requesty?
Yes. glm-5.2:flex runs through Requesty's OpenAI-compatible API, served from DeepInfra Inc.. You do not host the model yourself: point base_url at Requesty, set the model to "deepinfra/glm-5.2:flex", and requests are routed to the upstream provider with automatic failover. The same key gives you 600+ other models too.

Access glm-5.2:flex through Requesty

One API key, 600+ models, OpenAI-compatible. No markup on provider prices, automatic failover, and smart caching built-in.

All DeepInfra Inc. models