Models

GLM 5.2 vs GPT 4.1 Nano

Compare GLM 5.2 from Z.AI and GPT 4.1 Nano from OpenAI on key metrics including benchmarks, price, context length, and other model features. Access both models and hundreds of others through the AIHubMix API.

Z.AIGLM 5.2OpenAIGPT 4.1 Nano
36% off
Z.AI logo
GLM 5.2
Z.AI · text → text

GLM-5.2 is Z.ai’s flagship model for the era of long-horizon tasks. With a truly usable 1M-token context window, it can handle project-level engineering context, execute long-running tasks more reliably, follow engineering standards more consistently, and complete the full development workflow from requirements to multi-platform deployment in a single task.

Input$1.1268$0.7212 /M
Output$3.9438$2.524 /M
Cache read$0.2817$0.1803 /M
OpenAI logo
GPT 4.1 Nano
OpenAI · text, image → text

Ultra-lightweight model with million-token context, optimized for speed and low latency, costing only $0.10 per million input tokens. It is suitable for edge computing and real-time interaction. The automatic caching mechanism offers a 75% cost reduction on cache hits.

Input$0.1 /M
Output$0.4 /M
Cache read$0.025 /M

Pricing & Specifications

Prices are per million tokens. Time to First Token and throughput are rolling averages measured on AIHubMix.

GLM 5.2
GPT 4.1 Nano
Input /M
$1.1268$0.721236%
$0.1
Output /M
$3.9438$2.52436%
$0.4
Cache read /M
$0.2817$0.180336%
$0.025
Context length
1,000,000
1,047,576
Max output
128,000
32,768
Time to First Token
0.6 s
0.8 s
Throughput
35.9 tok/s
72.7 tok/s
Modalities
text
textimage
Supported Parameters
thinkingtoolsfunction callingstructured outputs
toolsfunction callingstructured outputslong context
API Formats
chat_completions · claude_api
Released
June 16, 2026
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Promotional prices show the discounted rate; see each model page for promotion windows.

Activity Past 30 Days

Daily traffic served through AIHubMix — how demand for each model is trending.

glm-5.2gpt-4.1-nano

Tokens / day

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Requests / day

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Performance Past 3 Days

Measured on real AIHubMix traffic, hourly buckets. Gaps mean no traffic in that hour.

glm-5.2gpt-4.1-nano

Throughput (tok/s)

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TTFT (s)

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Uptime (%)

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LMArena Benchmarks

LMArena ratings by capability (Bradley-Terry, commonly called Elo). Higher is better.

Text
glm-5.2gpt-4.1-nano
1240132014001480
Overall
13221472
Coding
13741509
Math
12741476
Hard prompts
13331492
Instruction following
13001465
Multi-turn
13141469
Creative writing
13071451
Longer query
13251482
Chinese
13201517
English
13401480

Source: LMArena (arena.ai) leaderboard, imported by AIHubMix. Models without published ratings are omitted per chart.

Cost calculator

Estimate your monthly bill for the same workload on each model.

GPT 4.1 Nano
$12.00 /mo
GLM 5.2
$127$81.13 /mo

Monthly = daily × 30. Discounted rates applied where a promotion is active.

FAQ

Which is cheaper: GLM 5.2, GPT 4.1 Nano?

GPT 4.1 Nano: $0.4/M output tokens; GLM 5.2: $2.524/M. Use the cost calculator above to estimate your own workload.

How do their coding arena scores compare?

GLM 5.2: 1509; GPT 4.1 Nano: 1374 (LMArena coding leaderboard).

Which responds faster?

GLM 5.2: 0.6s time to first token measured on AIHubMix; see the live performance charts above for how each model behaves across the day.

How large is each context window?

GLM 5.2 accepts 1,000,000 and GPT 4.1 Nano accepts 1,047,576 input tokens. Maximum output per request is 128,000 tokens on GLM 5.2 and 32,768 tokens on GPT 4.1 Nano.

Which one generates tokens faster?

GPT 4.1 Nano at 72.7 tok/s and GLM 5.2 at 35.9 tok/s, measured as output throughput on AIHubMix — a separate metric from time to first token.

What inputs and capabilities does each model support?

GLM 5.2 accepts text input and supports thinking, tool calling, function calling and structured outputs; GPT 4.1 Nano accepts text and image input and supports tool calling, function calling, structured outputs and long context.

Can I call GLM 5.2 and GPT 4.1 Nano with the same API key?

Yes. AIHubMix serves every model on this page behind one OpenAI-compatible endpoint, so switching between them is a one-line change to the model field — no second account, key or SDK.

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