Models

glm-5.2 vs qwen3.8-max

Output tokens cost $1.97 per million on glm-5.2 and $5.07 per million on qwen3.8-max. Input tokens cost $0.56 per million on glm-5.2 and $1.69 per million on qwen3.8-max. Cached input tokens are billed at $0.14 per million on glm-5.2 and $0.17 per million on qwen3.8-max. Discounted rates are shown where a promotion is active. Context windows are 1,000,000 tokens on glm-5.2 and 991,000 tokens on qwen3.8-max. First-token latency measured on AIHubMix is 1.8s on glm-5.2 and 3.5s on qwen3.8-max. Measured output throughput is 46.9 tokens/s on glm-5.2 and 37.0 tokens/s on qwen3.8-max.

Z.AIglm-5.2Qwenqwen3.8-max
up to 50% off·14:00–23:59 UTC
Z.AI
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$1.13$0.56 /M
Output$3.94$1.97 /M
Qwen
qwen3.8-max
Qwen · text → text

Qwen 3.8 Max(qwen3.8-max) is Alibaba Cloud’s flagship native vision-language model, built on a 2.4-trillion-parameter Mixture-of-Experts (MoE) architecture and supporting context windows of up to 1 million tokens. It is well suited for complex multimodal understanding, advanced reasoning, software development, agentic workflows, and long-context processing. At a similar price to Qwen3.7-Max, Qwen3.8-Max delivers significant improvements in reasoning, coding, and agent capabilities, with overall performance comparable to today’s leading models.

Input$1.69 /M
Output$5.07 /M

Specs & Pricing

Prices are per million tokens. Latency and throughput are rolling averages measured on AIHubMix.

glm-5.2
qwen3.8-max
Input price
$1.13$0.5650%
$1.69
Output price
$3.94$1.9750%
$5.07
Cache read
$0.28$0.1450%
$0.17
Context window
1,000,000
991,000
Max output
128,000
128,000
Latency (first token)
1.8 s
3.5 s
Throughput
46.9 TPS
37.0 TPS
Modalities
text
text
Features
thinkingtoolsfunction callingstructured outputs
toolsfunction callingstructured outputsweblong contextthinking
Endpoints
chat_completions · claude_api

Promotional prices show the discounted rate; see each model page for promotion windows.

Usage on AIHubMix last 30 days

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

glm-5.2qwen3.8-max

Tokens / day

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Requests / day

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Live Performance last 3 days

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

glm-5.2qwen3.8-max

Throughput (TPS)

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Latency (s)

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Uptime (%)

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Cost Calculator

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

glm-5.2
$127$63.38 /mo
qwen3.8-max
$177 /mo

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

FAQ

Which is cheaper: glm-5.2, qwen3.8-max?

glm-5.2: $1.97/M output tokens; qwen3.8-max: $5.07/M. Use the cost calculator above to estimate your own workload.

Which responds faster?

glm-5.2: 1.8s first-token latency 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 qwen3.8-max accepts 991,000 input tokens. Maximum output per request is 128,000 tokens on glm-5.2 and 128,000 tokens on qwen3.8-max.

Which one generates tokens faster?

glm-5.2 at 46.9 tokens/s and qwen3.8-max at 37.0 tokens/s, measured as output throughput on AIHubMix — a separate metric from first-token latency.

What inputs and capabilities does each model support?

glm-5.2 accepts text input and supports thinking, tool calling, function calling and structured outputs; qwen3.8-max accepts text input and supports tool calling, function calling, structured outputs, web search, long context and thinking.

Can I call glm-5.2 and qwen3.8-max 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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