Models

gemini-3.6-flash vs glm-5.2

Output tokens cost $7.50 per million on gemini-3.6-flash and $1.97 per million on glm-5.2. Input tokens cost $1.50 per million on gemini-3.6-flash and $0.56 per million on glm-5.2. Cached input tokens are billed at $0.15 per million on gemini-3.6-flash and $0.14 per million on glm-5.2. Discounted rates are shown where a promotion is active. Context windows are 1,048,576 tokens on gemini-3.6-flash and 1,000,000 tokens on glm-5.2. First-token latency measured on AIHubMix is 3.1s on gemini-3.6-flash and 1.8s on glm-5.2. Measured output throughput is 123.8 tokens/s on gemini-3.6-flash and 46.9 tokens/s on glm-5.2.

Googlegemini-3.6-flashZ.AIglm-5.2
Google
gemini-3.6-flash
Google · text, image, audio, video → text

Gemini 3.6 Flash provides sustained frontier-level intelligence optimized for real-world tasks at a higher speed and lower cost. Designed for the agentic era, it excels at code generation, agentic execution, and spatial reasoning. This model is particularly effective for rapid agentic loops involving complex coding cycles and iterations.

Input$1.50 /M
Output$7.50 /M
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

Specs & Pricing

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

gemini-3.6-flash
glm-5.2
Input price
$1.50
$1.13$0.5650%
Output price
$7.50
$3.94$1.9750%
Cache read
$0.15
$0.28$0.1450%
Context window
1,048,576
1,000,000
Max output
65,536
128,000
Latency (first token)
3.1 s
1.8 s
Throughput
123.8 TPS
46.9 TPS
Modalities
textimageaudiovideo
text
Features
thinkingtoolsfunction callingstructured outputsweblong context
thinkingtoolsfunction callingstructured outputs
Endpoints
chat_completions · gemini_api · claude_api
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.

gemini-3.6-flashglm-5.2

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.

gemini-3.6-flashglm-5.2

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
gemini-3.6-flash
$203 /mo

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

FAQ

Which is cheaper: gemini-3.6-flash, glm-5.2?

glm-5.2: $1.97/M output tokens; gemini-3.6-flash: $7.50/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?

gemini-3.6-flash accepts 1,048,576 and glm-5.2 accepts 1,000,000 input tokens. Maximum output per request is 65,536 tokens on gemini-3.6-flash and 128,000 tokens on glm-5.2.

Which one generates tokens faster?

gemini-3.6-flash at 123.8 tokens/s and glm-5.2 at 46.9 tokens/s, measured as output throughput on AIHubMix — a separate metric from first-token latency.

What inputs and capabilities does each model support?

gemini-3.6-flash accepts text, image, audio and video input and supports thinking, tool calling, function calling, structured outputs, web search and long context; glm-5.2 accepts text input and supports thinking, tool calling, function calling and structured outputs.

Can I call gemini-3.6-flash and glm-5.2 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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