Models

gemini-3.7-flash vs glm-5.2

Output tokens cost $3.75 per million on gemini-3.7-flash and $2.76 per million on glm-5.2. Input tokens cost $0.75 per million on gemini-3.7-flash and $0.79 per million on glm-5.2. Cached input tokens are billed at $0.08 per million on gemini-3.7-flash and $0.20 per million on glm-5.2. Discounted rates are shown where a promotion is active. Context lengths are 1,048,576 tokens on gemini-3.7-flash and 1,000,000 tokens on glm-5.2. Time to first token (TTFT) measured on AIHubMix is 2.2s on gemini-3.7-flash and 1.8s on glm-5.2. Measured output throughput is 53.7 tok/s on gemini-3.7-flash and 49.3 tok/s on glm-5.2.

Googlegemini-3.7-flashZ.AIglm-5.2
Google logo
gemini-3.7-flash
Google · text, image, audio, video → text

Gemini 3.7 Flash is Google’s natively multimodal reasoning model for coding, agents, web development, and knowledge work. It supports a 1M-token context window and adjustable thinking levels. Compared with Gemini 3.6 Flash, it improves coding, tool use, multi-step planning, and instruction following.

Input$0.75 /M
Output$3.75 /M
up to 30% off·00:00–23:59 UTC
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$1.13$0.79 /M
Output$3.94$2.76 /M

Pricing & Specifications

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

gemini-3.7-flash
glm-5.2
Input /M
$0.75
$1.13$0.7930%
Output /M
$3.75
$3.94$2.7630%
Cache read /M
$0.08
$0.28$0.2030%
Context length
1,048,576
1,000,000
Max output
65,536
128,000
Time to First Token
2.2 s
1.8 s
Throughput
53.7 tok/s
49.3 tok/s
Modalities
textimageaudiovideo
text
Supported Parameters
thinkingtoolsfunction callingstructured outputsweblong context
thinkingtoolsfunction callingstructured outputs
API Formats
chat_completions · gemini_api · claude_api
chat_completions · claude_api

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.

gemini-3.7-flashglm-5.2

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.

gemini-3.7-flashglm-5.2

Throughput (tok/s)

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TTFT (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$88.74 /mo
gemini-3.7-flash
$101 /mo

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

FAQ

Which is cheaper: gemini-3.7-flash, glm-5.2?

glm-5.2: $2.76/M output tokens; gemini-3.7-flash: $3.75/M. Use the cost calculator above to estimate your own workload.

Which responds faster?

glm-5.2: 1.8s 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?

gemini-3.7-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-3.7-flash and 128,000 tokens on glm-5.2.

Which one generates tokens faster?

gemini-3.7-flash at 53.7 tok/s and glm-5.2 at 49.3 tok/s, measured as output throughput on AIHubMix — a separate metric from time to first token.

What inputs and capabilities does each model support?

gemini-3.7-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-3.7-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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