Models

GLM 5.2 vs Qwen3.5 27B

Output tokens cost $3.94 per million on GLM 5.2 and $0.68 per million on Qwen3.5 27B. Input tokens cost $1.13 per million on GLM 5.2 and $0.08 per million on Qwen3.5 27B. Cached input tokens are billed at $0.28 per million on GLM 5.2 and $0.08 per million on Qwen3.5 27B. Context lengths are 1,000,000 tokens on GLM 5.2 and 991,000 tokens on Qwen3.5 27B. Time to first token (TTFT) measured on AIHubMix is 1.1s on GLM 5.2 and 1.3s on Qwen3.5 27B. Measured output throughput is 37.0 tok/s on GLM 5.2 and 70.6 tok/s on Qwen3.5 27B. On the LMArena coding leaderboard GLM 5.2 scores 1505 and Qwen3.5 27B scores 1450.

Z.AIGLM 5.2QwenQwen3.5 27B
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 /M
Output$3.94 /M
Qwen logo
Qwen3.5 27B
Qwen · text, image, video → text

The Qwen 3.5 native vision-language Plus model is built on a hybrid architecture that integrates linear attention mechanisms with sparse mixture-of-experts models, achieving higher inference efficiency. In multiple task evaluations, the 3.5 series has demonstrated outstanding performance comparable to current leading frontier models, with leapfrog improvements over the 3 series in both pure-text and multimodal capabilities. This model version is functionally equivalent to the snapshot model qwen3.5-plus-2026-02-15.

Input$0.08 /M
Output$0.68 /M

Pricing & Specifications

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

GLM 5.2
Qwen3.5 27B
Input /M
$1.13
$0.08
Output /M
$3.94
$0.68
Cache read /M
$0.28
$0.08
Context length
1,000,000
991,000
Max output
128,000
64,000
Time to First Token
1.1 s
1.3 s
Throughput
37.0 tok/s
70.6 tok/s
Modalities
text
textimagevideo
Supported Parameters
thinkingtoolsfunction callingstructured outputs
toolsfunction callingstructured outputsweblong contextthinking
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-5.2qwen3.5-27b

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-5.2qwen3.5-27b

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-5.2qwen3.5-27b
1340140014601520
Overall
14081470
Coding
14501505
Math
14281475
Hard prompts
14261488
Instruction following
14001462
Multi-turn
14141470
Creative writing
13571450
Longer query
14221479
Chinese
14701516
English
14251477
WebDev Arena
glm-5.2qwen3.5-27b
13201400148015601640
Overall
13571582
React
13451594
HTML
13931537
Gaming
13451617
Simulations
13351606
Data analytics
13561542

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.

Qwen3.5 27B
$15.23 /mo
GLM 5.2
$127 /mo

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

FAQ

Which is cheaper: GLM 5.2, Qwen3.5 27B?

Qwen3.5 27B: $0.68/M output tokens; GLM 5.2: $3.94/M. Use the cost calculator above to estimate your own workload.

How do their coding arena scores compare?

GLM 5.2: 1505; Qwen3.5 27B: 1450 (LMArena coding leaderboard).

Which responds faster?

GLM 5.2: 1.1s 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 Qwen3.5 27B accepts 991,000 input tokens. Maximum output per request is 128,000 tokens on GLM 5.2 and 64,000 tokens on Qwen3.5 27B.

Which one generates tokens faster?

Qwen3.5 27B at 70.6 tok/s and GLM 5.2 at 37.0 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; Qwen3.5 27B accepts text, image and video input and supports tool calling, function calling, structured outputs, web search, long context and thinking.

Can I call GLM 5.2 and Qwen3.5 27B 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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