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GLM 5.3 vs Qwen3.8 Max

Compare GLM 5.3 from Z.AI and Qwen3.8 Max from Qwen 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 5.3QwenQwen3.8 Max
Z.AI logo
GLM 5.3
Z.AI · text → text

GLM-5.3 is Z.AI’s coding and agentic reasoning model, built for complex software engineering, long-running agent tasks, vulnerability analysis, and other demanding workloads. Building on GLM-5.2, it incorporates further post-training improvements to deliver stronger coding performance, better task execution, and greater token efficiency. We currently offer the production-ready GLM-5.3 API with unlimited concurrency, making it well suited for high-throughput workloads, coding agents, and large-scale automation. For a limited time, GLM-5.3 is available at 10% off.

Input$1.1268 /M
Output$3.9438 /M
Cache read$0.2817 /M
Qwen logo
Qwen3.8 Max
Qwen · text, image, video → text

Qwen3.8-Max is Alibaba Cloud Tongyi Qianwen's next-generation flagship large language model, featuring a mixture-of-experts (MoE) architecture with 2.4 trillion parameters. It achieves another breakthrough in encoding depth, enabling it to handle more complex engineering-grade projects and long-term autonomous development; collaborative agent capabilities are significantly enhanced, performing more confidently in multi-tool orchestration and end-to-end delivery; visual understanding is comprehensively improved, with more sensitive and accurate chart reasoning, document parsing, and multimodal perception. Continuing the 1-million-context window, reasoning modes, and a complete tool ecosystem, it continues to evolve at a higher level of intelligence.

Input$1.69 /M
Output$5.07 /M
Cache read$0.169 /M

Pricing & Specifications

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

GLM 5.3
Qwen3.8 Max
Input /M
$1.1268
$1.69
Output /M
$3.9438
$5.07
Cache read /M
$0.2817
$0.169
Context length
1,048,576
1,000,000
Max output
131,072
131,072
Time to First Token
0.8 s
24.5 s
Throughput
48.4 tok/s
24.2 tok/s
Modalities
text
textimagevideo
Supported Parameters
thinkingtoolsfunction callingstructured outputs
toolsfunction callingstructured outputsweblong contextthinking
API Formats
Released
August 14, 2026
August 3, 2026

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-5.3qwen3.8-max

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-5.3qwen3.8-max

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 5.3
$127 /mo
Qwen3.8 Max
$177 /mo

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

FAQ

Which is cheaper: GLM 5.3, Qwen3.8 Max?

GLM 5.3: $3.9438/M output tokens; Qwen3.8 Max: $5.07/M. Use the cost calculator above to estimate your own workload.

Which responds faster?

GLM 5.3: 0.8s 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?

GLM 5.3 accepts 1,048,576 and Qwen3.8 Max accepts 1,000,000 input tokens. Maximum output per request is 131,072 tokens on GLM 5.3 and 131,072 tokens on Qwen3.8 Max.

Which one generates tokens faster?

GLM 5.3 at 48.4 tok/s and Qwen3.8 Max at 24.2 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 5.3 accepts text input and supports thinking, tool calling, function calling and structured outputs; Qwen3.8 Max accepts text, image and video input and supports tool calling, function calling, structured outputs, web search, long context and thinking.

Can I call GLM 5.3 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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