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gemini-2.5-pro-exp-03-25 vs Qwen3.8 Max

Compare gemini-2.5-pro-exp-03-25 from Google 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.

Googlegemini-2.5-pro-exp-03-25QwenQwen3.8 Max
Google logo
gemini-2.5-pro-exp-03-25
Google · text, image, audio, video → text

Google’s latest experimental model, highly unstable, for experience only. It boasts strong reasoning and coding capabilities, able to "think" before responding, enhancing performance and accuracy in complex tasks. It supports multimodal inputs (text, audio, images, video) and a 1 million token context window, suitable for advanced programming, math, and science tasks. This means Gemini 2.5 can handle more complex problems in coding, science and math, and support more context-aware agents.

Input$1.25 /M
Output$5 /M
Cache read$0.125 /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.

gemini-2.5-pro-exp-03-25
Qwen3.8 Max
Input /M
$1.25
$1.69
Output /M
$5
$5.07
Cache read /M
$0.125
$0.169
Context length
0
1,000,000
Max output
0
131,072
Time to First Token
8.3 s
12.5 s
Throughput
122.0 tok/s
28.4 tok/s
Modalities
textimageaudiovideo
textimagevideo
Supported Parameters
structured outputstoolslong context
toolsfunction callingstructured outputsweblong contextthinking
API Formats
Released
March 25, 2025
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.

gemini-2.5-pro-exp-03-25qwen3.8-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.

gemini-2.5-pro-exp-03-25qwen3.8-max

Throughput (tok/s)

-

TTFT (s)

-

Uptime (%)

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Cost calculator

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

gemini-2.5-pro-exp-03-25
$150 /mo
Qwen3.8 Max
$177 /mo

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

FAQ

Which is cheaper: gemini-2.5-pro-exp-03-25, Qwen3.8 Max?

gemini-2.5-pro-exp-03-25: $5/M output tokens; Qwen3.8 Max: $5.07/M. Use the cost calculator above to estimate your own workload.

Which responds faster?

gemini-2.5-pro-exp-03-25: 8.3s time to first token measured on AIHubMix; see the live performance charts above for how each model behaves across the day.

Which one generates tokens faster?

gemini-2.5-pro-exp-03-25 at 122.0 tok/s and Qwen3.8 Max at 28.4 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-2.5-pro-exp-03-25 accepts text, image, audio and video input and supports structured outputs, tool calling and long context; 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 gemini-2.5-pro-exp-03-25 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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