gemini-2.5-flash-search integrates Google's official search functionality; the search feature will have an additional separate fee log directly incorporated into the scoring, with detailed logs not displayed; this will be fixed and displayed later; only supports OpenAI-compatible formats for invocation, does not support Gemini SDK; for Gemini's native SDK, please set parameters directly using the official search parameters.
Gemini 2.5 Flash Search vs Qwen3.8 Max Preview
Output tokens cost $2.50 per million on Gemini 2.5 Flash Search and $1.01 per million on Qwen3.8 Max Preview. Input tokens cost $0.30 per million on Gemini 2.5 Flash Search and $0.34 per million on Qwen3.8 Max Preview. Cached input tokens are billed at $0.03 per million on Gemini 2.5 Flash Search and $0.03 per million on Qwen3.8 Max Preview. Context lengths are 1,048,576 tokens on Gemini 2.5 Flash Search and 983,616 tokens on Qwen3.8 Max Preview. Time to first token (TTFT) measured on AIHubMix is 0.7s on Gemini 2.5 Flash Search and 2.4s on Qwen3.8 Max Preview. Measured output throughput is 54.6 tok/s on Gemini 2.5 Flash Search and 48.1 tok/s on Qwen3.8 Max Preview. On the LMArena coding leaderboard Gemini 2.5 Flash Search scores 1424 and Qwen3.8 Max Preview scores 1520.
Qwen 3.8 Max Preview(Qwen3.8-Max-Preview) is the latest-generation foundation model in the Qwen family, packing 2.4T parameters and still evolving. Compared with the previous flagship Qwen 3.7 Max, it delivers major gains in core capabilities like Coding and Cowork (professional productivity), with world-leading performance on complex, long-horizon tasks such as full-stack development, data analysis, and Office workflows. Launch offer: Credits are consumed at just 20% of the standard rate, effectively 5× your usage. Limited time only.
Pricing & Specifications
Prices are per million tokens. Time to First Token and throughput are rolling averages measured on AIHubMix.
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.
Tokens / day
Requests / day
Performance Past 3 Days
Measured on real AIHubMix traffic, hourly buckets. Gaps mean no traffic in that hour.
Throughput (tok/s)
TTFT (s)
Uptime (%)
LMArena Benchmarks
LMArena ratings by capability (Bradley-Terry, commonly called Elo). Higher is better.
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.
Monthly = daily × 30. Discounted rates applied where a promotion is active.
FAQ
Which is cheaper: Gemini 2.5 Flash Search, Qwen3.8 Max Preview?
Qwen3.8 Max Preview: $1.01/M output tokens; Gemini 2.5 Flash Search: $2.50/M. Use the cost calculator above to estimate your own workload.
How do their coding arena scores compare?
Qwen3.8 Max Preview: 1520; Gemini 2.5 Flash Search: 1424 (LMArena coding leaderboard).
Which responds faster?
Gemini 2.5 Flash Search: 0.7s 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 2.5 Flash Search accepts 1,048,576 and Qwen3.8 Max Preview accepts 983,616 input tokens. Maximum output per request is 65,536 tokens on Gemini 2.5 Flash Search and 131,072 tokens on Qwen3.8 Max Preview.
Which one generates tokens faster?
Gemini 2.5 Flash Search at 54.6 tok/s and Qwen3.8 Max Preview at 48.1 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 Flash Search accepts text, image, audio and video input and supports web search, tool calling, function calling, structured outputs and long context; Qwen3.8 Max Preview accepts text and image input and supports tool calling, function calling, structured outputs, web search, long context and thinking.
Can I call Gemini 2.5 Flash Search and Qwen3.8 Max Preview 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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