Models

mai-thinking-1 vs qwen3.8-max-preview

Output tokens cost $8.00 per million on mai-thinking-1 and $1.01 per million on qwen3.8-max-preview. Input tokens cost $2.00 per million on mai-thinking-1 and $0.34 per million on qwen3.8-max-preview. Cached input tokens are billed at $2.00 per million on mai-thinking-1 and $0.03 per million on qwen3.8-max-preview. Context lengths are 256,000 tokens on mai-thinking-1 and 983,616 tokens on qwen3.8-max-preview. Time to first token (TTFT) measured on AIHubMix is 6.7s on mai-thinking-1 and 2.4s on qwen3.8-max-preview. Measured output throughput is 41.7 tok/s on mai-thinking-1 and 48.1 tok/s on qwen3.8-max-preview.

Microsoftmai-thinking-1Qwenqwen3.8-max-preview
Microsoft logo
mai-thinking-1
Microsoft · text → text

MAI-Thinking-1 is Microsoft’s first inference model in the MAI series, built for enterprise-scale workloads. With excellent reasoning, mathematical, and general intelligence capabilities, combined with superior cost-effectiveness, it makes high-throughput, 24/7 AI workloads economically viable.

Input$2.00 /M
Output$8.00 /M
Qwen logo
qwen3.8-max-preview
Qwen · text, image → text

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.

Input$0.34 /M
Output$1.01 /M

Pricing & Specifications

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

mai-thinking-1
qwen3.8-max-preview
Input /M
$2.00
$0.34
Output /M
$8.00
$1.01
Cache read /M
$2.00
$0.03
Context length
256,000
983,616
Max output
256,000
131,072
Time to First Token
6.7 s
2.4 s
Throughput
41.7 tok/s
48.1 tok/s
Modalities
text
textimage
Supported Parameters
thinkingstructured outputs
toolsfunction callingstructured outputsweblong contextthinking
API Formats
chat_completions

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.

mai-thinking-1qwen3.8-max-preview

Tokens / day

-

Requests / day

-

Performance Past 3 Days

Measured on real AIHubMix traffic, hourly buckets. Gaps mean no traffic in that hour.

mai-thinking-1qwen3.8-max-preview

Throughput (tok/s)

-

TTFT (s)

-

Uptime (%)

-

Cost calculator

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

qwen3.8-max-preview
$35.49 /mo
mai-thinking-1
$240 /mo

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

FAQ

Which is cheaper: mai-thinking-1, qwen3.8-max-preview?

qwen3.8-max-preview: $1.01/M output tokens; mai-thinking-1: $8.00/M. Use the cost calculator above to estimate your own workload.

Which responds faster?

qwen3.8-max-preview: 2.4s 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?

mai-thinking-1 accepts 256,000 and qwen3.8-max-preview accepts 983,616 input tokens. Maximum output per request is 256,000 tokens on mai-thinking-1 and 131,072 tokens on qwen3.8-max-preview.

Which one generates tokens faster?

qwen3.8-max-preview at 48.1 tok/s and mai-thinking-1 at 41.7 tok/s, measured as output throughput on AIHubMix — a separate metric from time to first token.

What inputs and capabilities does each model support?

mai-thinking-1 accepts text input and supports thinking and structured outputs; 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 mai-thinking-1 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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