Models

gpt-5.5 vs qwen3.8-max-preview

Output tokens cost $30.00 per million on gpt-5.5 and $1.01 per million on qwen3.8-max-preview. Input tokens cost $5.00 per million on gpt-5.5 and $0.34 per million on qwen3.8-max-preview. Cached input tokens are billed at $0.50 per million on gpt-5.5 and $0.03 per million on qwen3.8-max-preview. Context windows are 1,050,000 tokens on gpt-5.5 and 983,616 tokens on qwen3.8-max-preview. First-token latency measured on AIHubMix is 5.4s on gpt-5.5 and 2.4s on qwen3.8-max-preview. Measured output throughput is 49.1 tokens/s on gpt-5.5 and 48.1 tokens/s on qwen3.8-max-preview.

OpenAIgpt-5.5Qwenqwen3.8-max-preview
OpenAI
gpt-5.5
OpenAI · text, image → text

GPT-5.5 raises the baseline for complex production workflows. It’s a strong fit for coding use cases, tool-heavy agents, grounded assistants, long-context retrieval, product-spec-to-plan workflows, and customer-facing workflows where execution quality and response polish are critical.

Input$5.00 /M
Output$30.00 /M
Qwen
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

Specs & Pricing

Prices are per million tokens. Latency and throughput are rolling averages measured on AIHubMix.

gpt-5.5
qwen3.8-max-preview
Input price
$5.00
$0.34
Output price
$30.00
$1.01
Cache read
$0.50
$0.03
Context window
1,050,000
983,616
Max output
128,000
131,072
Latency (first token)
5.4 s
2.4 s
Throughput
49.1 TPS
48.1 TPS
Modalities
textimage
textimage
Features
thinkingfunction callingstructured outputswebtools
toolsfunction callingstructured outputsweblong contextthinking
Endpoints
chat_completions · claude_api · responses

Promotional prices show the discounted rate; see each model page for promotion windows.

Usage on AIHubMix last 30 days

Daily traffic served through AIHubMix — how demand for each model is trending.

gpt-5.5qwen3.8-max-preview

Tokens / day

-

Requests / day

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Live Performance last 3 days

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

gpt-5.5qwen3.8-max-preview

Throughput (TPS)

-

Latency (s)

-

Uptime (%)

-

Cost Calculator

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

qwen3.8-max-preview
$35.49 /mo
gpt-5.5
$750 /mo

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

FAQ

Which is cheaper: gpt-5.5, qwen3.8-max-preview?

qwen3.8-max-preview: $1.01/M output tokens; gpt-5.5: $30.00/M. Use the cost calculator above to estimate your own workload.

Which responds faster?

qwen3.8-max-preview: 2.4s first-token latency measured on AIHubMix; see the live performance charts above for how each model behaves across the day.

How large is each context window?

gpt-5.5 accepts 1,050,000 and qwen3.8-max-preview accepts 983,616 input tokens. Maximum output per request is 128,000 tokens on gpt-5.5 and 131,072 tokens on qwen3.8-max-preview.

Which one generates tokens faster?

gpt-5.5 at 49.1 tokens/s and qwen3.8-max-preview at 48.1 tokens/s, measured as output throughput on AIHubMix — a separate metric from first-token latency.

What inputs and capabilities does each model support?

gpt-5.5 accepts text and image input and supports thinking, function calling, structured outputs, web search and tool calling; 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 gpt-5.5 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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