GPT-5.6 Luna is designed for cost-sensitive, high-volume workloads. It roughly corresponds to the nano model tier used in earlier GPT-5 families.
gpt-5.6-luna vs qwen3.8-max
Output tokens cost $1.20 per million on gpt-5.6-luna and $5.07 per million on qwen3.8-max. Input tokens cost $0.20 per million on gpt-5.6-luna and $1.69 per million on qwen3.8-max. Cached input tokens are billed at $0.02 per million on gpt-5.6-luna and $0.17 per million on qwen3.8-max. Context windows are 1,050,000 tokens on gpt-5.6-luna and 991,000 tokens on qwen3.8-max. First-token latency measured on AIHubMix is 3.1s on gpt-5.6-luna and 3.5s on qwen3.8-max. Measured output throughput is 93.6 tokens/s on gpt-5.6-luna and 37.1 tokens/s on qwen3.8-max.
Qwen 3.8 Max(qwen3.8-max) is Alibaba Cloud’s flagship native vision-language model, built on a 2.4-trillion-parameter Mixture-of-Experts (MoE) architecture and supporting context windows of up to 1 million tokens. It is well suited for complex multimodal understanding, advanced reasoning, software development, agentic workflows, and long-context processing. At a similar price to Qwen3.7-Max, Qwen3.8-Max delivers significant improvements in reasoning, coding, and agent capabilities, with overall performance comparable to today’s leading models.
Specs & Pricing
Prices are per million tokens. Latency and throughput are rolling averages measured on AIHubMix.
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.
Tokens / day
Requests / day
Live Performance last 3 days
Measured on real AIHubMix traffic, hourly buckets. Gaps mean no traffic in that hour.
Throughput (TPS)
Latency (s)
Uptime (%)
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: gpt-5.6-luna, qwen3.8-max?
gpt-5.6-luna: $1.20/M output tokens; qwen3.8-max: $5.07/M. Use the cost calculator above to estimate your own workload.
Which responds faster?
gpt-5.6-luna: 3.1s 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-5.6-luna accepts 1,050,000 and qwen3.8-max accepts 991,000 input tokens. Maximum output per request is 128,000 tokens on gpt-5.6-luna and 128,000 tokens on qwen3.8-max.
Which one generates tokens faster?
gpt-5.6-luna at 93.6 tokens/s and qwen3.8-max at 37.1 tokens/s, measured as output throughput on AIHubMix — a separate metric from first-token latency.
What inputs and capabilities does each model support?
gpt-5.6-luna accepts text and image input and supports tool calling, thinking and structured outputs; qwen3.8-max accepts text input and supports tool calling, function calling, structured outputs, web search, long context and thinking.
Can I call gpt-5.6-luna 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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