gpt-5.6-luna
OpenAI · text, image → text
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.
Input$0.20 /M
Output$1.20 /M
← Modelsgpt-5.6-luna
qwen3.7-flash
gpt-5.6-luna vs qwen3.7-flash
Output tokens cost $1.20 per million on gpt-5.6-luna and $1.13 per million on qwen3.7-flash. Input tokens cost $0.20 per million on gpt-5.6-luna and $0.28 per million on qwen3.7-flash. Cached input tokens are billed at $0.02 per million on gpt-5.6-luna and $0.06 per million on qwen3.7-flash. Context windows are 1,050,000 tokens on gpt-5.6-luna and 991,000 tokens on qwen3.7-flash. First-token latency measured on AIHubMix is 3.1s on gpt-5.6-luna and 2.1s on qwen3.7-flash. Measured output throughput is 93.6 tokens/s on gpt-5.6-luna and 104.1 tokens/s on qwen3.7-flash.
gpt-5.6-lunaqwen3.7-flash+ Add model 2/4
qwen3.7-flash
Qwen · text → text
The Qwen 3.7 series' mid-to-high cost-performance "Plus" model builds on strong text capabilities with a comprehensive upgrade to vision-language abilities, while retaining full agent capabilities in coding, tool use, and productivity workflows. Its core features are multimodal interactive hybrid agent capabilities, able to perceive real-world scenes, read screens and operate GUIs, generate code based on visual references, and provide end-to-end navigation of mobile applications.
Input$0.28 /M
Output$1.13 /M
Specs & Pricing
Prices are per million tokens. Latency and throughput are rolling averages measured on AIHubMix.
gpt-5.6-luna
qwen3.7-flash
Input price
$0.20
$0.28
Output price
$1.20
$1.13
Cache read
$0.02
$0.06
Context window
1,050,000
991,000
Max output
128,000
64,000
Latency (first token)
3.1 s
2.1 s
Throughput
93.6 TPS
104.1 TPS
Modalities
textimage
text
Features
toolsthinkingstructured outputs
toolsfunction callingstructured outputsweblong contextthinking
Endpoints
chat_completions · 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-5.6-lunaqwen3.7-flash
Tokens / day
-
Requests / day
-
Live Performance last 3 days
Measured on real AIHubMix traffic, hourly buckets. Gaps mean no traffic in that hour.
gpt-5.6-lunaqwen3.7-flash
Throughput (TPS)
-
Latency (s)
-
Uptime (%)
-
Cost Calculator
Estimate your monthly bill for the same workload on each model.
gpt-5.6-luna
$30.00 /mo
qwen3.7-flash
$33.84 /mo
Monthly = daily × 30. Discounted rates applied where a promotion is active.
FAQ
Which is cheaper: gpt-5.6-luna, qwen3.7-flash?
qwen3.7-flash: $1.13/M output tokens; gpt-5.6-luna: $1.20/M. Use the cost calculator above to estimate your own workload.
Which responds faster?
qwen3.7-flash: 2.1s 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 qwen3.7-flash accepts 991,000 input tokens. Maximum output per request is 128,000 tokens on gpt-5.6-luna and 64,000 tokens on qwen3.7-flash.
Which one generates tokens faster?
qwen3.7-flash at 104.1 tokens/s and gpt-5.6-luna at 93.6 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; qwen3.7-flash 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 qwen3.7-flash 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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