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$0.2 /M
Output$1.2 /M
Cache read$0.02 /M
← ModelsGPT 5.6 Luna
Qwen3 235B A22B Instruct 2507
GPT 5.6 Luna vs Qwen3 235B A22B Instruct 2507
Compare GPT 5.6 Luna from OpenAI and Qwen3 235B A22B Instruct 2507 from Qwen on key metrics including benchmarks, price, context length, and other model features. Access both models and hundreds of others through the AIHubMix API.
GPT 5.6 LunaQwen3 235B A22B Instruct 2507+ Add model · 2/4
Qwen3 235B A22B Instruct 2507
Qwen · text, image → text
Qwen3-235B-A22B-Instruct-2507
Input$0.28 /M
Output$1.12 /M
Pricing & Specifications
Prices are per million tokens. Time to First Token and throughput are rolling averages measured on AIHubMix.
GPT 5.6 Luna
Qwen3 235B A22B Instruct 2507
Input /M
$0.2
$0.28
Output /M
$1.2
$1.12
Cache read /M
$0.02
-
Context length
1,050,000
262,144
Max output
128,000
16,384
Time to First Token
5.1 s
1.5 s
Throughput
47.6 tok/s
96.5 tok/s
Modalities
textimage
textimage
Supported Parameters
toolsthinkingstructured outputs
toolsfunction callingstructured outputs
API Formats
chat_completions · responses
Released
July 9, 2026
July 21, 2025
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.
gpt-5.6-lunaqwen3-235b-a22b-instruct-2507
Tokens / day
-
Requests / day
-
Performance Past 3 Days
Measured on real AIHubMix traffic, hourly buckets. Gaps mean no traffic in that hour.
gpt-5.6-lunaqwen3-235b-a22b-instruct-2507
Throughput (tok/s)
-
TTFT (s)
-
Uptime (%)
-
Cost calculator
Estimate your monthly bill for the same workload on each model.
GPT 5.6 Luna
$30.00 /mo
Qwen3 235B A22B Instruct 2507
$33.60 /mo
Monthly = daily × 30. Discounted rates applied where a promotion is active.
FAQ
Which is cheaper: GPT 5.6 Luna, Qwen3 235B A22B Instruct 2507?
Qwen3 235B A22B Instruct 2507: $1.12/M output tokens; GPT 5.6 Luna: $1.2/M. Use the cost calculator above to estimate your own workload.
Which responds faster?
Qwen3 235B A22B Instruct 2507: 1.5s 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?
GPT 5.6 Luna accepts 1,050,000 and Qwen3 235B A22B Instruct 2507 accepts 262,144 input tokens. Maximum output per request is 128,000 tokens on GPT 5.6 Luna and 16,384 tokens on Qwen3 235B A22B Instruct 2507.
Which one generates tokens faster?
Qwen3 235B A22B Instruct 2507 at 96.5 tok/s and GPT 5.6 Luna at 47.6 tok/s, measured as output throughput on AIHubMix — a separate metric from time to first token.
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 235B A22B Instruct 2507 accepts text and image input and supports tool calling, function calling and structured outputs.
Can I call GPT 5.6 Luna and Qwen3 235B A22B Instruct 2507 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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