tokevenGPTvsAlibaba (Qwen)
GPT 5.6 Luna vs Qwen 3.8 Max
Side-by-side comparison of pricing, task quality, and projected cost at higher scale.
Pricing
Side-by-side pricing
GPT 5.6 Luna
Fast / BudgetQwen 3.8 Max
FlagshipInput $/MTok
$0.20
$2.00
Output $/MTok
$1.20
$6.00
Cache discount
90% off
88% off
Context
922K
1M
Quality
Task confidence comparison
Confidence score from zero to one hundred by task type, where higher is better.
Code Generation
62
vs
0
Code Review
68
vs
0
Summarization
57
vs
0
Q&A
85
vs
0
Extraction
74
vs
0
Reasoning
86
vs
0
Classification
91
vs
0
Creative Writing
69
vs
0
GPT 5.6 Luna
Qwen 3.8 Max
Guidance
When to use GPT 5.6 Luna vs Qwen 3.8 Max
Choose GPT 5.6 Luna when...
- -Cost matters: 90% cheaper on input tokens
Choose Qwen 3.8 Max when...
- -You need a larger context window (1M vs 922K)
- Similar performance; consider provider preference or ecosystem fit.
At scale
Cost at scale
Estimated cost assuming a seventy percent input and thirty percent output token split.
GPT 5.6 Luna
Qwen 3.8 Max
100K tokens
$0.05Cheaper
$0.32
1M tokens
$0.82Cheaper
$3.20
10M tokens
$8.20Cheaper
$32.00
FAQ
When should I use GPT 5.6 Luna instead of Qwen 3.8 Max?
GPT 5.6 Luna and Qwen 3.8 Max perform similarly across all tracked tasks. Pick based on pricing and provider preference.
Is Qwen 3.8 Max cheaper than GPT 5.6 Luna?
Qwen 3.8 Max input costs $2.00/MTok, which is 900% more than GPT 5.6 Luna at $0.20/MTok.
What are the context window sizes for GPT 5.6 Luna and Qwen 3.8 Max?
GPT 5.6 Luna has a 922K token context window. Qwen 3.8 Max has a 1M token context window.
Go deeper on either model
Per-call cost calculators, provider lineups, and price history for both models on this page.
Other comparisons
How GPT 5.6 Luna and Qwen 3.8 Max stack up against the rest of the field.
Track your real costs
Comparisons show estimated costs at list price. The dashboard reveals your real spend and savings.