tokevenGPTvsAlibaba (Qwen)
GPT 5.6 Luna vs Qwen 3.8 Flash
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 Flash
Fast / BudgetInput $/MTok
$0.20
$0.15
Output $/MTok
$1.20
$0.47
Cache discount
90% off
89% 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 Flash
Guidance
When to use GPT 5.6 Luna vs Qwen 3.8 Flash
Choose GPT 5.6 Luna when...
- Similar performance; consider provider preference or ecosystem fit.
Choose Qwen 3.8 Flash when...
- -Cost matters: 25% cheaper on input tokens
- -You need a larger context window (1M vs 922K)
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 Flash
100K tokens
$0.05
$0.02Cheaper
1M tokens
$0.82
$0.25Cheaper
10M tokens
$8.20
$2.46Cheaper
FAQ
When should I use GPT 5.6 Luna instead of Qwen 3.8 Flash?
GPT 5.6 Luna and Qwen 3.8 Flash perform similarly across all tracked tasks. Pick based on pricing and provider preference.
Is Qwen 3.8 Flash cheaper than GPT 5.6 Luna?
Yes. Qwen 3.8 Flash input costs $0.15/MTok vs $0.20/MTok for GPT 5.6 Luna, saving 25% on input.
What are the context window sizes for GPT 5.6 Luna and Qwen 3.8 Flash?
GPT 5.6 Luna has a 922K token context window. Qwen 3.8 Flash 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 Flash 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.