tokevenGPTvsAlibaba (Qwen)
GPT 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 6 Luna
Fast / BudgetQwen 3.8 Flash
Fast / BudgetInput $/MTok
$0.10
$0.15
Output $/MTok
$0.50
$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
0
vs
0
Summarization
53
vs
0
Q&A
0
vs
0
Extraction
75
vs
0
Reasoning
82
vs
0
Classification
0
vs
0
Creative Writing
63
vs
0
GPT 6 Luna
Qwen 3.8 Flash
Guidance
When to use GPT 6 Luna vs Qwen 3.8 Flash
Choose GPT 6 Luna when...
- -Cost matters: 33% cheaper on input tokens
Choose Qwen 3.8 Flash 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 6 Luna
Qwen 3.8 Flash
100K tokens
$0.02Cheaper
$0.02
1M tokens
$0.36
$0.25Cheaper
10M tokens
$3.65
$2.46Cheaper
FAQ
When should I use GPT 6 Luna instead of Qwen 3.8 Flash?
GPT 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 6 Luna?
Qwen 3.8 Flash input costs $0.15/MTok, which is 50% more than GPT 6 Luna at $0.10/MTok.
What are the context window sizes for GPT 6 Luna and Qwen 3.8 Flash?
GPT 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 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.