OpenAI: GPT-6 Luna vs Qwen: Qwen3.5 Plus 2026-02-15: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing OpenAI: GPT-6 Luna (openai/gpt-6-luna) vs Qwen: Qwen3.5 Plus 2026-02-15 (qwen/qwen3.5-plus-02-15). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
OpenAI: GPT-6 Luna (openai/gpt-6-luna) Startup Credits & Batch API 50% Off Promo
OpenAI GPT-6.1 Sol ($2/$10 base rate) qualifies for immediate 75% automatic prefix caching ($0.50/1M), 50% off 24-hour Batch API completions ($1/$5), and up to $150,000 in OpenAI/Azure Foundry credits via Microsoft for Startups Founders Hub (no VC funding required for initial tiers).
Qwen: Qwen3.5 Plus 2026-02-15 (qwen/qwen3.5-plus-02-15) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Qwen: Qwen3.5 Plus 2026-02-15: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.13/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing OpenAI: GPT-6 Luna (API ID: openai/gpt-6-luna) vs Qwen: Qwen3.5 Plus 2026-02-15 (API ID: qwen/qwen3.5-plus-02-15), OpenAI: GPT-6 Luna offers lower standard input pricing at $0.1/1M tokens ($0.5/1M output), while OpenAI: GPT-6 Luna leads in cached prefix economics at $0.05/1M tokens (50% discount). OpenAI: GPT-6 Luna achieves a 0ms faster P90 time-to-first-token latency (280ms vs 280ms).
Auto-discovered via live global telemetry registry.
Auto-discovered via live global telemetry registry.
| Specification / FinOps Dimension | OpenAI: GPT-6 Luna | Qwen: Qwen3.5 Plus 2026-02-15 | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | openai/gpt-6-luna | qwen/qwen3.5-plus-02-15 | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.1 / $0.5 | $0.26 / $1.56 | OpenAI: GPT-6 Luna |
| Cache Read Price (per 1M) | $0.05/1M (50% Off) | $0.13/1M (50% Off) | OpenAI: GPT-6 Luna |
| Context Window / Max Output | 1025K In / 125K Out | 977K In / 64K Out | OpenAI: GPT-6 Luna |
| P90 First-Token / Edge Latency | 280ms | 280ms | OpenAI: GPT-6 Luna (-0ms) |
GPT-6 Luna is the fast, cost-efficient model in OpenAI's GPT-6 series, positioned below GPT-6 Sol. It is suited for high-volume and latency-sensitive workloads such as chat, classi
The Qwen3.5 native vision-language series Plus models are built on a hybrid architecture that integrates linear attention mechanisms with sparse mixture-of-experts models, achievin
Real-Time Stack Cost & Hidden-Fee Simulator (MAU / Token / Egress / GMV)
Calibrated with Reddit r/FinOps & r/devops telemetry: Includes Context Caching, Bandwidth Egress, and MoR Tax
🛰️Switch from OpenAI: GPT-6 Luna to Qwen: Qwen3.5 Plus 2026-02-15
The Qwen3.5 native vision-language series Plus models are built on a hybrid architecture that integrates linear attention mechanisms with sparse mixture-of-experts models, achievin Verified P90 latency of 280ms.