Qwen: Qwen3.8 Max (0902) vs OpenAI: GPT-6 Luna (batch): Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Qwen: Qwen3.8 Max (0902) (qwen/qwen3.8-max-0902) vs OpenAI: GPT-6 Luna (batch) (openai/gpt-6-luna:batch). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
Qwen: Qwen3.8 Max (0902) (qwen/qwen3.8-max-0902) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Qwen: Qwen3.8 Max (0902): Activate ephemeral prefix caching to slash input costs by 50% (down to $1/1M) or route via asynchronous Batch API for 50% off standard token rates.
OpenAI: GPT-6 Luna (batch) (openai/gpt-6-luna:batch) 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).
In Etuki October 2026 FinOps telemetry comparing Qwen: Qwen3.8 Max (0902) (API ID: qwen/qwen3.8-max-0902) vs OpenAI: GPT-6 Luna (batch) (API ID: openai/gpt-6-luna:batch), OpenAI: GPT-6 Luna (batch) offers lower standard input pricing at $0.05/1M tokens ($0.25/1M output), while OpenAI: GPT-6 Luna (batch) leads in cached prefix economics at $0.025/1M tokens (50% discount). Qwen: Qwen3.8 Max (0902) 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 | Qwen: Qwen3.8 Max (0902) | OpenAI: GPT-6 Luna (batch) | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | qwen/qwen3.8-max-0902 | openai/gpt-6-luna:batch | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $2 / $6 | $0.05 / $0.25 | OpenAI: GPT-6 Luna (batch) |
| Cache Read Price (per 1M) | $1/1M (50% Off) | $0.025/1M (50% Off) | OpenAI: GPT-6 Luna (batch) |
| Context Window / Max Output | 977K In / 128K Out | 1025K In / 125K Out | Qwen: Qwen3.8 Max (0902) |
| P90 First-Token / Edge Latency | 280ms | 280ms | Qwen: Qwen3.8 Max (0902) (-0ms) |
Qwen3.8 Max 0902 is an updated snapshot of Qwen3.8 Max from Alibaba's Qwen team. It is a 2.4-trillion-parameter mixture-of-experts model that accepts text, image, and video input a
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
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 Qwen: Qwen3.8 Max (0902) to OpenAI: GPT-6 Luna (batch)
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 Verified P90 latency of 280ms.