Qwen: Qwen3.5-9B vs OpenAI: GPT-5.6 Luna: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Qwen: Qwen3.5-9B (qwen/qwen3.5-9b) vs OpenAI: GPT-5.6 Luna (openai/gpt-5.6-luna). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
Qwen: Qwen3.5-9B (qwen/qwen3.5-9b) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Qwen: Qwen3.5-9B: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.05/1M) or route via asynchronous Batch API for 50% off standard token rates.
OpenAI: GPT-5.6 Luna (openai/gpt-5.6-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).
In Etuki October 2026 FinOps telemetry comparing Qwen: Qwen3.5-9B (API ID: qwen/qwen3.5-9b) vs OpenAI: GPT-5.6 Luna (API ID: openai/gpt-5.6-luna), Qwen: Qwen3.5-9B offers lower standard input pricing at $0.1/1M tokens ($0.15/1M output), while Qwen: Qwen3.5-9B leads in cached prefix economics at $0.05/1M tokens (50% discount). Qwen: Qwen3.5-9B 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: Qwen3.5-9B | OpenAI: GPT-5.6 Luna | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | qwen/qwen3.5-9b | openai/gpt-5.6-luna | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.1 / $0.15 | $0.2 / $1.2 | Qwen: Qwen3.5-9B |
| Cache Read Price (per 1M) | $0.05/1M (50% Off) | $0.1/1M (50% Off) | Qwen: Qwen3.5-9B |
| Context Window / Max Output | 256K In / 32K Out | 1025K In / 125K Out | OpenAI: GPT-5.6 Luna |
| P90 First-Token / Edge Latency | 280ms | 280ms | Qwen: Qwen3.5-9B (-0ms) |
Qwen3.5-9B is a multimodal foundation model from the Qwen3.5 family, designed to deliver strong reasoning, coding, and visual understanding in an efficient 9B-parameter architectur
GPT-5.6 Luna is a fast, cost-efficient model in OpenAI's GPT-5.6 series. It is suited for high-volume, latency-sensitive tasks such as chat, classification, and lightweight agentic
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: Qwen3.5-9B to OpenAI: GPT-5.6 Luna
GPT-5.6 Luna is a fast, cost-efficient model in OpenAI's GPT-5.6 series. It is suited for high-volume, latency-sensitive tasks such as chat, classification, and lightweight agentic Verified P90 latency of 280ms.