Qwen: Qwen3.5-35B-A3B vs OpenAI: GPT-5.6 Luna (batch): Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Qwen: Qwen3.5-35B-A3B (qwen/qwen3.5-35b-a3b) vs OpenAI: GPT-5.6 Luna (batch) (openai/gpt-5.6-luna:batch). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
Qwen: Qwen3.5-35B-A3B (qwen/qwen3.5-35b-a3b) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Qwen: Qwen3.5-35B-A3B: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.075/1M) or route via asynchronous Batch API for 50% off standard token rates.
OpenAI: GPT-5.6 Luna (batch) (openai/gpt-5.6-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: Qwen3.5-35B-A3B (API ID: qwen/qwen3.5-35b-a3b) vs OpenAI: GPT-5.6 Luna (batch) (API ID: openai/gpt-5.6-luna:batch), OpenAI: GPT-5.6 Luna (batch) offers lower standard input pricing at $0.1/1M tokens ($0.6/1M output), while OpenAI: GPT-5.6 Luna (batch) leads in cached prefix economics at $0.05/1M tokens (50% discount). Qwen: Qwen3.5-35B-A3B 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: Qwen3.5-35B-A3B | OpenAI: GPT-5.6 Luna (batch) | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | qwen/qwen3.5-35b-a3b | openai/gpt-5.6-luna:batch | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.15 / $1 | $0.1 / $0.6 | OpenAI: GPT-5.6 Luna (batch) |
| Cache Read Price (per 1M) | $0.075/1M (50% Off) | $0.05/1M (50% Off) | OpenAI: GPT-5.6 Luna (batch) |
| Context Window / Max Output | 256K In / 16K Out | 1025K In / 125K Out | OpenAI: GPT-5.6 Luna (batch) |
| P90 First-Token / Edge Latency | 280ms | 280ms | Qwen: Qwen3.5-35B-A3B (-0ms) |
The Qwen3.5 Series 35B-A3B is a native vision-language model designed with a hybrid architecture that integrates linear attention mechanisms and a sparse mixture-of-experts model,
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: Qwen3.5-35B-A3B to OpenAI: GPT-5.6 Luna (batch)
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.