Qwen: Qwen3.5-27B vs Qwen: Qwen3.8 Max (0902): Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Qwen: Qwen3.5-27B (qwen/qwen3.5-27b) vs Qwen: Qwen3.8 Max (0902) (qwen/qwen3.8-max-0902). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
Qwen: Qwen3.5-27B (qwen/qwen3.5-27b) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Qwen: Qwen3.5-27B: 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.
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.
In Etuki October 2026 FinOps telemetry comparing Qwen: Qwen3.5-27B (API ID: qwen/qwen3.5-27b) vs Qwen: Qwen3.8 Max (0902) (API ID: qwen/qwen3.8-max-0902), Qwen: Qwen3.5-27B offers lower standard input pricing at $0.26/1M tokens ($2.6/1M output), while Qwen: Qwen3.5-27B leads in cached prefix economics at $0.13/1M tokens (50% discount). Qwen: Qwen3.5-27B 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: Qwen3.5-27B | Qwen: Qwen3.8 Max (0902) | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | qwen/qwen3.5-27b | qwen/qwen3.8-max-0902 | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.26 / $2.6 | $2 / $6 | Qwen: Qwen3.5-27B |
| Cache Read Price (per 1M) | $0.13/1M (50% Off) | $1/1M (50% Off) | Qwen: Qwen3.5-27B |
| Context Window / Max Output | 256K In / 80K Out | 977K In / 128K Out | Qwen: Qwen3.8 Max (0902) |
| P90 First-Token / Edge Latency | 280ms | 280ms | Qwen: Qwen3.5-27B (-0ms) |
The Qwen3.5 27B native vision-language Dense model incorporates a linear attention mechanism, delivering fast response times while balancing inference speed and performance. Its ov
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
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: Qwen3.5-27B to Qwen: Qwen3.8 Max (0902)
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 Verified P90 latency of 280ms.