Qwen: Qwen3.5 397B A17B vs NVIDIA: Nemotron 3.5 Super VL: Live Promos, Pricing, Hidden Fees & Latency
Qwen: Qwen3.5 397B A17B (qwen/qwen3.5-397b-a17b) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Qwen: Qwen3.5 397B A17B: Activate ephemeral prefix caching to slash input costs by 50% (down to 0.078/1M) or route via asynchronous Batch API for 50% off standard token rates.
NVIDIA: Nemotron 3.5 Super VL (nvidia/nemotron-3.5-super-vl) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for NVIDIA: Nemotron 3.5 Super VL: 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.
In Etuki October 2026 FinOps telemetry comparing Qwen: Qwen3.5 397B A17B (API ID: qwen/qwen3.5-397b-a17b) vs NVIDIA: Nemotron 3.5 Super VL (API ID: nvidia/nemotron-3.5-super-vl), NVIDIA: Nemotron 3.5 Super VL offers lower standard input pricing at $0.15/1M tokens ($0.5/1M output), while NVIDIA: Nemotron 3.5 Super VL leads in cached prefix economics at $0.075/1M tokens (50% discount). Qwen: Qwen3.5 397B A17B 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 397B A17B | NVIDIA: Nemotron 3.5 Super VL | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | qwen/qwen3.5-397b-a17b | nvidia/nemotron-3.5-super-vl | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.39 / $2.34 | $0.15 / $0.5 | NVIDIA: Nemotron 3.5 Super VL |
| Cache Read Price (per 1M) | $0.078/1M (50% Off) | $0.075/1M (50% Off) | NVIDIA: Nemotron 3.5 Super VL |
| Context Window / Max Output | 256K In / 64K Out | 1024K In / 230K Out | NVIDIA: Nemotron 3.5 Super VL |
| P90 First-Token / Edge Latency | 280ms | 280ms | Qwen: Qwen3.5 397B A17B (-0ms) |
The Qwen3.5 series 397B-A17B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, ach
NVIDIA Nemotron 3.5 Super VL is an open multimodal mixture-of-experts model from NVIDIA, with 12B active parameters out of 120B total. It takes text, images, documents, GUI screens
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 397B A17B to NVIDIA: Nemotron 3.5 Super VL
NVIDIA Nemotron 3.5 Super VL is an open multimodal mixture-of-experts model from NVIDIA, with 12B active parameters out of 120B total. It takes text, images, documents, GUI screens Verified P90 latency of 280ms.