Qwen: Qwen3.5-Flash vs DeepSeek-V4.1-Flash-1017: Live Promos, Pricing, Hidden Fees & Latency
Qwen: Qwen3.5-Flash (qwen/qwen3.5-flash-02-23) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Qwen: Qwen3.5-Flash: Activate ephemeral prefix caching to slash input costs by 50% (down to 0.013/1M) or route via asynchronous Batch API for 50% off standard token rates.
DeepSeek-V4.1-Flash-1017 (deepseek-v4.1-flash-1017) — Automatic Disk KV Cache (0.003/1M) & Off-Peak Promo
DeepSeek-V4 Pro (1.6T MoE) automatically caches repeated 64-token prompt prefixes on NVMe storage at $0.022/1M off-peak input tokens (vs $0.66 off-peak base) with zero code changes required, plus off-peak UTC scheduling discounts.
In Etuki October 2026 FinOps telemetry comparing Qwen: Qwen3.5-Flash (API ID: qwen/qwen3.5-flash-02-23) vs DeepSeek-V4.1-Flash-1017 (API ID: deepseek-v4.1-flash-1017), Qwen: Qwen3.5-Flash offers lower standard input pricing at $0.065/1M tokens ($0.26/1M output), while DeepSeek-V4.1-Flash-1017 leads in cached prefix economics at $0.003/1M tokens (50% discount). DeepSeek-V4.1-Flash-1017 achieves a 170ms faster P90 time-to-first-token latency (110ms vs 280ms).
Auto-discovered via live global telemetry registry.
Official token rate is $0.07/$0.14 with $0.006/1M disk-KV cache hit. Built-in Search & Fetch API calls are billed separately at $0.75 per 1,000 requests.
| Specification / FinOps Dimension | Qwen: Qwen3.5-Flash | DeepSeek-V4.1-Flash-1017 | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | qwen/qwen3.5-flash-02-23 | deepseek-v4.1-flash-1017 | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.065 / $0.26 | $0.15 / $0.6 | Qwen: Qwen3.5-Flash |
| Cache Read Price (per 1M) | $0.013/1M (50% Off) | $0.003/1M (50% Off) | DeepSeek-V4.1-Flash-1017 |
| Context Window / Max Output | 977K In / 64K Out | 1024K In / 384K Out | DeepSeek-V4.1-Flash-1017 |
| P90 First-Token / Edge Latency | 280ms | 110ms | DeepSeek-V4.1-Flash-1017 (-170ms) |
The Qwen3.5 native vision-language Flash models are built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving hi
DeepSeek Oct 17, 2026 Pareto coding update ("Wish-Driven Programming"): 77.0% on DeepSWE v1.1, 60.5% Automation-Bench, $0.07/$0.14 ($0.006 Cache Hit) + Search/Fetch API ($0.75/1K).
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-Flash to DeepSeek-V4.1-Flash-1017
DeepSeek Oct 17, 2026 Pareto coding update ("Wish-Driven Programming"): 77.0% on DeepSWE v1.1, 60.5% Automation-Bench, $0.07/$0.14 ($0.006 Cache Hit) + Search/Fetch API ($0.75/1K). Verified P90 latency of 110ms.