DeepSeek: DeepSeek V3.2 Exp vs Qwen: Qwen3 30B A3B: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing DeepSeek: DeepSeek V3.2 Exp (deepseek/deepseek-v3.2-exp) vs Qwen: Qwen3 30B A3B (qwen/qwen3-30b-a3b). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
DeepSeek: DeepSeek V3.2 Exp (deepseek/deepseek-v3.2-exp) — Automatic Disk KV Cache ($0.135/1M) & Off-Peak Promo
DeepSeek-V4 Pro (1.6T MoE) automatically caches repeated 64-token prompt prefixes on NVMe storage at $0.07/1M input tokens (50% off $0.14 base) with zero code changes required, plus off-peak UTC scheduling discounts.
Qwen: Qwen3 30B A3B (qwen/qwen3-30b-a3b) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Qwen: Qwen3 30B A3B: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.06/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing DeepSeek: DeepSeek V3.2 Exp (API ID: deepseek/deepseek-v3.2-exp) vs Qwen: Qwen3 30B A3B (API ID: qwen/qwen3-30b-a3b), Qwen: Qwen3 30B A3B offers lower standard input pricing at $0.12/1M tokens ($0.5/1M output), while Qwen: Qwen3 30B A3B leads in cached prefix economics at $0.06/1M tokens (50% discount). DeepSeek: DeepSeek V3.2 Exp 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 | DeepSeek: DeepSeek V3.2 Exp | Qwen: Qwen3 30B A3B | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | deepseek/deepseek-v3.2-exp | qwen/qwen3-30b-a3b | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.27 / $0.41 | $0.12 / $0.5 | Qwen: Qwen3 30B A3B |
| Cache Read Price (per 1M) | $0.135/1M (50% Off) | $0.06/1M (50% Off) | Qwen: Qwen3 30B A3B |
| Context Window / Max Output | 160K In / 144K Out | 40K In / 16K Out | DeepSeek: DeepSeek V3.2 Exp |
| P90 First-Token / Edge Latency | 280ms | 280ms | DeepSeek: DeepSeek V3.2 Exp (-0ms) |
DeepSeek-V3.2-Exp is an experimental large language model released by DeepSeek as an intermediate step between V3.1 and future architectures. It introduces DeepSeek Sparse Attentio
Qwen3, the latest generation in the Qwen large language model series, features both dense and mixture-of-experts (MoE) architectures to excel in reasoning, multilingual support, an
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 DeepSeek: DeepSeek V3.2 Exp to Qwen: Qwen3 30B A3B
Qwen3, the latest generation in the Qwen large language model series, features both dense and mixture-of-experts (MoE) architectures to excel in reasoning, multilingual support, an Verified P90 latency of 280ms.