DeepSeek: DeepSeek V3.2 vs Pareto 26.10: Live Promos, Pricing, Hidden Fees & Latency
DeepSeek: DeepSeek V3.2 (deepseek/deepseek-v3.2) — Automatic Disk KV Cache (0.14/1M) & 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.
Pareto 26.10 (unbiased/pareto-26.10) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Pareto 26.10: Activate ephemeral prefix caching to slash input costs by 50% (down to 0.4/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing DeepSeek: DeepSeek V3.2 (API ID: deepseek/deepseek-v3.2) vs Pareto 26.10 (API ID: unbiased/pareto-26.10), DeepSeek: DeepSeek V3.2 offers lower standard input pricing at $0.28/1M tokens ($0.42/1M output), while DeepSeek: DeepSeek V3.2 leads in cached prefix economics at $0.14/1M tokens (50% discount). DeepSeek: DeepSeek V3.2 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 | Pareto 26.10 | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | deepseek/deepseek-v3.2 | unbiased/pareto-26.10 | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.28 / $0.42 | $0.8 / $3.2 | DeepSeek: DeepSeek V3.2 |
| Cache Read Price (per 1M) | $0.14/1M (50% Off) | $0.4/1M (50% Off) | DeepSeek: DeepSeek V3.2 |
| Context Window / Max Output | 160K In / 64K Out | 1024K In / 128K Out | Pareto 26.10 |
| P90 First-Token / Edge Latency | 280ms | 280ms | DeepSeek: DeepSeek V3.2 (-0ms) |
DeepSeek-V3.2 is a large language model designed to harmonize high computational efficiency with strong reasoning and agentic tool-use performance. It introduces DeepSeek Sparse At
Pareto is a multimodal composite model built for research, coding, and agentic workflows, while delivering frontier-level performance across a broad range of general-purpose tasks.
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 to Pareto 26.10
Pareto is a multimodal composite model built for research, coding, and agentic workflows, while delivering frontier-level performance across a broad range of general-purpose tasks. Verified P90 latency of 280ms.