Perceptron: Perceptron Mk1.5 vs DeepSeek: DeepSeek V4 Pro 0813: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Perceptron: Perceptron Mk1.5 (perceptron/perceptron-mk1.5) vs DeepSeek: DeepSeek V4 Pro 0813 (deepseek/deepseek-v4-pro-0813). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
Perceptron: Perceptron Mk1.5 (perceptron/perceptron-mk1.5) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Perceptron: Perceptron Mk1.5: 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.
DeepSeek: DeepSeek V4 Pro 0813 (deepseek/deepseek-v4-pro-0813) — Automatic Disk KV Cache ($0.33/1M) & 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.
In Etuki October 2026 FinOps telemetry comparing Perceptron: Perceptron Mk1.5 (API ID: perceptron/perceptron-mk1.5) vs DeepSeek: DeepSeek V4 Pro 0813 (API ID: deepseek/deepseek-v4-pro-0813), Perceptron: Perceptron Mk1.5 offers lower standard input pricing at $0.15/1M tokens ($1.5/1M output), while Perceptron: Perceptron Mk1.5 leads in cached prefix economics at $0.075/1M tokens (50% discount). Perceptron: Perceptron Mk1.5 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 | Perceptron: Perceptron Mk1.5 | DeepSeek: DeepSeek V4 Pro 0813 | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | perceptron/perceptron-mk1.5 | deepseek/deepseek-v4-pro-0813 | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.15 / $1.5 | $0.66 / $1.98 | Perceptron: Perceptron Mk1.5 |
| Cache Read Price (per 1M) | $0.075/1M (50% Off) | $0.33/1M (50% Off) | Perceptron: Perceptron Mk1.5 |
| Context Window / Max Output | 36K In / 8K Out | 1024K In / 384K Out | DeepSeek: DeepSeek V4 Pro 0813 |
| P90 First-Token / Edge Latency | 280ms | 280ms | Perceptron: Perceptron Mk1.5 (-0ms) |
Perceptron Mk1.5 is Perceptron's embodied reasoning model for physical agents. It accepts text, image, video, and audio input, and answers with text plus optional structured annota
DeepSeek V4 Pro 0813 is a large-scale mixture-of-experts model from DeepSeek. This is the GA release of DeepSeek V4 Pro.
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 Perceptron: Perceptron Mk1.5 to DeepSeek: DeepSeek V4 Pro 0813
DeepSeek V4 Pro 0813 is a large-scale mixture-of-experts model from DeepSeek. This is the GA release of DeepSeek V4 Pro. Verified P90 latency of 280ms.