PrismML: Ternary Bonsai 2 27B vs DeepSeek: DeepSeek V3.2 Exp: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing PrismML: Ternary Bonsai 2 27B (prism-ml/ternary-bonsai-2-27b) vs DeepSeek: DeepSeek V3.2 Exp (deepseek/deepseek-v3.2-exp). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
PrismML: Ternary Bonsai 2 27B (prism-ml/ternary-bonsai-2-27b) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for PrismML: Ternary Bonsai 2 27B: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.0375/1M) or route via asynchronous Batch API for 50% off standard token rates.
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.
In Etuki October 2026 FinOps telemetry comparing PrismML: Ternary Bonsai 2 27B (API ID: prism-ml/ternary-bonsai-2-27b) vs DeepSeek: DeepSeek V3.2 Exp (API ID: deepseek/deepseek-v3.2-exp), PrismML: Ternary Bonsai 2 27B offers lower standard input pricing at $0.075/1M tokens ($0.5/1M output), while PrismML: Ternary Bonsai 2 27B leads in cached prefix economics at $0.0375/1M tokens (50% discount). PrismML: Ternary Bonsai 2 27B 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 | PrismML: Ternary Bonsai 2 27B | DeepSeek: DeepSeek V3.2 Exp | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | prism-ml/ternary-bonsai-2-27b | deepseek/deepseek-v3.2-exp | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.075 / $0.5 | $0.27 / $0.41 | PrismML: Ternary Bonsai 2 27B |
| Cache Read Price (per 1M) | $0.0375/1M (50% Off) | $0.135/1M (50% Off) | PrismML: Ternary Bonsai 2 27B |
| Context Window / Max Output | 256K In / 32K Out | 160K In / 144K Out | DeepSeek: DeepSeek V3.2 Exp |
| P90 First-Token / Edge Latency | 280ms | 280ms | PrismML: Ternary Bonsai 2 27B (-0ms) |
Bonsai 2 27B is a 27B-parameter reasoning model from PrismML derived from Qwen3.8-27B. It supports coding, mathematics, tool calling, and image understanding with a 262K-token cont
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
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 PrismML: Ternary Bonsai 2 27B to DeepSeek: DeepSeek V3.2 Exp
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 Verified P90 latency of 280ms.