Poolside: Laguna S 2.1 vs OpenAI: GPT-6 Luna (batch): Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Poolside: Laguna S 2.1 (poolside/laguna-s-2.1) vs OpenAI: GPT-6 Luna (batch) (openai/gpt-6-luna:batch). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
Poolside: Laguna S 2.1 (poolside/laguna-s-2.1) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Poolside: Laguna S 2.1: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.045/1M) or route via asynchronous Batch API for 50% off standard token rates.
OpenAI: GPT-6 Luna (batch) (openai/gpt-6-luna:batch) Startup Credits & Batch API 50% Off Promo
OpenAI GPT-6.1 Sol ($2/$10 base rate) qualifies for immediate 75% automatic prefix caching ($0.50/1M), 50% off 24-hour Batch API completions ($1/$5), and up to $150,000 in OpenAI/Azure Foundry credits via Microsoft for Startups Founders Hub (no VC funding required for initial tiers).
In Etuki October 2026 FinOps telemetry comparing Poolside: Laguna S 2.1 (API ID: poolside/laguna-s-2.1) vs OpenAI: GPT-6 Luna (batch) (API ID: openai/gpt-6-luna:batch), OpenAI: GPT-6 Luna (batch) offers lower standard input pricing at $0.05/1M tokens ($0.25/1M output), while OpenAI: GPT-6 Luna (batch) leads in cached prefix economics at $0.025/1M tokens (50% discount). Poolside: Laguna S 2.1 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 | Poolside: Laguna S 2.1 | OpenAI: GPT-6 Luna (batch) | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | poolside/laguna-s-2.1 | openai/gpt-6-luna:batch | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.09 / $0.18 | $0.05 / $0.25 | OpenAI: GPT-6 Luna (batch) |
| Cache Read Price (per 1M) | $0.045/1M (50% Off) | $0.025/1M (50% Off) | OpenAI: GPT-6 Luna (batch) |
| Context Window / Max Output | 1024K In / 128K Out | 1025K In / 125K Out | Poolside: Laguna S 2.1 |
| P90 First-Token / Edge Latency | 280ms | 280ms | Poolside: Laguna S 2.1 (-0ms) |
Laguna S 2.1 is the latest coding agent model from [Poolside](<https://poolside.ai/>). Laguna S 2.1 is a 118B total parameter model with 8B active parameters, scoring 70.2% on Term
GPT-6 Luna is the fast, cost-efficient model in OpenAI's GPT-6 series, positioned below GPT-6 Sol. It is suited for high-volume and latency-sensitive workloads such as chat, classi
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 Poolside: Laguna S 2.1 to OpenAI: GPT-6 Luna (batch)
GPT-6 Luna is the fast, cost-efficient model in OpenAI's GPT-6 series, positioned below GPT-6 Sol. It is suited for high-volume and latency-sensitive workloads such as chat, classi Verified P90 latency of 280ms.