Meta Llama 4 Scout vs OpenAI: o1: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Meta Llama 4 Scout (llama-4-scout) vs OpenAI: o1 (openai/o1). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
Meta Llama 4 Scout (llama-4-scout) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Meta Llama 4 Scout: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.225/1M) or route via asynchronous Batch API for 50% off standard token rates.
OpenAI: o1 (openai/o1) 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 Meta Llama 4 Scout (API ID: llama-4-scout) vs OpenAI: o1 (API ID: openai/o1), Meta Llama 4 Scout offers lower standard input pricing at $0.45/1M tokens ($0.65/1M output), while Meta Llama 4 Scout leads in cached prefix economics at $0.225/1M tokens (50% discount). Meta Llama 4 Scout achieves a 140ms faster P90 time-to-first-token latency (140ms vs 280ms).
Enable Prompt Context Caching & Batch API to reduce repeated system prompt input token burn by 50%-97.5%.
Auto-discovered via live global telemetry registry.
| Specification / FinOps Dimension | Meta Llama 4 Scout | OpenAI: o1 | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | llama-4-scout | openai/o1 | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.45 / $0.65 | $15 / $60 | Meta Llama 4 Scout |
| Cache Read Price (per 1M) | $0.225/1M (50% Off) | $7.5/1M (50% Off) | Meta Llama 4 Scout |
| Context Window / Max Output | 400K In / 128K Out | 195K In / 98K Out | Meta Llama 4 Scout |
| P90 First-Token / Edge Latency | 140ms | 280ms | Meta Llama 4 Scout (-140ms) |
Meta open-weight multimodal MoE model supporting 10M+ extended context on dedicated clusters.
The latest and strongest model family from OpenAI, o1 is designed to spend more time thinking before responding. The o1 model series is trained with large-scale reinforcement learn
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 Meta Llama 4 Scout to OpenAI: o1
The latest and strongest model family from OpenAI, o1 is designed to spend more time thinking before responding. The o1 model series is trained with large-scale reinforcement learn Verified P90 latency of 280ms.