Meta Llama 4 Scout vs Google: Gemma 3 27B: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Meta Llama 4 Scout (llama-4-scout) vs Google: Gemma 3 27B (google/gemma-3-27b-it). 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.
Google: Gemma 3 27B (google/gemma-3-27b-it) — Google AI Startup Credits ($350K) & 50% Cache Promo
Google DeepMind is currently subsidizing Gemini 4 Argon at 50% off standard rates ($2.00/1M input & $10.00/1M output instead of $4/$20) until November 30, 2026, alongside 95% off Context Caching ($0.10/1M) and up to $350,000 in Google for Startups Cloud/Vertex AI credits.
In Etuki October 2026 FinOps telemetry comparing Meta Llama 4 Scout (API ID: llama-4-scout) vs Google: Gemma 3 27B (API ID: google/gemma-3-27b-it), Google: Gemma 3 27B offers lower standard input pricing at $0.08/1M tokens ($0.45/1M output), while Google: Gemma 3 27B leads in cached prefix economics at $0.04/1M 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 | Google: Gemma 3 27B | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | llama-4-scout | google/gemma-3-27b-it | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.45 / $0.65 | $0.08 / $0.45 | Google: Gemma 3 27B |
| Cache Read Price (per 1M) | $0.225/1M (50% Off) | $0.04/1M (50% Off) | Google: Gemma 3 27B |
| Context Window / Max Output | 400K In / 128K Out | 128K In / 115K 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.
Gemma 3 introduces multimodality, supporting vision-language input and text outputs. It handles context windows up to 128k tokens, understands over 140 languages, and offers improv
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 Google: Gemma 3 27B
Gemma 3 introduces multimodality, supporting vision-language input and text outputs. It handles context windows up to 128k tokens, understands over 140 languages, and offers improv Verified P90 latency of 280ms.