Meta: Llama 3.3 70B Instruct vs Google: Gemini 3.1 Pro Preview: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Meta: Llama 3.3 70B Instruct (meta-llama/llama-3.3-70b-instruct) vs Google: Gemini 3.1 Pro Preview (google/gemini-3.1-pro-preview). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
Meta: Llama 3.3 70B Instruct (meta-llama/llama-3.3-70b-instruct) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Meta: Llama 3.3 70B Instruct: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.295/1M) or route via asynchronous Batch API for 50% off standard token rates.
Google: Gemini 3.1 Pro Preview (google/gemini-3.1-pro-preview) — 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 3.3 70B Instruct (API ID: meta-llama/llama-3.3-70b-instruct) vs Google: Gemini 3.1 Pro Preview (API ID: google/gemini-3.1-pro-preview), Meta: Llama 3.3 70B Instruct offers lower standard input pricing at $0.59/1M tokens ($0.79/1M output), while Meta: Llama 3.3 70B Instruct leads in cached prefix economics at $0.295/1M tokens (50% discount). Meta: Llama 3.3 70B Instruct 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 | Meta: Llama 3.3 70B Instruct | Google: Gemini 3.1 Pro Preview | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | meta-llama/llama-3.3-70b-instruct | google/gemini-3.1-pro-preview | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.59 / $0.79 | $2 / $12 | Meta: Llama 3.3 70B Instruct |
| Cache Read Price (per 1M) | $0.295/1M (50% Off) | $1/1M (50% Off) | Meta: Llama 3.3 70B Instruct |
| Context Window / Max Output | 128K In / 32K Out | 1024K In / 64K Out | Google: Gemini 3.1 Pro Preview |
| P90 First-Token / Edge Latency | 280ms | 280ms | Meta: Llama 3.3 70B Instruct (-0ms) |
The Meta Llama 3.3 multilingual large language model (LLM) is a pretrained and instruction tuned generative model in 70B (text in/text out). The Llama 3.3 instruction tuned text on
Gemini 3.1 Pro Preview is Google’s frontier reasoning model, delivering enhanced software engineering performance, improved agentic reliability, and more efficient token usage acro
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 3.3 70B Instruct to Google: Gemini 3.1 Pro Preview
Gemini 3.1 Pro Preview is Google’s frontier reasoning model, delivering enhanced software engineering performance, improved agentic reliability, and more efficient token usage acro Verified P90 latency of 280ms.