Google Gemini 2.5 Pro vs OpenAI GPT-6.1 Terra — API Pricing, 150K Cache & Latency Benchmark
Side-by-side unit economics audit comparing Google Gemini 2.5 Pro (google/gemini-2.5-pro: Input $1.25/1M, Output $10/1M, Warm Cache Read $0.31/1M) against OpenAI GPT-6.1 Terra (openai/gpt-6.1-terra: Input $1/1M, Output $5/1M, Warm Cache Read $0.05/1M).
Activate 4-breakpoint prefix caching on Google Gemini 2.5 Pro to cut input token costs from $1.25/1M down to $0.31/1M, or route async workloads via Batch API for 50% off.
Lock static system prompt prefixes on OpenAI GPT-6.1 Terra to pay $0.05/1M warm cache rates instead of $1/1M uncached input, plus eligible startup cloud credits.
In Etuki FinOps telemetry comparing Google Gemini 2.5 Pro (API ID: google/gemini-2.5-pro) vs OpenAI GPT-6.1 Terra (API ID: openai/gpt-6.1-terra), OpenAI GPT-6.1 Terra offers lower standard uncached input pricing at $1/1M tokens, while OpenAI GPT-6.1 Terra leads in 10-turn 150K cache-pinned coding economics at $0.3175 per 10 turns (saving $0.4885 over Google Gemini 2.5 Pro). For latency-sensitive interactive agents, OpenAI GPT-6.1 Terra delivers 295ms faster P90 time-to-first-token (265ms vs 560ms).
| Specification / FinOps Dimension | Google Gemini 2.5 Pro (google/gemini-2.5-pro) | OpenAI GPT-6.1 Terra (openai/gpt-6.1-terra) | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | google/gemini-2.5-pro | openai/gpt-6.1-terra | UMCE 563-Registry Locked |
| 563-Registry & Routing Eligibility | is_known: true | routable: true | is_known: true | routable: true | Both Merkle Verified |
| Standard Uncached Input (/1M tokens) | $1.25 / 1M | $1 / 1M | OpenAI GPT-6.1 Terra |
| Warm Prefix Cache Read (/1M tokens) | $0.31 / 1M | $0.05 / 1M | OpenAI GPT-6.1 Terra |
| Standard Output (/1M tokens) | $10 / 1M | $5 / 1M | OpenAI GPT-6.1 Terra |
| Context Window Capacity | 200K Tokens | 200K Tokens | Google Gemini 2.5 Pro |
| 150K Prompt × 10 Turns (Unpinned Cold + 2K Out) | $2.0750 | $1.6000 | OpenAI GPT-6.1 Terra |
| 150K × 10 Turns Case A (100% Static Pinned) | $0.8060 (saves $1.2690) | $0.3175 (saves $1.2825) | OpenAI GPT-6.1 Terra (-$0.4885) |
| 150K × 10 Turns Case B (90% Static + 10% Tail) | $0.9329 (saves $1.1421) | $0.4457 (saves $1.1543) | OpenAI GPT-6.1 Terra |
| P50 / P90 First-Token Latency | 381ms / 560ms (86 tok/s) | 180ms / 265ms (132 tok/s) | OpenAI GPT-6.1 Terra (-295ms) |
1. Full-Turn Rate-Card Substitution for Google Gemini 2.5 Pro: At an uncached input rate of $1.25/1M, output rate of $10/1M, and warm cache read rate of $0.31/1M, running 10 consecutive 150,000-token coding agent turns (with 2,000 output tokens/turn) without prefix pinning costs $2.0750. Locking 100% static prefixes (Case A: 1 cold turn + 9 warm cached turns + 20K total output) reduces 10-turn spend to $0.8060 (saving $1.2690); under a 90% static prefix + 10% dynamic tail workload (Case B), 10-turn spend is $0.9329.
2. Full-Turn Rate-Card Substitution for OpenAI GPT-6.1 Terra & Winner Verdict: On OpenAI GPT-6.1 Terra ($1/1M input, $5/1M output, $0.05/1M warm cache), 10 unpinned 150K turns cost $1.6000, dropping to $0.3175 in Case A and $0.4457 in Case B. Across every 10-turn 150K coding loop (including output tokens), OpenAI GPT-6.1 Terra delivers an additional $0.4885 Case-A cost advantage.
Production Workload TCO: 25,000 MAU • 50M Tokens/Mo (50% Cache Hit) • 2,000 GB Egress
💡 Optimal FinOps Verdict: Deploying OpenAI GPT-6.1 Terra saves $60.20/month ($722/year) at 25,000 MAU & 50M monthly tokens (80% input / 20% output split with 50% prefix cache hit rate).