Anthropic Claude 3.7 Sonnet vs OpenAI GPT-6.1 Terra — API Pricing, 150K Cache & Latency Benchmark
Side-by-side unit economics audit comparing Anthropic Claude 3.7 Sonnet (anthropic/claude-3-7-sonnet: Input $3/1M, Output $15/1M, Warm Cache Read $0.3/1M) 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 Anthropic Claude 3.7 Sonnet to cut input token costs from $3/1M down to $0.3/1M, 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 Anthropic Claude 3.7 Sonnet (API ID: anthropic/claude-3-7-sonnet) 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 $0.8375 over Anthropic Claude 3.7 Sonnet). For latency-sensitive interactive agents, OpenAI GPT-6.1 Terra delivers 315ms faster P90 time-to-first-token (265ms vs 580ms).
| Specification / FinOps Dimension | Anthropic Claude 3.7 Sonnet (anthropic/claude-3-7-sonnet) | OpenAI GPT-6.1 Terra (openai/gpt-6.1-terra) | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | anthropic/claude-3-7-sonnet | 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) | $3 / 1M | $1 / 1M | OpenAI GPT-6.1 Terra |
| Warm Prefix Cache Read (/1M tokens) | $0.3 / 1M | $0.05 / 1M | OpenAI GPT-6.1 Terra |
| Standard Output (/1M tokens) | $15 / 1M | $5 / 1M | OpenAI GPT-6.1 Terra |
| Context Window Capacity | 200K Tokens | 200K Tokens | Anthropic Claude 3.7 Sonnet |
| 150K Prompt × 10 Turns (Unpinned Cold + 2K Out) | $4.8000 | $1.6000 | OpenAI GPT-6.1 Terra |
| 150K × 10 Turns Case A (100% Static Pinned) | $1.1550 (saves $3.6450) | $0.3175 (saves $1.2825) | OpenAI GPT-6.1 Terra (-$0.8375) |
| 150K × 10 Turns Case B (90% Static + 10% Tail) | $1.5195 (saves $3.2805) | $0.4457 (saves $1.1543) | OpenAI GPT-6.1 Terra |
| P50 / P90 First-Token Latency | 394ms / 580ms (78 tok/s) | 180ms / 265ms (132 tok/s) | OpenAI GPT-6.1 Terra (-315ms) |
1. Full-Turn Rate-Card Substitution for Anthropic Claude 3.7 Sonnet: At an uncached input rate of $3/1M, output rate of $15/1M, and warm cache read rate of $0.3/1M, running 10 consecutive 150,000-token coding agent turns (with 2,000 output tokens/turn) without prefix pinning costs $4.8000. Locking 100% static prefixes (Case A: 1 cold turn + 9 warm cached turns + 20K total output) reduces 10-turn spend to $1.1550 (saving $3.6450); under a 90% static prefix + 10% dynamic tail workload (Case B), 10-turn spend is $1.5195.
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 $0.8375 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 $145.00/month ($1740/year) at 25,000 MAU & 50M monthly tokens (80% input / 20% output split with 50% prefix cache hit rate).