DeepSeek V3.1 Terminus vs OpenAI GPT-4.1 — API Pricing, 150K Cache & Latency Benchmark
Side-by-side unit economics audit comparing DeepSeek V3.1 Terminus (deepseek/deepseek-v3-1-terminus: Input $0.27/1M, Output $1.1/1M, Warm Cache Read $0.07/1M) against OpenAI GPT-4.1 (openai/gpt-4.1: Input $2/1M, Output $8/1M, Warm Cache Read $0.5/1M).
Activate 4-breakpoint prefix caching on DeepSeek V3.1 Terminus to cut input token costs from $0.27/1M down to $0.07/1M, or route async workloads via Batch API for 50% off.
Lock static system prompt prefixes on OpenAI GPT-4.1 to pay $0.5/1M warm cache rates instead of $2/1M uncached input, plus eligible startup cloud credits.
In Etuki FinOps telemetry comparing DeepSeek V3.1 Terminus (API ID: deepseek/deepseek-v3-1-terminus) vs OpenAI GPT-4.1 (API ID: openai/gpt-4.1), DeepSeek V3.1 Terminus offers lower standard uncached input pricing at $0.27/1M tokens, while DeepSeek V3.1 Terminus leads in 10-turn 150K cache-pinned coding economics at $0.1570 per 10 turns (saving $0.9780 over OpenAI GPT-4.1). For latency-sensitive interactive agents, DeepSeek V3.1 Terminus delivers 60ms faster P90 time-to-first-token (350ms vs 410ms).
| Specification / FinOps Dimension | DeepSeek V3.1 Terminus (deepseek/deepseek-v3-1-terminus) | OpenAI GPT-4.1 (openai/gpt-4.1) | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | deepseek/deepseek-v3-1-terminus | openai/gpt-4.1 | 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) | $0.27 / 1M | $2 / 1M | DeepSeek V3.1 Terminus |
| Warm Prefix Cache Read (/1M tokens) | $0.07 / 1M | $0.5 / 1M | DeepSeek V3.1 Terminus |
| Standard Output (/1M tokens) | $1.1 / 1M | $8 / 1M | DeepSeek V3.1 Terminus |
| Context Window Capacity | 200K Tokens | 200K Tokens | DeepSeek V3.1 Terminus |
| 150K Prompt × 10 Turns (Unpinned Cold + 2K Out) | $0.4270 | $3.1600 | DeepSeek V3.1 Terminus |
| 150K × 10 Turns Case A (100% Static Pinned) | $0.1570 (saves $0.2700) | $1.1350 (saves $2.0250) | DeepSeek V3.1 Terminus (-$0.9780) |
| 150K × 10 Turns Case B (90% Static + 10% Tail) | $0.1840 (saves $0.2430) | $1.3375 (saves $1.8225) | DeepSeek V3.1 Terminus |
| P50 / P90 First-Token Latency | 238ms / 350ms (104 tok/s) | 279ms / 410ms (98 tok/s) | DeepSeek V3.1 Terminus (-60ms) |
1. Full-Turn Rate-Card Substitution for DeepSeek V3.1 Terminus: At an uncached input rate of $0.27/1M, output rate of $1.1/1M, and warm cache read rate of $0.07/1M, running 10 consecutive 150,000-token coding agent turns (with 2,000 output tokens/turn) without prefix pinning costs $0.4270. Locking 100% static prefixes (Case A: 1 cold turn + 9 warm cached turns + 20K total output) reduces 10-turn spend to $0.1570 (saving $0.2700); under a 90% static prefix + 10% dynamic tail workload (Case B), 10-turn spend is $0.1840.
2. Full-Turn Rate-Card Substitution for OpenAI GPT-4.1 & Winner Verdict: On OpenAI GPT-4.1 ($2/1M input, $8/1M output, $0.5/1M warm cache), 10 unpinned 150K turns cost $3.1600, dropping to $1.1350 in Case A and $1.3375 in Case B. Across every 10-turn 150K coding loop (including output tokens), DeepSeek V3.1 Terminus delivers an additional $0.9780 Case-A cost advantage.
Production Workload TCO: 25,000 MAU • 50M Tokens/Mo (50% Cache Hit) • 2,000 GB Egress
💡 Optimal FinOps Verdict: Deploying DeepSeek V3.1 Terminus saves $112.20/month ($1346/year) at 25,000 MAU & 50M monthly tokens (80% input / 20% output split with 50% prefix cache hit rate).