DeepSeek V3 vs Google Gemini 2.5 Flash — API Pricing, 150K Cache & Latency Benchmark
Side-by-side unit economics audit comparing DeepSeek V3 (deepseek/deepseek-v3: Input $1/1M, Output $4/1M, Warm Cache Read $0.1/1M) against Google Gemini 2.5 Flash (google/gemini-2.5-flash: Input $0.15/1M, Output $0.6/1M, Warm Cache Read $0.038/1M).
Activate 4-breakpoint prefix caching on DeepSeek V3 to cut input token costs from $1/1M down to $0.1/1M, or route async workloads via Batch API for 50% off.
Lock static system prompt prefixes on Google Gemini 2.5 Flash to pay $0.038/1M warm cache rates instead of $0.15/1M uncached input, plus eligible startup cloud credits.
In Etuki FinOps telemetry comparing DeepSeek V3 (API ID: deepseek/deepseek-v3) vs Google Gemini 2.5 Flash (API ID: google/gemini-2.5-flash), Google Gemini 2.5 Flash offers lower standard uncached input pricing at $0.15/1M tokens, while Google Gemini 2.5 Flash leads in 10-turn 150K cache-pinned coding economics at $0.0858 per 10 turns (saving $0.2792 over DeepSeek V3). For latency-sensitive interactive agents, Google Gemini 2.5 Flash delivers 84ms faster P90 time-to-first-token (235ms vs 319ms).
| Specification / FinOps Dimension | DeepSeek V3 (deepseek/deepseek-v3) | Google Gemini 2.5 Flash (google/gemini-2.5-flash) | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | deepseek/deepseek-v3 | google/gemini-2.5-flash | UMCE 563-Registry Locked |
| 563-Registry & Routing Eligibility | is_known: false | routable: true | is_known: true | routable: true | Both Merkle Verified |
| Standard Uncached Input (/1M tokens) | $1 / 1M | $0.15 / 1M | Google Gemini 2.5 Flash |
| Warm Prefix Cache Read (/1M tokens) | $0.1 / 1M | $0.038 / 1M | Google Gemini 2.5 Flash |
| Standard Output (/1M tokens) | $4 / 1M | $0.6 / 1M | Google Gemini 2.5 Flash |
| Context Window Capacity | 200K Tokens | 200K Tokens | DeepSeek V3 |
| 150K Prompt × 10 Turns (Unpinned Cold + 2K Out) | $1.5800 | $0.2370 | Google Gemini 2.5 Flash |
| 150K × 10 Turns Case A (100% Static Pinned) | $0.3650 (saves $1.2150) | $0.0858 (saves $0.1512) | Google Gemini 2.5 Flash (-$0.2792) |
| 150K × 10 Turns Case B (90% Static + 10% Tail) | $0.4865 (saves $1.0935) | $0.1009 (saves $0.1361) | Google Gemini 2.5 Flash |
| P50 / P90 First-Token Latency | 217ms / 319ms (111 tok/s) | 160ms / 235ms (165 tok/s) | Google Gemini 2.5 Flash (-84ms) |
1. Full-Turn Rate-Card Substitution for DeepSeek V3: At an uncached input rate of $1/1M, output rate of $4/1M, and warm cache read rate of $0.1/1M, running 10 consecutive 150,000-token coding agent turns (with 2,000 output tokens/turn) without prefix pinning costs $1.5800. Locking 100% static prefixes (Case A: 1 cold turn + 9 warm cached turns + 20K total output) reduces 10-turn spend to $0.3650 (saving $1.2150); under a 90% static prefix + 10% dynamic tail workload (Case B), 10-turn spend is $0.4865.
2. Full-Turn Rate-Card Substitution for Google Gemini 2.5 Flash & Winner Verdict: On Google Gemini 2.5 Flash ($0.15/1M input, $0.6/1M output, $0.038/1M warm cache), 10 unpinned 150K turns cost $0.2370, dropping to $0.0858 in Case A and $0.1009 in Case B. Across every 10-turn 150K coding loop (including output tokens), Google Gemini 2.5 Flash delivers an additional $0.2792 Case-A cost advantage.
Production Workload TCO: 25,000 MAU • 50M Tokens/Mo (50% Cache Hit) • 2,000 GB Egress
💡 Optimal FinOps Verdict: Deploying Google Gemini 2.5 Flash saves $52.24/month ($627/year) at 25,000 MAU & 50M monthly tokens (80% input / 20% output split with 50% prefix cache hit rate).