DeepSeek: DeepSeek Pro Latest vs Meta: Llama 3.3 70B Instruct: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing DeepSeek: DeepSeek Pro Latest (~deepseek/deepseek-pro-latest) vs Meta: Llama 3.3 70B Instruct (meta-llama/llama-3.3-70b-instruct). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
DeepSeek: DeepSeek Pro Latest (~deepseek/deepseek-pro-latest) — Automatic Disk KV Cache ($0.1125/1M) & Off-Peak Promo
DeepSeek-V4 Pro (1.6T MoE) automatically caches repeated 64-token prompt prefixes on NVMe storage at $0.07/1M input tokens (50% off $0.14 base) with zero code changes required, plus off-peak UTC scheduling discounts.
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.
In Etuki October 2026 FinOps telemetry comparing DeepSeek: DeepSeek Pro Latest (API ID: ~deepseek/deepseek-pro-latest) vs Meta: Llama 3.3 70B Instruct (API ID: meta-llama/llama-3.3-70b-instruct), DeepSeek: DeepSeek Pro Latest offers lower standard input pricing at $0.225/1M tokens ($8/1M output), while DeepSeek: DeepSeek Pro Latest leads in cached prefix economics at $0.1125/1M tokens (50% discount). DeepSeek: DeepSeek Pro Latest 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 | DeepSeek: DeepSeek Pro Latest | Meta: Llama 3.3 70B Instruct | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | ~deepseek/deepseek-pro-latest | meta-llama/llama-3.3-70b-instruct | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.225 / $8 | $0.59 / $0.79 | DeepSeek: DeepSeek Pro Latest |
| Cache Read Price (per 1M) | $0.1125/1M (50% Off) | $0.295/1M (50% Off) | DeepSeek: DeepSeek Pro Latest |
| Context Window / Max Output | 1024K In / 384K Out | 128K In / 32K Out | DeepSeek: DeepSeek Pro Latest |
| P90 First-Token / Edge Latency | 280ms | 280ms | DeepSeek: DeepSeek Pro Latest (-0ms) |
This model always redirects to the latest model in the DeepSeek Pro family.
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
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 DeepSeek: DeepSeek Pro Latest to Meta: Llama 3.3 70B Instruct
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 Verified P90 latency of 280ms.