Meta: Llama 3.3 70B Instruct vs DeepSeek: DeepSeek V3 0324: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Meta: Llama 3.3 70B Instruct (meta-llama/llama-3.3-70b-instruct) vs DeepSeek: DeepSeek V3 0324 (deepseek/deepseek-chat-v3-0324). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
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.
DeepSeek: DeepSeek V3 0324 (deepseek/deepseek-chat-v3-0324) — Automatic Disk KV Cache ($0.145/1M) & 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.
In Etuki October 2026 FinOps telemetry comparing Meta: Llama 3.3 70B Instruct (API ID: meta-llama/llama-3.3-70b-instruct) vs DeepSeek: DeepSeek V3 0324 (API ID: deepseek/deepseek-chat-v3-0324), DeepSeek: DeepSeek V3 0324 offers lower standard input pricing at $0.29/1M tokens ($1.14/1M output), while DeepSeek: DeepSeek V3 0324 leads in cached prefix economics at $0.145/1M tokens (50% discount). Meta: Llama 3.3 70B Instruct 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 | Meta: Llama 3.3 70B Instruct | DeepSeek: DeepSeek V3 0324 | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | meta-llama/llama-3.3-70b-instruct | deepseek/deepseek-chat-v3-0324 | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.59 / $0.79 | $0.29 / $1.14 | DeepSeek: DeepSeek V3 0324 |
| Cache Read Price (per 1M) | $0.295/1M (50% Off) | $0.145/1M (50% Off) | DeepSeek: DeepSeek V3 0324 |
| Context Window / Max Output | 128K In / 32K Out | 160K In / 113K Out | DeepSeek: DeepSeek V3 0324 |
| P90 First-Token / Edge Latency | 280ms | 280ms | Meta: Llama 3.3 70B Instruct (-0ms) |
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
DeepSeek V3, a 685B-parameter, mixture-of-experts model, is the latest iteration of the flagship chat model family from the DeepSeek team. It succeeds the [DeepSeek V3](/deepseek/d
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 Meta: Llama 3.3 70B Instruct to DeepSeek: DeepSeek V3 0324
DeepSeek V3, a 685B-parameter, mixture-of-experts model, is the latest iteration of the flagship chat model family from the DeepSeek team. It succeeds the [DeepSeek V3](/deepseek/d Verified P90 latency of 280ms.