Meta: Llama 3.3 70B Instruct vs Sao10K: Llama 3 8B Lunaris: 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 Sao10K: Llama 3 8B Lunaris (sao10k/l3-lunaris-8b). 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.
Sao10K: Llama 3 8B Lunaris (sao10k/l3-lunaris-8b) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Sao10K: Llama 3 8B Lunaris: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.02/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing Meta: Llama 3.3 70B Instruct (API ID: meta-llama/llama-3.3-70b-instruct) vs Sao10K: Llama 3 8B Lunaris (API ID: sao10k/l3-lunaris-8b), Sao10K: Llama 3 8B Lunaris offers lower standard input pricing at $0.04/1M tokens ($0.05/1M output), while Sao10K: Llama 3 8B Lunaris leads in cached prefix economics at $0.02/1M 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 | Sao10K: Llama 3 8B Lunaris | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | meta-llama/llama-3.3-70b-instruct | sao10k/l3-lunaris-8b | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.59 / $0.79 | $0.04 / $0.05 | Sao10K: Llama 3 8B Lunaris |
| Cache Read Price (per 1M) | $0.295/1M (50% Off) | $0.02/1M (50% Off) | Sao10K: Llama 3 8B Lunaris |
| Context Window / Max Output | 128K In / 32K Out | 8K In / 7K Out | Meta: Llama 3.3 70B Instruct |
| 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
Lunaris 8B is a versatile generalist and roleplaying model based on Llama 3. It's a strategic merge of multiple models, designed to balance creativity with improved logic and gener
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 Sao10K: Llama 3 8B Lunaris
Lunaris 8B is a versatile generalist and roleplaying model based on Llama 3. It's a strategic merge of multiple models, designed to balance creativity with improved logic and gener Verified P90 latency of 280ms.