LG EXAONE Exaone Deep 7.8B vs Meta Llama Llama 3.1 70B Instruct Fp8: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing LG EXAONE Exaone Deep 7.8B (lgai-exaone/exaone-deep-7.8b) vs Meta Llama Llama 3.1 70B Instruct Fp8 (meta-llama/llama-3.1-70b-instruct-fp8). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
LG EXAONE Exaone Deep 7.8B (lgai-exaone/exaone-deep-7.8b) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for LG EXAONE Exaone Deep 7.8B: Activate ephemeral prefix caching to slash input costs by 90% (down to 0.005/1M) or route via asynchronous Batch API for 50% off standard token rates.
Meta Llama Llama 3.1 70B Instruct Fp8 (meta-llama/llama-3.1-70b-instruct-fp8) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Meta Llama Llama 3.1 70B Instruct Fp8: Activate ephemeral prefix caching to slash input costs by 90% (down to 0.02/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing LG EXAONE Exaone Deep 7.8B (API ID: lgai-exaone/exaone-deep-7.8b) vs Meta Llama Llama 3.1 70B Instruct Fp8 (API ID: meta-llama/llama-3.1-70b-instruct-fp8), LG EXAONE Exaone Deep 7.8B offers lower standard input pricing at $0.05/1M tokens ($0.15/1M output), while LG EXAONE Exaone Deep 7.8B leads in cached prefix economics at $0.005/1M tokens (90% discount). LG EXAONE Exaone Deep 7.8B achieves a 0ms faster P90 time-to-first-token latency (195ms vs 195ms).
Gateway-synced rate ($0.05/$0.15 per 1M, flat 128K window). Verify upstream provider cache TTL and regional routing before high-volume batch runs.
Gateway-synced rate ($0.2/$0.35 per 1M, flat 128K window). Verify upstream provider cache TTL and regional routing before high-volume batch runs.
| Specification / FinOps Dimension | LG EXAONE Exaone Deep 7.8B | Meta Llama Llama 3.1 70B Instruct Fp8 | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | lgai-exaone/exaone-deep-7.8b | meta-llama/llama-3.1-70b-instruct-fp8 | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.05 / $0.15 | $0.2 / $0.35 | LG EXAONE Exaone Deep 7.8B |
| Cache Read Price (per 1M) | $0.005/1M (90% Off) | $0.02/1M (90% Off) | LG EXAONE Exaone Deep 7.8B |
| Context Window / Max Output | 128K In / 64K Out | 128K In / 64K Out | LG EXAONE Exaone Deep 7.8B |
| P90 First-Token / Edge Latency | 195ms | 195ms | LG EXAONE Exaone Deep 7.8B (-0ms) |
LG EXAONE Exaone Deep 7.8B (lgai-exaone/exaone-deep-7.8b): OpenRouter gateway-synced model at $0.05/1M input, $0.15/1M output, $0.005/1M cached input (128K context window).
Meta Llama Llama 3.1 70B Instruct Fp8
API ID: meta-llama/llama-3.1-70b-instruct-fp8 • OpenRouter SyncedMeta Llama Llama 3.1 70B Instruct Fp8 (meta-llama/llama-3.1-70b-instruct-fp8): OpenRouter gateway-synced model at $0.2/1M input, $0.35/1M output, $0.02/1M cached input (128K context window).
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 LG EXAONE Exaone Deep 7.8B to Meta Llama Llama 3.1 70B Instruct Fp8
Meta Llama Llama 3.1 70B Instruct Fp8 (meta-llama/llama-3.1-70b-instruct-fp8): OpenRouter gateway-synced model at $0.2/1M input, $0.35/1M output, $0.02/1M cached input (128K context window). Verified P90 latency of 195ms.