LG EXAONE Exaone 3.5 7.8B Instruct vs OpenAI GPT-5.4 nano: Live Promos, Pricing, Hidden Fees & Latency
LG EXAONE Exaone 3.5 7.8B Instruct (lgai-exaone/exaone-3.5-7.8b-instruct) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for LG EXAONE Exaone 3.5 7.8B Instruct: Activate ephemeral prefix caching to slash input costs by 90% (down to 0.004/1M) or route via asynchronous Batch API for 50% off standard token rates.
OpenAI GPT-5.4 nano (gpt-5.4-nano) Startup Credits & Batch API 50% Off Promo
OpenAI GPT-6.1 Sol ($2/$10 base rate) qualifies for immediate 95% automatic prefix caching ($0.10/1M), 50% off 24-hour Batch API completions ($1/$5), and up to $150,000 in OpenAI/Azure Foundry credits via Microsoft for Startups Founders Hub (no VC funding required for initial tiers).
In Etuki October 2026 FinOps telemetry comparing LG EXAONE Exaone 3.5 7.8B Instruct (API ID: lgai-exaone/exaone-3.5-7.8b-instruct) vs OpenAI GPT-5.4 nano (API ID: gpt-5.4-nano), LG EXAONE Exaone 3.5 7.8B Instruct offers lower standard input pricing at $0.04/1M tokens ($0.12/1M output), while LG EXAONE Exaone 3.5 7.8B Instruct leads in cached prefix economics at $0.004/1M tokens (90% discount). OpenAI GPT-5.4 nano achieves a 85ms faster P90 time-to-first-token latency (110ms vs 195ms).
Gateway-synced rate ($0.04/$0.12 per 1M, flat 128K window). Verify upstream provider cache TTL and regional routing before high-volume batch runs.
Enable Prompt Context Caching & Batch API to reduce repeated system prompt input token burn by 50%-97.5%.
| Specification / FinOps Dimension | LG EXAONE Exaone 3.5 7.8B Instruct | OpenAI GPT-5.4 nano | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | lgai-exaone/exaone-3.5-7.8b-instruct | gpt-5.4-nano | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.04 / $0.12 | $0.2 / $1.25 | LG EXAONE Exaone 3.5 7.8B Instruct |
| Cache Read Price (per 1M) | $0.004/1M (90% Off) | $0.02/1M (90% Off) | LG EXAONE Exaone 3.5 7.8B Instruct |
| Context Window / Max Output | 128K In / 64K Out | 128K In / 128K Out | OpenAI GPT-5.4 nano |
| P90 First-Token / Edge Latency | 195ms | 110ms | OpenAI GPT-5.4 nano (-85ms) |
LG EXAONE Exaone 3.5 7.8B Instruct (lgai-exaone/exaone-3.5-7.8b-instruct): OpenRouter gateway-synced model at $0.04/1M input, $0.12/1M output, $0.004/1M cached input (128K context window).
OpenAI GPT-5.4 nano high-throughput classification & routing model ($0.20/$1.25 per 1M, Official Cache Read $0.02/1M [90% Off], 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 3.5 7.8B Instruct to OpenAI GPT-5.4 nano
OpenAI GPT-5.4 nano high-throughput classification & routing model ($0.20/$1.25 per 1M, Official Cache Read $0.02/1M [90% Off], 128K context window). Verified P90 latency of 110ms.