LG EXAONE Exaone 3.5 7.8B Instruct vs 01.AI Yi Vision: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing LG EXAONE Exaone 3.5 7.8B Instruct (lgai-exaone/exaone-3.5-7.8b-instruct) vs 01.AI Yi Vision (01-ai/yi-vision). Simulate cache read multipliers, context cliffs, MAU bills, and P90 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.
01.AI Yi Vision (01-ai/yi-vision) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for 01.AI Yi Vision: Activate ephemeral prefix caching to slash input costs by 90% (down to 0.03/1M) or route via asynchronous Batch API for 50% off standard token rates.
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 01.AI Yi Vision (API ID: 01-ai/yi-vision), 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). LG EXAONE Exaone 3.5 7.8B Instruct achieves a 0ms faster P90 time-to-first-token latency (195ms 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.
Gateway-synced rate ($0.3/$0.6 per 1M, flat 32K window). Verify upstream provider cache TTL and regional routing before high-volume batch runs.
| Specification / FinOps Dimension | LG EXAONE Exaone 3.5 7.8B Instruct | 01.AI Yi Vision | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | lgai-exaone/exaone-3.5-7.8b-instruct | 01-ai/yi-vision | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.04 / $0.12 | $0.3 / $0.6 | LG EXAONE Exaone 3.5 7.8B Instruct |
| Cache Read Price (per 1M) | $0.004/1M (90% Off) | $0.03/1M (90% Off) | LG EXAONE Exaone 3.5 7.8B Instruct |
| Context Window / Max Output | 128K In / 64K Out | 32K In / 64K Out | LG EXAONE Exaone 3.5 7.8B Instruct |
| P90 First-Token / Edge Latency | 195ms | 195ms | LG EXAONE Exaone 3.5 7.8B Instruct (-0ms) |
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).
01.AI Yi Vision (01-ai/yi-vision): OpenRouter gateway-synced model at $0.3/1M input, $0.6/1M output, $0.03/1M cached input (32K 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 01.AI Yi Vision
01.AI Yi Vision (01-ai/yi-vision): OpenRouter gateway-synced model at $0.3/1M input, $0.6/1M output, $0.03/1M cached input (32K context window). Verified P90 latency of 195ms.