AionLabs: Aion 3.5 vs MoonshotAI: Kimi K2 0711: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing AionLabs: Aion 3.5 (aion-labs/aion-3.5) vs MoonshotAI: Kimi K2 0711 (moonshotai/kimi-k2). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
AionLabs: Aion 3.5 (aion-labs/aion-3.5) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for AionLabs: Aion 3.5: Activate ephemeral prefix caching to slash input costs by 50% (down to $1.5/1M) or route via asynchronous Batch API for 50% off standard token rates.
MoonshotAI: Kimi K2 0711 (moonshotai/kimi-k2) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for MoonshotAI: Kimi K2 0711: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.285/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing AionLabs: Aion 3.5 (API ID: aion-labs/aion-3.5) vs MoonshotAI: Kimi K2 0711 (API ID: moonshotai/kimi-k2), MoonshotAI: Kimi K2 0711 offers lower standard input pricing at $0.57/1M tokens ($2.3/1M output), while MoonshotAI: Kimi K2 0711 leads in cached prefix economics at $0.285/1M tokens (50% discount). AionLabs: Aion 3.5 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 | AionLabs: Aion 3.5 | MoonshotAI: Kimi K2 0711 | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | aion-labs/aion-3.5 | moonshotai/kimi-k2 | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $3 / $6 | $0.57 / $2.3 | MoonshotAI: Kimi K2 0711 |
| Cache Read Price (per 1M) | $1.5/1M (50% Off) | $0.285/1M (50% Off) | MoonshotAI: Kimi K2 0711 |
| Context Window / Max Output | 256K In / 32K Out | 128K In / 96K Out | MoonshotAI: Kimi K2 0711 |
| P90 First-Token / Edge Latency | 280ms | 280ms | AionLabs: Aion 3.5 (-0ms) |
Aion 3.5 is a multi-model roleplaying and storytelling system from AionLabs, built on the GLM family of models. It uses a collaborative generation process in which multiple special
Kimi K2 Instruct is a large-scale Mixture-of-Experts (MoE) language model developed by Moonshot AI, featuring 1 trillion total parameters with 32 billion active per forward pass. I
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 AionLabs: Aion 3.5 to MoonshotAI: Kimi K2 0711
Kimi K2 Instruct is a large-scale Mixture-of-Experts (MoE) language model developed by Moonshot AI, featuring 1 trillion total parameters with 32 billion active per forward pass. I Verified P90 latency of 280ms.