MoonshotAI: Kimi K3 vs Cohere: Command A: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing MoonshotAI: Kimi K3 (moonshotai/kimi-k3) vs Cohere: Command A (cohere/command-a). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
MoonshotAI: Kimi K3 (moonshotai/kimi-k3) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for MoonshotAI: Kimi K3: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.225/1M) or route via asynchronous Batch API for 50% off standard token rates.
Cohere: Command A (cohere/command-a) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Cohere: Command A: Activate ephemeral prefix caching to slash input costs by 50% (down to $1.25/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing MoonshotAI: Kimi K3 (API ID: moonshotai/kimi-k3) vs Cohere: Command A (API ID: cohere/command-a), MoonshotAI: Kimi K3 offers lower standard input pricing at $0.45/1M tokens ($15/1M output), while MoonshotAI: Kimi K3 leads in cached prefix economics at $0.225/1M tokens (50% discount). MoonshotAI: Kimi K3 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 | MoonshotAI: Kimi K3 | Cohere: Command A | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | moonshotai/kimi-k3 | cohere/command-a | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.45 / $15 | $2.5 / $10 | MoonshotAI: Kimi K3 |
| Cache Read Price (per 1M) | $0.225/1M (50% Off) | $1.25/1M (50% Off) | MoonshotAI: Kimi K3 |
| Context Window / Max Output | 1024K In / 922K Out | 250K In / 8K Out | MoonshotAI: Kimi K3 |
| P90 First-Token / Edge Latency | 280ms | 280ms | MoonshotAI: Kimi K3 (-0ms) |
Kimi K3 is a 2.8T parameter open-weight multimodal reasoning model from Moonshot AI. It is suited for complex coding, knowledge work, and long-horizon agentic workflows, and is par
Command A is an open-weights 111B parameter model with a 256k context window focused on delivering great performance across agentic, multilingual, and coding use cases. Compared to
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 MoonshotAI: Kimi K3 to Cohere: Command A
Command A is an open-weights 111B parameter model with a 256k context window focused on delivering great performance across agentic, multilingual, and coding use cases. Compared to Verified P90 latency of 280ms.