Qwen: Qwen3.7 Max vs MoonshotAI: Kimi K3 (batch): Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Qwen: Qwen3.7 Max (qwen/qwen3.7-max) vs MoonshotAI: Kimi K3 (batch) (moonshotai/kimi-k3:batch). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
Qwen: Qwen3.7 Max (qwen/qwen3.7-max) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Qwen: Qwen3.7 Max: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.7375/1M) or route via asynchronous Batch API for 50% off standard token rates.
MoonshotAI: Kimi K3 (batch) (moonshotai/kimi-k3:batch) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for MoonshotAI: Kimi K3 (batch): Activate ephemeral prefix caching to slash input costs by 50% (down to $1.14/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing Qwen: Qwen3.7 Max (API ID: qwen/qwen3.7-max) vs MoonshotAI: Kimi K3 (batch) (API ID: moonshotai/kimi-k3:batch), Qwen: Qwen3.7 Max offers lower standard input pricing at $1.475/1M tokens ($4.425/1M output), while Qwen: Qwen3.7 Max leads in cached prefix economics at $0.7375/1M tokens (50% discount). Qwen: Qwen3.7 Max 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 | Qwen: Qwen3.7 Max | MoonshotAI: Kimi K3 (batch) | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | qwen/qwen3.7-max | moonshotai/kimi-k3:batch | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $1.475 / $4.425 | $2.28 / $11.4 | Qwen: Qwen3.7 Max |
| Cache Read Price (per 1M) | $0.7375/1M (50% Off) | $1.14/1M (50% Off) | Qwen: Qwen3.7 Max |
| Context Window / Max Output | 977K In / 128K Out | 1024K In / 16K Out | Qwen: Qwen3.7 Max |
| P90 First-Token / Edge Latency | 280ms | 280ms | Qwen: Qwen3.7 Max (-0ms) |
Qwen3.7-Max is the flagship model in Alibaba's Qwen3.7 series. It supports text input and output and is designed for agent-centric workloads, with particular strengths in coding, o
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
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 Qwen: Qwen3.7 Max to MoonshotAI: Kimi K3 (batch)
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 Verified P90 latency of 280ms.