MoonshotAI: Kimi K3.1 Pro vs Alibaba Qwen Qwen Vl Max: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing MoonshotAI: Kimi K3.1 Pro (moonshotai/kimi-k3.1-pro) vs Alibaba Qwen Qwen Vl Max (qwen/qwen-vl-max). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
MoonshotAI: Kimi K3.1 Pro (moonshotai/kimi-k3.1-pro) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for MoonshotAI: Kimi K3.1 Pro: Activate ephemeral prefix caching to slash input costs by 90% (down to 0.2/1M) or route via asynchronous Batch API for 50% off standard token rates.
Alibaba Qwen Qwen Vl Max (qwen/qwen-vl-max) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Alibaba Qwen Qwen Vl Max: Activate ephemeral prefix caching to slash input costs by 90% (down to 0.08/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing MoonshotAI: Kimi K3.1 Pro (API ID: moonshotai/kimi-k3.1-pro) vs Alibaba Qwen Qwen Vl Max (API ID: qwen/qwen-vl-max), Alibaba Qwen Qwen Vl Max offers lower standard input pricing at $0.8/1M tokens ($2.4/1M output), while Alibaba Qwen Qwen Vl Max leads in cached prefix economics at $0.08/1M tokens (90% discount). MoonshotAI: Kimi K3.1 Pro achieves a 0ms faster P90 time-to-first-token latency (195ms vs 195ms).
Gateway-synced rate ($2/$10 per 1M, flat 1049K window). Verify upstream provider cache TTL and regional routing before high-volume batch runs.
Gateway-synced rate ($0.8/$2.4 per 1M, flat 128K window). Verify upstream provider cache TTL and regional routing before high-volume batch runs.
| Specification / FinOps Dimension | MoonshotAI: Kimi K3.1 Pro | Alibaba Qwen Qwen Vl Max | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | moonshotai/kimi-k3.1-pro | qwen/qwen-vl-max | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $2 / $10 | $0.8 / $2.4 | Alibaba Qwen Qwen Vl Max |
| Cache Read Price (per 1M) | $0.2/1M (90% Off) | $0.08/1M (90% Off) | Alibaba Qwen Qwen Vl Max |
| Context Window / Max Output | 1049K In / 64K Out | 128K In / 64K Out | MoonshotAI: Kimi K3.1 Pro |
| P90 First-Token / Edge Latency | 195ms | 195ms | MoonshotAI: Kimi K3.1 Pro (-0ms) |
MoonshotAI: Kimi K3.1 Pro (moonshotai/kimi-k3.1-pro): OpenRouter gateway-synced model at $2/1M input, $10/1M output, $0.2/1M cached input (1049K context window).
Alibaba Qwen Qwen Vl Max (qwen/qwen-vl-max): OpenRouter gateway-synced model at $0.8/1M input, $2.4/1M output, $0.08/1M cached input (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 MoonshotAI: Kimi K3.1 Pro to Alibaba Qwen Qwen Vl Max
Alibaba Qwen Qwen Vl Max (qwen/qwen-vl-max): OpenRouter gateway-synced model at $0.8/1M input, $2.4/1M output, $0.08/1M cached input (128K context window). Verified P90 latency of 195ms.