MoonshotAI: Kimi K2 Thinking vs Qwen: Qwen3 VL 235B A22B Instruct: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing MoonshotAI: Kimi K2 Thinking (moonshotai/kimi-k2-thinking) vs Qwen: Qwen3 VL 235B A22B Instruct (qwen/qwen3-vl-235b-a22b-instruct). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
MoonshotAI: Kimi K2 Thinking (moonshotai/kimi-k2-thinking) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for MoonshotAI: Kimi K2 Thinking: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.3/1M) or route via asynchronous Batch API for 50% off standard token rates.
Qwen: Qwen3 VL 235B A22B Instruct (qwen/qwen3-vl-235b-a22b-instruct) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Qwen: Qwen3 VL 235B A22B Instruct: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.105/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing MoonshotAI: Kimi K2 Thinking (API ID: moonshotai/kimi-k2-thinking) vs Qwen: Qwen3 VL 235B A22B Instruct (API ID: qwen/qwen3-vl-235b-a22b-instruct), Qwen: Qwen3 VL 235B A22B Instruct offers lower standard input pricing at $0.21/1M tokens ($1.9/1M output), while Qwen: Qwen3 VL 235B A22B Instruct leads in cached prefix economics at $0.105/1M tokens (50% discount). MoonshotAI: Kimi K2 Thinking 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 K2 Thinking | Qwen: Qwen3 VL 235B A22B Instruct | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | moonshotai/kimi-k2-thinking | qwen/qwen3-vl-235b-a22b-instruct | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.6 / $2.5 | $0.21 / $1.9 | Qwen: Qwen3 VL 235B A22B Instruct |
| Cache Read Price (per 1M) | $0.3/1M (50% Off) | $0.105/1M (50% Off) | Qwen: Qwen3 VL 235B A22B Instruct |
| Context Window / Max Output | 256K In / 96K Out | 256K In / 32K Out | MoonshotAI: Kimi K2 Thinking |
| P90 First-Token / Edge Latency | 280ms | 280ms | MoonshotAI: Kimi K2 Thinking (-0ms) |
Kimi K2 Thinking is Moonshot AI’s most advanced open reasoning model to date, extending the K2 series into agentic, long-horizon reasoning. Built on the trillion-parameter Mixture-
Qwen3-VL-235B-A22B Instruct is an open-weight multimodal model that unifies strong text generation with visual understanding across images and video. The Instruct model targets gen
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 K2 Thinking to Qwen: Qwen3 VL 235B A22B Instruct
Qwen3-VL-235B-A22B Instruct is an open-weight multimodal model that unifies strong text generation with visual understanding across images and video. The Instruct model targets gen Verified P90 latency of 280ms.