Qwen: Qwen3 32B vs Tencent: Hy-MT2-1.8B: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Qwen: Qwen3 32B (qwen/qwen3-32b) vs Tencent: Hy-MT2-1.8B (tencent/hy-mt2-1.8b). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
Qwen: Qwen3 32B (qwen/qwen3-32b) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Qwen: Qwen3 32B: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.04/1M) or route via asynchronous Batch API for 50% off standard token rates.
Tencent: Hy-MT2-1.8B (tencent/hy-mt2-1.8b) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Tencent: Hy-MT2-1.8B: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.022/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing Qwen: Qwen3 32B (API ID: qwen/qwen3-32b) vs Tencent: Hy-MT2-1.8B (API ID: tencent/hy-mt2-1.8b), Tencent: Hy-MT2-1.8B offers lower standard input pricing at $0.044/1M tokens ($0.177/1M output), while Tencent: Hy-MT2-1.8B leads in cached prefix economics at $0.022/1M tokens (50% discount). Qwen: Qwen3 32B 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 32B | Tencent: Hy-MT2-1.8B | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | qwen/qwen3-32b | tencent/hy-mt2-1.8b | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.08 / $0.28 | $0.044 / $0.177 | Tencent: Hy-MT2-1.8B |
| Cache Read Price (per 1M) | $0.04/1M (50% Off) | $0.022/1M (50% Off) | Tencent: Hy-MT2-1.8B |
| Context Window / Max Output | 128K In / 16K Out | 8K In / 4K Out | Qwen: Qwen3 32B |
| P90 First-Token / Edge Latency | 280ms | 280ms | Qwen: Qwen3 32B (-0ms) |
Qwen3-32B is a dense 32.8B parameter causal language model from the Qwen3 series, optimized for both complex reasoning and efficient dialogue. It supports seamless switching betwee
Hy-MT2-1.8B is a compact 1.8B-parameter translation model from Tencent. It supports 33 language pairs and five Chinese dialect and minority-language pairs, with workflows for struc
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 32B to Tencent: Hy-MT2-1.8B
Hy-MT2-1.8B is a compact 1.8B-parameter translation model from Tencent. It supports 33 language pairs and five Chinese dialect and minority-language pairs, with workflows for struc Verified P90 latency of 280ms.