Tencent: Hy4 preview vs Morph: Morph V3 Large: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Tencent: Hy4 preview (tencent/hy4-preview) vs Morph: Morph V3 Large (morph/morph-v3-large). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
Tencent: Hy4 preview (tencent/hy4-preview) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Tencent: Hy4 preview: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.417/1M) or route via asynchronous Batch API for 50% off standard token rates.
Morph: Morph V3 Large (morph/morph-v3-large) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Morph: Morph V3 Large: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.45/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing Tencent: Hy4 preview (API ID: tencent/hy4-preview) vs Morph: Morph V3 Large (API ID: morph/morph-v3-large), Tencent: Hy4 preview offers lower standard input pricing at $0.834/1M tokens ($2.501/1M output), while Tencent: Hy4 preview leads in cached prefix economics at $0.417/1M tokens (50% discount). Tencent: Hy4 preview 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 | Tencent: Hy4 preview | Morph: Morph V3 Large | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | tencent/hy4-preview | morph/morph-v3-large | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.834 / $2.501 | $0.9 / $1.9 | Tencent: Hy4 preview |
| Cache Read Price (per 1M) | $0.417/1M (50% Off) | $0.45/1M (50% Off) | Tencent: Hy4 preview |
| Context Window / Max Output | 1024K In / 63K Out | 256K In / 128K Out | Morph: Morph V3 Large |
| P90 First-Token / Edge Latency | 280ms | 280ms | Tencent: Hy4 preview (-0ms) |
Tencent: Hy4 preview is a mixture-of-experts model from Tencent, with 49B active parameters out of 770B total. It is designed for coding agents, complex tool-use workflows, and pro
Morph's high-accuracy apply model for complex code edits. ~4,500 tokens/sec with 98% accuracy for precise code transformations. The model requires the prompt to be in the following
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 Tencent: Hy4 preview to Morph: Morph V3 Large
Morph's high-accuracy apply model for complex code edits. ~4,500 tokens/sec with 98% accuracy for precise code transformations. The model requires the prompt to be in the following Verified P90 latency of 280ms.