Microsoft: Phi 4 vs Qwen: Qwen3.8 2.4T A95B: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Microsoft: Phi 4 (microsoft/phi-4) vs Qwen: Qwen3.8 2.4T A95B (qwen/qwen3.8-2.4t-a95b). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
Microsoft: Phi 4 (microsoft/phi-4) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Microsoft: Phi 4: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.035/1M) or route via asynchronous Batch API for 50% off standard token rates.
Qwen: Qwen3.8 2.4T A95B (qwen/qwen3.8-2.4t-a95b) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Qwen: Qwen3.8 2.4T A95B: Activate ephemeral prefix caching to slash input costs by 50% (down to $1/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing Microsoft: Phi 4 (API ID: microsoft/phi-4) vs Qwen: Qwen3.8 2.4T A95B (API ID: qwen/qwen3.8-2.4t-a95b), Microsoft: Phi 4 offers lower standard input pricing at $0.07/1M tokens ($0.14/1M output), while Microsoft: Phi 4 leads in cached prefix economics at $0.035/1M tokens (50% discount). Microsoft: Phi 4 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 | Microsoft: Phi 4 | Qwen: Qwen3.8 2.4T A95B | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | microsoft/phi-4 | qwen/qwen3.8-2.4t-a95b | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.07 / $0.14 | $2 / $6 | Microsoft: Phi 4 |
| Cache Read Price (per 1M) | $0.035/1M (50% Off) | $1/1M (50% Off) | Microsoft: Phi 4 |
| Context Window / Max Output | 16K In / 14K Out | 1024K In / 128K Out | Qwen: Qwen3.8 2.4T A95B |
| P90 First-Token / Edge Latency | 280ms | 280ms | Microsoft: Phi 4 (-0ms) |
[Microsoft Research](/microsoft) Phi-4 is designed to perform well in complex reasoning tasks and can operate efficiently in situations with limited memory or where quick responses
Qwen3.8 2.4T A95B is an open-weight sparse mixture-of-experts model from Qwen and the open-weight variant of [Qwen3.8 Max](/qwen/qwen3.8-max), with 95 billion active parameters out
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 Microsoft: Phi 4 to Qwen: Qwen3.8 2.4T A95B
Qwen3.8 2.4T A95B is an open-weight sparse mixture-of-experts model from Qwen and the open-weight variant of [Qwen3.8 Max](/qwen/qwen3.8-max), with 95 billion active parameters out Verified P90 latency of 280ms.