DeepSeek: DeepSeek V3.2 vs Z.ai: GLM 4.7 Flash: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing DeepSeek: DeepSeek V3.2 (deepseek/deepseek-v3.2) vs Z.ai: GLM 4.7 Flash (z-ai/glm-4.7-flash). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
DeepSeek: DeepSeek V3.2 (deepseek/deepseek-v3.2) — Automatic Disk KV Cache ($0.1295/1M) & Off-Peak Promo
DeepSeek-V4 Pro (1.6T MoE) automatically caches repeated 64-token prompt prefixes on NVMe storage at $0.07/1M input tokens (50% off $0.14 base) with zero code changes required, plus off-peak UTC scheduling discounts.
Z.ai: GLM 4.7 Flash (z-ai/glm-4.7-flash) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Z.ai: GLM 4.7 Flash: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.0302/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing DeepSeek: DeepSeek V3.2 (API ID: deepseek/deepseek-v3.2) vs Z.ai: GLM 4.7 Flash (API ID: z-ai/glm-4.7-flash), Z.ai: GLM 4.7 Flash offers lower standard input pricing at $0.0605/1M tokens ($0.4/1M output), while Z.ai: GLM 4.7 Flash leads in cached prefix economics at $0.0302/1M tokens (50% discount). DeepSeek: DeepSeek V3.2 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 | DeepSeek: DeepSeek V3.2 | Z.ai: GLM 4.7 Flash | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | deepseek/deepseek-v3.2 | z-ai/glm-4.7-flash | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.259 / $0.8 | $0.0605 / $0.4 | Z.ai: GLM 4.7 Flash |
| Cache Read Price (per 1M) | $0.1295/1M (50% Off) | $0.0302/1M (50% Off) | Z.ai: GLM 4.7 Flash |
| Context Window / Max Output | 160K In / 144K Out | 195K In / 115K Out | DeepSeek: DeepSeek V3.2 |
| P90 First-Token / Edge Latency | 280ms | 280ms | DeepSeek: DeepSeek V3.2 (-0ms) |
DeepSeek-V3.2 is a large language model designed to harmonize high computational efficiency with strong reasoning and agentic tool-use performance. It introduces DeepSeek Sparse At
As a 30B-class SOTA model, GLM-4.7-Flash offers a new option that balances performance and efficiency. It is further optimized for agentic coding use cases, strengthening coding ca
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 DeepSeek: DeepSeek V3.2 to Z.ai: GLM 4.7 Flash
As a 30B-class SOTA model, GLM-4.7-Flash offers a new option that balances performance and efficiency. It is further optimized for agentic coding use cases, strengthening coding ca Verified P90 latency of 280ms.