OpenAI: GPT-3.5 Turbo vs Z.ai: GLM 4.5V: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing OpenAI: GPT-3.5 Turbo (openai/gpt-3.5-turbo) vs Z.ai: GLM 4.5V (z-ai/glm-4.5v). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
OpenAI: GPT-3.5 Turbo (openai/gpt-3.5-turbo) Startup Credits & Batch API 50% Off Promo
OpenAI GPT-6.1 Sol ($2/$10 base rate) qualifies for immediate 75% automatic prefix caching ($0.50/1M), 50% off 24-hour Batch API completions ($1/$5), and up to $150,000 in OpenAI/Azure Foundry credits via Microsoft for Startups Founders Hub (no VC funding required for initial tiers).
Z.ai: GLM 4.5V (z-ai/glm-4.5v) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Z.ai: GLM 4.5V: 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.
In Etuki October 2026 FinOps telemetry comparing OpenAI: GPT-3.5 Turbo (API ID: openai/gpt-3.5-turbo) vs Z.ai: GLM 4.5V (API ID: z-ai/glm-4.5v), OpenAI: GPT-3.5 Turbo offers lower standard input pricing at $0.5/1M tokens ($1.5/1M output), while OpenAI: GPT-3.5 Turbo leads in cached prefix economics at $0.25/1M tokens (50% discount). OpenAI: GPT-3.5 Turbo 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 | OpenAI: GPT-3.5 Turbo | Z.ai: GLM 4.5V | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | openai/gpt-3.5-turbo | z-ai/glm-4.5v | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.5 / $1.5 | $0.6 / $1.8 | OpenAI: GPT-3.5 Turbo |
| Cache Read Price (per 1M) | $0.25/1M (50% Off) | $0.3/1M (50% Off) | OpenAI: GPT-3.5 Turbo |
| Context Window / Max Output | 16K In / 4K Out | 64K In / 16K Out | Z.ai: GLM 4.5V |
| P90 First-Token / Edge Latency | 280ms | 280ms | OpenAI: GPT-3.5 Turbo (-0ms) |
GPT-3.5 Turbo is OpenAI's fastest model. It can understand and generate natural language or code, and is optimized for chat and traditional completion tasks. Training data up to S
GLM-4.5V is a vision-language foundation model for multimodal agent applications. Built on a Mixture-of-Experts (MoE) architecture with 106B parameters and 12B activated parameters
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 OpenAI: GPT-3.5 Turbo to Z.ai: GLM 4.5V
GLM-4.5V is a vision-language foundation model for multimodal agent applications. Built on a Mixture-of-Experts (MoE) architecture with 106B parameters and 12B activated parameters Verified P90 latency of 280ms.