Meta: Llama 4 Maverick vs Z.ai: GLM Latest: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Meta: Llama 4 Maverick (meta-llama/llama-4-maverick) vs Z.ai: GLM Latest (~z-ai/glm-latest). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
Meta: Llama 4 Maverick (meta-llama/llama-4-maverick) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Meta: Llama 4 Maverick: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.0938/1M) or route via asynchronous Batch API for 50% off standard token rates.
Z.ai: GLM Latest (~z-ai/glm-latest) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Z.ai: GLM Latest: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.012/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing Meta: Llama 4 Maverick (API ID: meta-llama/llama-4-maverick) vs Z.ai: GLM Latest (API ID: ~z-ai/glm-latest), Z.ai: GLM Latest offers lower standard input pricing at $0.024/1M tokens ($4.4/1M output), while Z.ai: GLM Latest leads in cached prefix economics at $0.012/1M tokens (50% discount). Meta: Llama 4 Maverick 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 | Meta: Llama 4 Maverick | Z.ai: GLM Latest | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | meta-llama/llama-4-maverick | ~z-ai/glm-latest | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.1875 / $0.6525 | $0.024 / $4.4 | Z.ai: GLM Latest |
| Cache Read Price (per 1M) | $0.0938/1M (50% Off) | $0.012/1M (50% Off) | Z.ai: GLM Latest |
| Context Window / Max Output | 1024K In / 16K Out | 1024K In / 128K Out | Z.ai: GLM Latest |
| P90 First-Token / Edge Latency | 280ms | 280ms | Meta: Llama 4 Maverick (-0ms) |
Llama 4 Maverick 17B Instruct (128E) is a high-capacity multimodal language model from Meta, built on a mixture-of-experts (MoE) architecture with 128 experts and 17 billion active
This model always redirects to the latest GLM model from Z.ai.
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 Meta: Llama 4 Maverick to Z.ai: GLM Latest
This model always redirects to the latest GLM model from Z.ai. Verified P90 latency of 280ms.