ReMM SLERP 13B vs Z.ai: GLM 5V Turbo: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing ReMM SLERP 13B (undi95/remm-slerp-l2-13b) vs Z.ai: GLM 5V Turbo (z-ai/glm-5v-turbo). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
ReMM SLERP 13B (undi95/remm-slerp-l2-13b) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for ReMM SLERP 13B: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.175/1M) or route via asynchronous Batch API for 50% off standard token rates.
Z.ai: GLM 5V Turbo (z-ai/glm-5v-turbo) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Z.ai: GLM 5V Turbo: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.6/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing ReMM SLERP 13B (API ID: undi95/remm-slerp-l2-13b) vs Z.ai: GLM 5V Turbo (API ID: z-ai/glm-5v-turbo), ReMM SLERP 13B offers lower standard input pricing at $0.35/1M tokens ($0.65/1M output), while ReMM SLERP 13B leads in cached prefix economics at $0.175/1M tokens (50% discount). ReMM SLERP 13B 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 | ReMM SLERP 13B | Z.ai: GLM 5V Turbo | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | undi95/remm-slerp-l2-13b | z-ai/glm-5v-turbo | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.35 / $0.65 | $1.2 / $4 | ReMM SLERP 13B |
| Cache Read Price (per 1M) | $0.175/1M (50% Off) | $0.6/1M (50% Off) | ReMM SLERP 13B |
| Context Window / Max Output | 6K In / 5K Out | 198K In / 128K Out | Z.ai: GLM 5V Turbo |
| P90 First-Token / Edge Latency | 280ms | 280ms | ReMM SLERP 13B (-0ms) |
A recreation trial of the original MythoMax-L2-B13 but with updated models. #merge
GLM-5V-Turbo is Z.ai’s first native multimodal agent foundation model, built for vision-based coding and agent-driven tasks. It natively handles image, video, and text inputs, exce
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 ReMM SLERP 13B to Z.ai: GLM 5V Turbo
GLM-5V-Turbo is Z.ai’s first native multimodal agent foundation model, built for vision-based coding and agent-driven tasks. It natively handles image, video, and text inputs, exce Verified P90 latency of 280ms.