LiquidAI: LFM2.5-2.6B (free) vs Z.ai: GLM 5.3: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing LiquidAI: LFM2.5-2.6B (free) (liquid/lfm-2.5-2.6b:free) vs Z.ai: GLM 5.3 (z-ai/glm-5.3). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
LiquidAI: LFM2.5-2.6B (free) (liquid/lfm-2.5-2.6b:free) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for LiquidAI: LFM2.5-2.6B (free): Activate ephemeral prefix caching to slash input costs by 50% (down to $0/1M) or route via asynchronous Batch API for 50% off standard token rates.
Z.ai: GLM 5.3 (z-ai/glm-5.3) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Z.ai: GLM 5.3: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.055/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing LiquidAI: LFM2.5-2.6B (free) (API ID: liquid/lfm-2.5-2.6b:free) vs Z.ai: GLM 5.3 (API ID: z-ai/glm-5.3), LiquidAI: LFM2.5-2.6B (free) offers lower standard input pricing at $0/1M tokens ($0/1M output), while LiquidAI: LFM2.5-2.6B (free) leads in cached prefix economics at $0/1M tokens (50% discount). LiquidAI: LFM2.5-2.6B (free) 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 | LiquidAI: LFM2.5-2.6B (free) | Z.ai: GLM 5.3 | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | liquid/lfm-2.5-2.6b:free | z-ai/glm-5.3 | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0 / $0 | $0.11 / $4.8 | LiquidAI: LFM2.5-2.6B (free) |
| Cache Read Price (per 1M) | $0/1M (50% Off) | $0.055/1M (50% Off) | LiquidAI: LFM2.5-2.6B (free) |
| Context Window / Max Output | 64K In / 8K Out | 1024K In / 922K Out | Z.ai: GLM 5.3 |
| P90 First-Token / Edge Latency | 280ms | 280ms | LiquidAI: LFM2.5-2.6B (free) (-0ms) |
LFM2.5-2.6B is a compact reasoning model from Liquid AI. It is suited for agent workflows, data extraction, RAG, and long-context processing. Liquid advises against using it for ag
GLM-5.3 is a large-scale reasoning model from Z.ai, built for complex software engineering and long-horizon agent tasks. It supports text input and output with a 1M-token context w
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 LiquidAI: LFM2.5-2.6B (free) to Z.ai: GLM 5.3
GLM-5.3 is a large-scale reasoning model from Z.ai, built for complex software engineering and long-horizon agent tasks. It supports text input and output with a 1M-token context w Verified P90 latency of 280ms.