LiquidAI: LFM2.5-24B-A2B vs Qwen: Qwen3.8 2.4T A95B: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing LiquidAI: LFM2.5-24B-A2B (liquid/lfm-2.5-24b-a2b) vs Qwen: Qwen3.8 2.4T A95B (qwen/qwen3.8-2.4t-a95b). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
LiquidAI: LFM2.5-24B-A2B (liquid/lfm-2.5-24b-a2b) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for LiquidAI: LFM2.5-24B-A2B: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.025/1M) or route via asynchronous Batch API for 50% off standard token rates.
Qwen: Qwen3.8 2.4T A95B (qwen/qwen3.8-2.4t-a95b) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Qwen: Qwen3.8 2.4T A95B: Activate ephemeral prefix caching to slash input costs by 50% (down to $1/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing LiquidAI: LFM2.5-24B-A2B (API ID: liquid/lfm-2.5-24b-a2b) vs Qwen: Qwen3.8 2.4T A95B (API ID: qwen/qwen3.8-2.4t-a95b), LiquidAI: LFM2.5-24B-A2B offers lower standard input pricing at $0.05/1M tokens ($0.7/1M output), while LiquidAI: LFM2.5-24B-A2B leads in cached prefix economics at $0.025/1M tokens (50% discount). LiquidAI: LFM2.5-24B-A2B 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: LFM2.5-24B-A2B | Qwen: Qwen3.8 2.4T A95B | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | liquid/lfm-2.5-24b-a2b | qwen/qwen3.8-2.4t-a95b | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.05 / $0.7 | $2 / $6 | LiquidAI: LFM2.5-24B-A2B |
| Cache Read Price (per 1M) | $0.025/1M (50% Off) | $1/1M (50% Off) | LiquidAI: LFM2.5-24B-A2B |
| Context Window / Max Output | 125K In / 8K Out | 1024K In / 128K Out | Qwen: Qwen3.8 2.4T A95B |
| P90 First-Token / Edge Latency | 280ms | 280ms | LiquidAI: LFM2.5-24B-A2B (-0ms) |
LFM2.5-24B-A2B is a mixture-of-experts reasoning model from Liquid AI with 24B total and 2.45B active parameters. It always reasons before answering and is built for agents that ca
Qwen3.8 2.4T A95B is an open-weight sparse mixture-of-experts model from Qwen and the open-weight variant of [Qwen3.8 Max](/qwen/qwen3.8-max), with 95 billion active parameters out
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: LFM2.5-24B-A2B to Qwen: Qwen3.8 2.4T A95B
Qwen3.8 2.4T A95B is an open-weight sparse mixture-of-experts model from Qwen and the open-weight variant of [Qwen3.8 Max](/qwen/qwen3.8-max), with 95 billion active parameters out Verified P90 latency of 280ms.