Rank #57
LiquidAI: LFM2.5-24B-A2B
- LLM
- 128k ctx
- 1M
- $0.38
Model · Vendors
LiquidAI
Ranked models from this vendor or team on Global rankings (same data snapshot as the main global board).
Board snapshot:
About this vendor
Liquid AI (Liquid Foundation Models / LFM) publishes efficient open-weight language models aimed at on-device and edge inference, listed on aggregator catalogs such as OpenRouter. On AI Hippo this vendor hub groups Liquid-tagged SKUs with Global Rankings placement, context metrics, and snapshot token pricing.
Vendor snapshot
Catalog models 3
Ranked on Global board 1
Best rank #57
Price range (avg/1M) $0.38–$0.42/1M
Max context 128k ctx
Model types
Top ranked models
Models on this board · Global rankings
| Rank | Name | Type | Key metric | 1M tokens (avg) |
|---|---|---|---|---|
| 57 | LiquidAI: LFM2.5-24B-A2B | LLM | 128k ctx | $0.38 |
Catalog models (not in ranking)
| Rank | Name | Size | Price | Notes |
|---|---|---|---|---|
| — | LiquidAI: LFM2.5-2.6B | 128k ctx | $0.42/1M | liquid/lfm-2.5-2.6b |
| — | LiquidAI: LFM2.5-2.6B (free) | 66k ctx | $0.00/1M | liquid/lfm-2.5-2.6b:free |
| — | LiquidAI: LFM2.5-24B-A2B | 128k ctx | $0.38/1M | liquid/lfm-2.5-24b-a2b |
Data sources & methodology
Counts and prices come from the OpenRouter catalog snapshot merged with AI Hippo Global rankings (same snapshot as /rankings/). Rank reflects the composite score on that board—not LMSYS Chatbot Arena ELO. Snapshot date: 2026-11-02. Methodology
FAQ
What is LiquidAI's highest-ranked model?
LiquidAI: LFM2.5-24B-A2B currently ranks #57 on AI Hippo's Global rankings board (snapshot 2026-11-02).
What does LiquidAI charge per 1M tokens?
Across catalog and ranked rows, blended 1M-token prices range from $0.38 to $0.42 in the latest snapshot (2026-11-02). Check individual model pages for prompt vs completion splits.
How many LiquidAI models are ranked vs catalog-only?
1 of 3 catalog models appear on Global rankings; the remaining 2 are listed under catalog-only on this page.
How is the Global rankings score calculated?
Global rankings uses on-site weighting (context window first, then blended 1M-token price)—not third-party ELO. Full methodology: /en/methodology/