Rank #50
Inference.net: Schematron V2 Turbo
- LLM
- 128k ctx
- 1M
- $0.09
Model · Vendors
Inference.net
Ranked models from this vendor or team on Global rankings (same data snapshot as the main global board).
Board snapshot:
About this vendor
Inference.net is an inference API host that lists third-party and open-weight models on aggregator catalogs such as OpenRouter. On AI Hippo this vendor hub groups Inference.net-tagged SKUs with Global Rankings placement, context metrics, and snapshot token pricing.
Vendor snapshot
Catalog models 2
Ranked on Global board 1
Best rank #50
Price range (avg/1M) $0.09–$0.14/1M
Max context 128k ctx
Model types
Top ranked models
Models on this board · Global rankings
| Rank | Name | Type | Key metric | 1M tokens (avg) |
|---|---|---|---|---|
| 50 | Inference.net: Schematron V2 Turbo | LLM | 128k ctx | $0.09 |
Catalog models (not in ranking)
| Rank | Name | Size | Price | Notes |
|---|---|---|---|---|
| — | Inference.net: Schematron V2 Small | 128k ctx | $0.14/1M | inference-net/schematron-v2-small |
| — | Inference.net: Schematron V2 Turbo | 128k ctx | $0.09/1M | inference-net/schematron-v2-turbo |
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: 2026-09-23. Methodology
FAQ
What is Inference.net's highest-ranked model?
Inference.net: Schematron V2 Turbo currently ranks #50 on AI Hippo's Global rankings board (snapshot 2026-09-23).
What does Inference.net charge per 1M tokens?
Across catalog and ranked rows, blended 1M-token prices range from $0.09 to $0.14 in the latest snapshot (2026-09-23). Check individual model pages for prompt vs completion splits.
How many Inference.net models are ranked vs catalog-only?
1 of 2 catalog models appear on Global rankings; the remaining 1 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/