Ling 3.0 Flash Fin
Ling 3.0 Flash Fin is worth evaluating for rag, agents, and long context when its provider route and context window match the workload.
Use it for
- Teams evaluating rag, agents, and long context
- Workloads that can use a 262k context window
- Buyers comparing 1 tracked provider route
Do not use it for
- Vision or document-understanding workloads
InclusionAI is Ant Group's artificial general intelligence research lab, responsible for developing the Ling series of l
Cheapest of 1 route · OpenRouter · cache read $0.012
About
Ling-3.0-flash-Fin is InclusionAI's finance-enhanced fine-tune of Ling-3.0-flash (124B total / 5.1B active, 262K context), trained with financial institutions for source-grounded retrieval, multi-document reasoning, valuation spreadsheets, and research-ready outputs. MIT-licensed weights on Hugging Face (inclusionAI/Ling-3.0-flash-Fin); OpenRouter id inclusionai/ling-3.0-flash-fin.
Top use-case fit: coding, agents, and build tasks
RAG
Included by capability and metadata signals in the decision map.
Agents
Included by capability and metadata signals in the decision map.
Long context
Included by capability and metadata signals in the decision map.
Provider price ladder
Compare API pricing across 1 providers for input and output tokens, batch, and cached reads when available.
| Provider | Input / 1M | Output / 1M | Cache | Route |
|---|---|---|---|---|
| OpenRouter | $0.060 | $0.180 | read $0.012 | Serverless |
Capabilities
Benchmark peer barsfor RAG
No task-mapped benchmark peers are available for this model yet.
Migration checks
No linked migration route is available for this model yet.
InclusionAI is Ant Group's artificial general intelligence research lab, responsible for developing the Ling series of l
Cheapest of 1 route · OpenRouter · cache read $0.012