Flan-UL2
Flan-UL2 is worth evaluating for general LLM work when its provider route and context window match the workload.
Use it for
- Teams evaluating general LLM work
- Workloads that can use a 2k context window
- Buyers comparing 1 tracked provider route
Do not use it for
- Vision or document-understanding workloads
- Strict JSON or tool-calling flows
- Family
- FLAN-UL2
- Released
- 2022-10-20
- Context
- 2k
- Parameters
- 20B
- Architecture
- Decoder Only
- Specialization
- general
- Training
- finetuned
Cheapest of 1 route · IBM watsonx
About
Flan-UL2 is Google DeepMind's FLAN-UL2 model. It was released 2022-10-20.
Flan-UL2 is a model in the FLAN-UL2 family. The structured metadata tracks a 2k-token context window. This page tracks provider routes through IBM watsonx, with the cheapest tracked route listed at $5 input and $5 output per 1M tokens. No headline benchmark score is tracked for Flan-UL2 yet.
Top use-case fit
No primary decision-task fit is mapped for this model yet.
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 | Route |
|---|---|---|---|
| IBM watsonx | $5.00 | $5.00 | Serverless |
Capabilities
No model capability flags are currently sourced.
Benchmark peer barsfor Coding
No task-mapped benchmark peers are available for this model yet.
Migration checks
No linked migration route is available for this model yet.