LLM Reference

Flan-UL2 on IBM Watsonx

Released
2022-10-20
Last refreshed
2026-05-22
Status
Researched 27d ago
Open sourceCommercial use: permitted

Flan-UL2 on IBM Watsonx 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
Specifications
Family
FLAN-UL2
Released
2022-10-20
Context
2k
Parameters
20B
Architecture
Decoder Only
Specialization
general
Openness
Open source
License
Apache 2.0OSI-approvedCommercial use: permitted
Created by

Pioneering artificial intelligence research.

London, United Kingdom
Founded 2014
Website
Pricing
Output / 1M
$0.185
Input / 1M
$0.185

Cheapest of 1 route · IBM watsonx

About

Flan-UL2 on IBM Watsonx is Google DeepMind's FLAN-UL2 model. Weights are openly available for self-hosting.

Flan-UL2 on IBM Watsonx is an open-source 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 $0.185 input and $0.185 output per 1M tokens. No headline benchmark score is tracked for Flan-UL2 on IBM Watsonx 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.

ProviderInput / 1MOutput / 1MRoute
IBM watsonx$0.185$0.185
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.