Pythia 31M
Pythia 31M has model metadata, but missing tracked provider pricing keeps it from being a default production pick.
Use it for
- Teams evaluating general LLM work
- Workloads that can use a 2k context window
Do not use it for
- Cost-sensitive launches that need sourced token pricing
- Vision or document-understanding workloads
- Strict JSON or tool-calling flows
- Family
- Pythia
- Released
- 2023-05-31
- Context
- 2k
- Parameters
- 31M
- Architecture
- Decoder Only
- Knowledge cutoff
- 2020-03
- Specialization
- general
- Training
- finetuned
No tracked provider token pricing is available yet.
About
Pythia 31M is an open-source large language model developed by EleutherAI, designed as part of a suite to explore interpretability, learning dynamics, and ethics in LLMs. This model employs the GPT-NeoXForCausalLM architecture with 30.5 million parameters and a context length of 2048 tokens. Trained from random weights associated with the Pythia series, it has several variants; these versions are based on different datasets such as SimpleWiki, SimplePile Lite, and GoodWiki. The model primarily focuses on text generation, with varying performances across different benchmarks compared to more extensive models like GPT-4. However, limitations include insufficient activity for serverless API deployment, and there is a noted lack of extensive documentation on its uses, training methods, and evaluation, hindering a thorough understanding of its full potential.
Pythia 31M is a model in the Pythia family. The structured metadata tracks a 2k-token context window. No headline benchmark score is tracked for Pythia 31M yet.
Top use-case fit
No primary decision-task fit is mapped for this model yet.
Provider price ladder
No tracked provider token pricing is available for this model yet.
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.