OpenChat
OpenChat 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
- OpenChat
- Released
- 2023-11-13
- Context
- 2k
- Parameters
- 13B
- Architecture
- Decoder Only
- Specialization
- general
- Training
- finetuned
No tracked provider token pricing is available yet.
About
OpenChat models are a series of open-source large language models (LLMs) developed for high efficiency, even with minimal training data 4. Built on transformer architecture, they excel in multi-round conversations and are adept at generating high-quality, human-like text 59. These models can engage in dialogues and perform coding tasks, and different versions, like OpenChat 3.5 and 3.6, feature varying parameters to cater to different performance needs 4. Despite their strengths, they share common LLM limitations, including potential for generating inaccurate information and requiring measures to prevent biased outputs. Designed for accessibility, some variants can run on consumer-grade GPUs 4.
OpenChat is a model. The structured metadata tracks a 2k-token context window. No headline benchmark score is tracked for OpenChat 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.