LLM Reference

OpenChat 2

Released
2023-12-28
Last refreshed
2026-04-15
Status
Researched 154d ago

OpenChat 2 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
Specifications
Released
2023-12-28
Context
2k
Parameters
13B
Architecture
Decoder Only
Specialization
general
Training
finetuned
Created by

Human-centered approach to safe AI

N/A
Founded N/A
Website
Pricing

No tracked provider token pricing is available yet.

About

OpenChat 2 is a conversational AI model built on the LLaMA architecture, meticulously fine-tuned using around 80,000 cleaned ShareGPT conversations. It is known for generating human-like responses and effectively engaging in multi-turn dialogues, making it ideal for chatbots and virtual assistants. The model demonstrates strong performance, with an 87.1% win-rate on the AlpacaEval benchmark and a 48.1% win-rate on the MT-bench, showcasing its competitive prowess among open-source models 256. Despite these strengths, OpenChat 2 does have limitations in complex reasoning, mathematical tasks, and programming challenges, sometimes leading to inaccurate information outputs known as "hallucinations" 347.

OpenChat 2 is a model. The structured metadata tracks a 2k-token context window. No headline benchmark score is tracked for OpenChat 2 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.

Rankings & picks(4)