What are the differences?
Between the Starling LM 7B Beta and GPT-3.5 Turbo 16K LLM models, which follows best instructions?
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Starling LM 7B Beta
Berkeley Nest
GPT-3.5 Turbo 16K
OpenAI
Overview
|  Starling LM 7B Beta | GPT-3.5 Turbo 16K | |
|---|---|---|
| Provider Organization responsible for this model. |  Berkeley Nest | OpenAI | 
| Input Context Window The total number of tokens that the input context window can accommodate. | 3.1K | 16K | 
| Maximum Output Tokens The maximum number of tokens this model can produce in one operation. | 4.1K | 16K | 
| Release Date The initial release date of the model. | November 15, 2023 24 months ago | June 13, 2023 29 months ago | 
| Knowledge Cutoff The latest date for which the information provided is considered reliable and current. | 2024/3 | 
Pricing
|  Starling LM 7B Beta | GPT-3.5 Turbo 16K | |
|---|---|---|
| Input Costs associated with the data input to the model. | Not specified. | $0.00 | 
| Output Costs associated with the tokens produced by the model. | Not specified. | $0.00 | 
Benchmark
|  Starling LM 7B Beta | GPT-3.5 Turbo 16K | |
|---|---|---|
| MMLU Assesses LLMs' ability to acquire knowledge in zero-shot and few-shot scenarios. | 63.9 | |
| MMMU Comprehensive benchmark covering multiple disciplines and modalities. | ||
| HellaSwag A demanding benchmark for sentence completion tasks. | ||
| Arena Elo Ranking metric for LMSYS Chatbot Arena. | 1119 | 
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1-line Integration
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Chat Replays
Analytics
Topic Classification
Agent Tracing
Custom Dashboards
Score LLM responses
PII Masking
Feedback Tracking
Open Source
Self Hostable
1-line Integration
Prompt Templates
Chat Replays
Analytics
Topic Classification
Agent Tracing
Custom Dashboards
Score LLM responses
PII Masking
Feedback Tracking




