[whatmodel.sh](../../README.md) / MPT-30B-Chat # MPT-30B-Chat MosaicML · released 2023-06 · 30B params · cc-by-nc-sa-4.0 **score 37.7** ±1.9 · comparison only: no current run option verified · from 3 benchmark results across 3 sources Score within the [LMArena (text)](https://whatmodel.sh/?set=lmarena-text&score=set) comparison set only. ## What it's good at ● marks MPT-30B-Chat among every model on that task or test, worst to best. 
task            vs the others         rank  counts  tests
chat & writing  ▁▁▁▃●▄▇█▇▇▇▃   #423 of 474     98%      3
chat & writing · #423 of 474 · 98% of its score Beats [Code Llama 70B Instruct](codellama-70b-instruct.md), [Gemma 4 E2B](gemma-4-e2b.md), [Phi-3-mini-4k-instruct (June 2024 update)](phi-3-mini-4k-instruct-june-2024.md) here, though they rank higher overall. Trails [Gemma 3 270M IT](gemma-3-270m.md), [SmolLM2 360M Instruct](smollm2-360m.md), [Granite 4.0 H 350M](granite-4-0-h-350m.md) here, though they rank lower overall. 
test                                                      result  vs the others in its run   difficulty                counts  why
LMArena (text)                                            1150.8  ▁▁▁▂●▃▃▆▆▇█▃ beats 40/385  avg 1260                     37%  blunt
Polyrating rating (bias-aware re-…                        1041.0  ▂▁▂▁▃●█▆▇▄▂▂ beats 23/95   avg 1187                     34%  typical
MT-Bench (GPT-4 single-answer gra…  6.3900 MT-Bench score (1-10)  ▆▂▂▆▆▄●█▂▄▄▆ beats 15/28   avg 8.539 MT-Bench scor…     27%  sharp · noisy
## How the score was worked out Each result implies a score on its own, after adjusting for how hard that test is and who ran it. The model's score is their weighted average, with a small pull toward the middle for thinly tested models. Each test's weight is its *counts* column above; here it is added up by who ran the tests. [Method](../method.md) 
source                                    results  share of the score
LMArena leaderboard dataset                     1   37% ▇▇▇▇
Polyrating: A Cost-Effective and Bias-A…        1   34% ▇▇▇▇
LMSYS Chatbot Arena leaderboard Space: …        1   27% ▇▇▇
prior: pull toward the middle                        2% ▇
weighted average                                   = 37.7
Licences: LMArena leaderboard dataset ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) · Polyrating: A Cost-Effective and Bias-Aware Rating System for LLM Evaluation ([CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/)) · LMSYS Chatbot Arena leaderboard Space: MT-Bench column of the published leaderboard table ([Apache-2.0](https://www.apache.org/licenses/LICENSE-2.0)) ## How to run it No verified API or local download yet. [interactive version](https://whatmodel.sh/model/mpt-30b-chat) · [JSON](https://whatmodel.sh/api?format=json&all=1)