[whatmodel.sh](../../README.md) / MPT-7B-Chat # MPT-7B-Chat MosaicML · released 2023-05 · 7B params · cc-by-nc-sa-4.0 **score 29.4** ±1.8 · comparison only: no current run option verified · from 4 benchmark results across 4 sources Score within the [LMArena (text)](https://whatmodel.sh/?set=lmarena-text&score=set) comparison set only. ## What it's good at _{● marks MPT-7B-Chat among every model on that task or test, worst to best.}

task            vs the others         rank  counts  tests
chat & writing  ▁▁●▃▅▄▇█▇▇▇▃   #459 of 474     90%      3

chat & writing · #459 of 474 · 90% of its score

Beats [Phi-2 (2.7B)](phi-2.md), [Falcon 40B Instruct](falcon-40b-instruct.md), [ChatGLM3-6B](chatglm3-6b.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 350M](granite-4-0-350m.md) here, though they rank lower overall.

test                                                      result  vs the others in its run  difficulty                counts  why
LMArena (text)                                            1063.5  ▁▁●▂▃▃▃▆▆▇█▃ beats 9/385  avg 1260                     34%  blunt
Polyrating rating (bias-aware re-…                         944.0  ▂▁●▁▃▇█▆▇▄▂▂ beats 8/95   avg 1187                     31%  typical
MT-Bench (GPT-4 single-answer gra…  5.4200 MT-Bench score (1-10)  ▆▂▂▆▆●██▂▄▄▆ beats 12/28  avg 8.539 MT-Bench scor…     24%  sharp · noisy

other tests (1)

test  result  vs the others in its run   difficulty        counts  why
MMLU   33.8%  ▁▁▁▁▁●▂▅██▆▄ beats 17/214  medium · avg 71%    8.9%  noisy · small run

## 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   34% ▇▇▇▇
Polyrating: A Cost-Effective and Bias-A…        1   31% ▇▇▇▇
LMSYS Chatbot Arena leaderboard Space: …        1   24% ▇▇▇
OLMo: Accelerating the Science of Langu…        1    9% ▇
prior: pull toward the middle                        1% ▇
weighted average                                   = 29.4

_{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)) · OLMo: Accelerating the Science of Language Models ([CC BY 4.0](../../licenses/paper-2402.00838v4-CC-BY-4.0.txt))} ## How to run it No verified API or local download yet. [interactive version](https://whatmodel.sh/model/mpt-7b-chat) · [JSON](https://whatmodel.sh/api?format=json&all=1)