Stablelm Tuned Alpha 7B — Benchmarks

Benchmark scores for Stablelm Tuned Alpha 7B aggregated from public leaderboards (7 boards), with how it ranks among open models and how it compares with its nearest neighbours. See hardware requirements for what you need to run it.

No llmrun Composite Score for Stablelm Tuned Alpha 7B: the score is only published for a model measured on at least 4 of the boards in the score panel, spanning at least 2 benchmark categories and including a reasoning or coding board — or on 3 boards that narrow its score to a 90% range of at most 15.6 points. Either way the results must come from at least two different benchmarks. Its individual scores below stand on their own — see how the llmrun Composite Score gets calculated.

Stablelm Tuned Alpha 7B reasoning benchmarks

Multi-step logic and problem-solving — can the model think through a hard problem rather than recall an answer.

WinoGrande
WinoGrande is a large-scale commonsense-reasoning test built around pronoun resolution: the model must pick which of two nouns a pronoun refers to in a sentence, using real-world knowledge to disambiguate. It was designed by AI2 to resist the shortcuts that let earlier models game its predecessor, Winograd.
51.5%
51.5%
median 70.1%open leader 89.2%
lowest · #51 of 51 open · #79 of 79 all
#51 of 51
#79 of 79
Lab-reported
Epoch AI · Apr 2023

Other results (1)· leaderboard-only, not part of the llmrun Score

PIQA
PIQA (Physical Interaction QA) asks a model to choose the more sensible of two ways to accomplish an everyday physical task, testing practical, physical-world commonsense that isn't well captured by purely textual reasoning tests.
65.8%
65.8%
median 80.1%open leader 88.6%
Overall best: GPT 4o Mini (Jul 18, 2024) 88.7%
lowest · #40 of 40 open · #59 of 59 all
#40 of 40
#59 of 59
Lab-reported
Epoch AI · Apr 2023

Stablelm Tuned Alpha 7B knowledge benchmarks

Breadth and depth of factual knowledge across many subjects, paired with the reasoning to apply it.

ARC Challenge
ARC Challenge is a set of grade-school science questions, curated by the Allen Institute for AI (AI2) to exclude ones that simple word-matching or retrieval can answer. It measures science knowledge paired with the reasoning needed to apply it.
27.0%
27.0%
median 53.9%open leader 95.3%
4th percentile · #54 of 56 open · #74 of 76 all
#54 of 56
#74 of 76
Lab-reported
Epoch AI · Apr 2023

Other results (3)· leaderboard-only, not part of the llmrun Score

HellaSwag
HellaSwag is a commonsense benchmark that asks a model to pick the most plausible continuation of an everyday situation. The wrong options are adversarially chosen to fool models, testing grounded commonsense understanding.
40.7%
40.7%
median 76.2%open leader 89.2%
Overall best: GPT 4 (Mar 14) 95.3%
2nd percentile · #46 of 47 open · #74 of 75 all
#46 of 47
#74 of 75
Lab-reported
Epoch AI · Apr 2023
BoolQ
BoolQ is a reading-comprehension benchmark of naturally occurring yes/no questions, each paired with a short passage that contains the answer. It tests whether a model can extract and reason over information from real text rather than just recall facts.
59.0%
59.0%
median 76.4%open leader 89.4%
Overall best: T5 11B 91.2%
lowest · #38 of 38 open · #71 of 76 all
#38 of 38
#71 of 76
Lab-reported
Epoch AI · Apr 2023
OpenBookQA
OpenBookQA is a science-question benchmark modeled on open-book exams: the model is given a small set of core science facts and must combine them with broader common knowledge to answer multi-step questions. It targets reasoning over recall.
32.4%
32.4%
median 56.8%open leader 88.0%
8th percentile · #24 of 26 open · #39 of 41 all
#24 of 26
#39 of 41
Lab-reported
Epoch AI · Apr 2023

Stablelm Tuned Alpha 7B instruction following benchmarks

How precisely a model obeys explicit, verifiable instructions — format, length, and content constraints — and, more broadly, how much people prefer its responses head-to-head in blind human voting.

LMArena Text
Arena (arena.ai, formerly LMArena / Chatbot Arena) ranks models by millions of blind, head-to-head human votes on real prompts. The Arena Score shown here is a Bradley-Terry rating computed with Arena's default style control, so higher means people preferred that model's answers more often — it's a relative rating, not a percentage, so compare it only to other models on this board.
953.3
953.3
median 1321.5open leader 1487.1
Overall best: Gemini 4 Argon (High) 1523.9
lowest · #187 of 187 open · #405 of 405 all
#187 of 187
#405 of 405
Arena
Arena · Oct 2026

Scores aggregated from public benchmark sources (Epoch AI: 6 boards, Arena: 1 board) — each linked from the benchmark pages. llmrun does not run these benchmarks. Percentiles and ranks are among open models in the llmrun catalogue; the median and leader marks refer to the same field.