# Arena-Hard (Mistral-7B-v0.1-Instruct) (JudgeBench) Benchmark Scores & Performance

> Arena-Hard (Mistral-7B-v0.1-Instruct) (JudgeBench) has published results in 1 original benchmark tables. The evaluated configuration, source metrics, and precision remain visible below. These results do not produce a general model score or rank.

Canonical page: https://benchlm.ai/models/native-judgebench-arena-hard-mistral-7b-v0-1-instruct

Last updated: 2026-10-01

General benchmark catalog last updated: October 1, 2026. This profile’s source review has its own date above.

## Model Details

| Property | Value |
|----------|-------|
| Creator | JudgeBench evaluated system |
| Source Type | Research system |
| Reasoning Type | Unspecified |
| Context Window | Not established by evaluation |
| Official model card | [Benchmark-owner results and configuration](https://arxiv.org/abs/2410.12784v2) |
| Overall Score | Not computed (source protocol results only) |
| Overall Rank | Unranked |

## Family & Coverage

- Family: Arena-Hard (Mistral-7B-v0.1-Instruct) (JudgeBench)
- Variant: benchmark-system
- Benchmarks covered: 0 of 645
- Coverage note: Original benchmark result tables appear below; these metrics are separate from weighted benchmark slots.

## Original benchmark results

[All model results (JSON)](/api/data/benchmarks?model=native-judgebench-arena-hard-mistral-7b-v0-1-instruct) · [Numeric metrics (CSV)](/api/data/benchmarks?model=native-judgebench-arena-hard-mistral-7b-v0-1-instruct&format=csv)

### Paper: Prometheus and its base model

JudgeBench’s paper and maintained leaderboard report judges under different prompts, reasoning efforts, and response-model splits. Accuracy is a percentage. The paper’s 700-pair GPT-4o split is distinct from the 270-pair Claude split. The app appends the same Nemotron CSV to both tabs without specifying a response split; we show that supplement once with its split unresolved. Live one-decimal values and paper two-decimal values are preserved separately.

Paper v2; source group labels and published precision are retained.

JudgeBench: A Benchmark for Evaluating LLM-Based Judges — Sijun Tan and colleagues. Numeric results transcribed and reformatted; evaluation notes and model links added by BenchLM. Published numeric precision is retained.

[Published source](https://arxiv.org/abs/2410.12784v2) · [Full JudgeBench results](/benchmarks/judgebench)

| Judge | Knowledge accuracy (%) |
| --- | --- |
| Arena-Hard (Mistral-7B-v0.1-Instruct) | 6.57 |

## Other JudgeBench evaluated system Models

- [Vanilla (Mistral-7B-v0.1-Instruct) (JudgeBench)](/models/native-judgebench-vanilla-mistral-7b-v0-1-instruct) - Score: not computed