[whatmodel.sh](../../README.md) / WizardLM-2 8x22B # WizardLM-2 8x22B Microsoft · released 2024-04 · 141B params (39B active) · apache-2.0 **score 50.5** ±1.2 · #357 of 732 · from 7 benchmark results across 6 sources Score within the [LMArena (text)](https://whatmodel.sh/?set=lmarena-text&score=set) comparison set only. ## What it's good at _{● marks WizardLM-2 8x22B among every model on that task or test, worst to best.}

task    vs the others          rank  counts  tests
coding  ▁▁▁▃▅●█▇▅▄▃▁   #315 of 469*     29%      1
math    ▁▁▃▅●▆▄█▄▂▁▁   #333 of 431*     28%      1

coding · #315 of 469 · 29% of its score

Beats [Solar Open 100B (102B-A12B)](solar-open-100b.md), [Qwen3-VL 30B-A3B Instruct](qwen3-vl-30b-a3b-instruct.md), [Qwen3 4B Instruct 2507](qwen3-4b-instruct-2507.md) here, though they rank higher overall. Trails [DeepSeek LLM 67B Chat](deepseek-llm-67b-chat.md), [WizardLM 70B V1.0](wizardlm-70b-v1-0.md), [Yi 1.5 9B Chat](yi-1-5-9b-chat.md) here, though they rank lower overall.

test                                result  vs the others in its run  difficulty        counts  why
Aider code editing (133 Exercism …   44.4%  ▁·▁▂▄●▆▄█▆▂▂ beats 12/62  medium · avg 51%     29%  sharp · at its level

math · #333 of 431 · 28% of its score

Beats [GPT-4 (0613)](gpt-4-0613.md), [Athene-70B](athene-70b.md), [Llama 3 70B Instruct](llama-3-70b.md) here, though they rank higher overall. Trails [Stable Code 3B](stable-code-3b.md), [Zephyr 7B beta](zephyr-7b-beta.md), [Qwen3 0.6B](qwen3-0-6b.md) here, though they rank lower overall.

test          result  vs the others in its run  difficulty      counts  why
MATH level 5   25.7%  ▂▂▅●▄█▆▃▅▂▃▄ beats 25/92  hard · avg 28%     28%  sharp · at its level

other tests (5)

test                                result  vs the others in its run   difficulty           counts  why
GPQA Diamond                         43.4%  ▁▁▁▁▂▄●▄▅▇█▅ beats 47/211  hard · avg 39%          16%  sharp
CPTUB average (SpeakLeash, 0-5 ju…   74.0%  ▁▂▂▂▃█▃▆●▄▂▃ beats 65/95   medium · avg 65%        11%  at its level
Polish EQ-Bench v2 (SpeakLeash)      69.6%  ▁··▁▁▂▂▆▅▆●▆ beats 51/70   medium · avg 62%       8.7%  at its level
Judgemark v2 (LLM-as-judge for cr…   55.4%  ▃▃··●▅▅···█▃ beats 2/10    medium · avg 53%       5.4%  at its level
Vectara hallucination leaderboard…   88.3%  ▁▁▂●▄▄█▆▃▂▂▁ beats 17/140  very easy · avg 94%    0.9%  blunt · maxed out · 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
Epoch AI                                      2   44% ▇▇▇▇▇
Aider code editing benchmark runs             1   29% ▇▇▇
SpeakLeash CPTUB                              1   11% ▇
SpeakLeash Polish EQ-Bench leaderboard        1    9% ▇
Judgemark v2 results                          1    5% ▇
Vectara hallucination leaderboard             1    1% ▇
prior: pull toward the middle                      1% ▇
weighted average                                 = 50.5

_{Licences: Epoch AI ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) · Aider code editing benchmark runs ([Apache-2.0](../../licenses/aider-polyglot-runs-Apache-2.0.txt)) · SpeakLeash CPTUB ([MIT](../../licenses/hf-leaderboard-spaces-MIT.txt)) · SpeakLeash Polish EQ-Bench leaderboard ([Apache-2.0](../../licenses/hf-leaderboard-spaces-Apache-2.0.txt)) · Judgemark v2 results ([MIT](../../licenses/judgemark-v2-MIT.txt)) · Vectara hallucination leaderboard ([Apache-2.0](https://www.apache.org/licenses/LICENSE-2.0))} ## How to run it ### Ollama (recommended) 1. Install Ollama. [Download it (macOS / Windows)](https://ollama.com/download) ```sh # Linux curl -fsSL https://ollama.com/install.sh | sh ``` 2. Run WizardLM-2 8x22B (Q4_0, needs ~85.1 GB, from [ollama.com](https://ollama.com/library/wizardlm2/tags)) ```sh ollama run wizardlm2:8x22b ``` Other versions: Q8_0 (~169.7 GB) `ollama run wizardlm2:8x22b-q8_0` [interactive version](https://whatmodel.sh/model/wizardlm-2-8x22b) · [JSON](https://whatmodel.sh/api?format=json&all=1)