[whatmodel.sh](../../README.md) / NexusRaven V2 13B
# NexusRaven V2 13B
Nexusflow · released 2023-12 · 13.02B params · other
**score 30.3** ±2.9 · #660 of 732 · from 5 benchmark results across 2 sources
Score within the [LMArena (text)](https://whatmodel.sh/?set=lmarena-text&score=set) comparison set only.
## What it's good at
● marks NexusRaven V2 13B among every model on that task or test, worst to best.
task vs the others rank counts tests
agent tasks ▁▁●▆█▄▅▅▄▄▂▁ #302 of 313* 17% 1
agent tasks · #302 of 313 · 17% of its score
Beats [QwQ-32B-Preview](qwq-32b-preview.md), [DeepSeek-Coder-V2 Lite Instruct (16B-A2.4B)](deepseek-coder-v2-lite-instruct.md), [Phi-4-mini 3.8B](phi-4-mini.md) here, though they rank higher overall. Trails [Granite 4.0 350M](granite-4-0-350m.md), [Granite 4.0 H 350M](granite-4-0-h-350m.md), [ChatGLM3-6B](chatglm3-6b.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
BFCL v3 36.0% ▁▁▁▁●▃▅█▅▄▁▁ beats 11/114 medium · avg 51% 17% blunt · at its level
other tests (4)
test result vs the others in its run difficulty counts why
Natural Questions (closed book) 14.2% ▁·▁·▁▂▁▂·●▂█ beats 12/28 medium · avg 48% 63% typical
TriviaQA 42.3% ▁··▁█▃▃▁▄●▄█ beats 18/28 easy · avg 73% 10% at its level · noisy
HaluEval QA hallucination detecti… 23.7% ●▁▁·▁▁·▁▁▁▁▁ beats 12/27 hard · avg 66% 3.8% too hard for it · noisy
TruthfulQA MC2 44.4% ▅▃█●▁▂▅···▁▁ beats 18/31 medium · avg 57% 2.5% blunt · at its level
source results share of the score
Hallucinations Leaderboard results 4 79% ▇▇▇▇▇▇▇▇▇▇
Berkeley Function Calling Leaderboard r… 1 17% ▇▇
prior: pull toward the middle 4% ▇
weighted average = 30.3
Licences: Hallucinations Leaderboard results ([Apache-2.0](https://www.apache.org/licenses/LICENSE-2.0)) · Berkeley Function Calling Leaderboard result archive ([Apache-2.0](../../licenses/bfcl-result-archive-v4-Apache-2.0.txt))
## How to run it
### llama.cpp (recommended)
1. Install llama.cpp. Homebrew and winget installs name the commands llama-cli and llama-server instead. [Other ways to install](https://github.com/ggml-org/llama.cpp/blob/master/docs/install.md)
```sh
# macOS / Linux
curl -LsSf https://llama.app/install.sh | sh
# Windows
irm https://llama.app/install.ps1 | iex
```
2. Run NexusRaven V2 13B (Q4_K_M, needs ~7.9 GB, from [huggingface.co/TheBloke](https://huggingface.co/TheBloke/NexusRaven-V2-13B-GGUF/tree/a2fd992cf9ade1dc9d04205278ace8b77dae8730))
```sh
llama cli -hf TheBloke/NexusRaven-V2-13B-GGUF:Q4_K_M
```
3. Or start a local server and open the address it prints (http://localhost:9931)
```sh
llama serve -hf TheBloke/NexusRaven-V2-13B-GGUF:Q4_K_M
```
Other versions: Q8_0 (~13.8 GB) `llama cli -hf TheBloke/NexusRaven-V2-13B-GGUF:Q8_0`
### LM Studio
1. Install LM Studio. Open the app once before using the lms command. [Download it (macOS / Windows / Linux)](https://lmstudio.ai/download)
2. Run NexusRaven V2 13B (Q4_K_M, needs ~7.9 GB, from [huggingface.co/TheBloke](https://huggingface.co/TheBloke/NexusRaven-V2-13B-GGUF/tree/a2fd992cf9ade1dc9d04205278ace8b77dae8730))
```sh
lms get https://huggingface.co/TheBloke/NexusRaven-V2-13B-GGUF@Q4_K_M -y
```
3. Then run lms ls to see its name, and lms chat followed by that name
Other versions: Q8_0 (~13.8 GB) `lms get https://huggingface.co/TheBloke/NexusRaven-V2-13B-GGUF@Q8_0 -y` · 6bit (~10.6 GB, Mac only) `lms get https://huggingface.co/k8smee/NexusRaven-V2-13B-mlx-6Bit -y`
### Ollama
1. Install Ollama. [Download it (macOS / Windows)](https://ollama.com/download)
```sh
# Linux
curl -fsSL https://ollama.com/install.sh | sh
```
2. Run NexusRaven V2 13B (Q4_0, needs ~7.4 GB, from [ollama.com](https://ollama.com/library/nexusraven/tags))
```sh
ollama run nexusraven:13b
```
### MLX (Mac)
1. Install MLX (Mac). Apple silicon Macs only, text only.
```sh
# with uv
uv tool install mlx-lm
# or
pip install mlx-lm
```
2. Run NexusRaven V2 13B (6bit, needs ~10.6 GB, Mac only, from [huggingface.co/k8smee](https://huggingface.co/k8smee/NexusRaven-V2-13B-mlx-6Bit/tree/e7735b8cc33742ca2dbe5e0ef75cc96f73056666))
```sh
mlx_lm.chat --model k8smee/NexusRaven-V2-13B-mlx-6Bit
```
3. Or start an OpenAI-compatible server at http://localhost:8080/v1
```sh
mlx_lm.server --model k8smee/NexusRaven-V2-13B-mlx-6Bit
```
Model repository and documentation: [huggingface.co/Nexusflow](https://huggingface.co/Nexusflow/NexusRaven-V2-13B)
[interactive version](https://whatmodel.sh/model/nexusraven-v2-13b) · [JSON](https://whatmodel.sh/api?format=json&all=1)