[whatmodel.sh](../../README.md) / AceReason-Nemotron-1.1-7B
# AceReason-Nemotron-1.1-7B
NVIDIA · released 2025-06 · 7.62B params · nvidia-open-model-license
**score 48.1** ±1.9 · #408 of 732 · from 3 benchmark results across 1 source · † no independently run results verified
Score within the [LMArena (text)](https://whatmodel.sh/?set=lmarena-text&score=set) comparison set only.
## What it's good at
● marks AceReason-Nemotron-1.1-7B among every model on that task or test, worst to best.
task vs the others rank counts tests
coding ▁▁▁▃▅●█▇▅▄▃▁ #322 of 469 98% 3
coding · #322 of 469 · 98% of its score
Beats [Solar Open 100B (102B-A12B)](solar-open-100b.md), [Qwen3 4B Instruct 2507](qwen3-4b-instruct-2507.md), [Qwen3-VL 8B Instruct](qwen3-vl-8b-instruct.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), [Code Tulu 2 34B](code-tulu-2-34b.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
LiveCodeBench Pro 2025Q2 (Easy) (… 42.3% ●·▄····▄▄▄█▄ beats 0/7 medium · avg 46% 46% at its level
LiveCodeBench Pro 2025Q2 (Medium)… 1.8% ●▃····▃·█·▃▃ beats 0/7 very hard · avg 2.6% 30% sharp · too hard for it
LiveCodeBench v6 (Aug 2024–May 20… 55.2% ●▄···▄·▄▄█·▄ beats 0/7 medium · avg 58% 22% at its level
source results share of the score
NVIDIA (submitted / maker-reported) 3 98% ▇▇▇▇▇▇▇▇▇▇▇▇
prior: pull toward the middle 2% ▇
weighted average = 48.1
Licences: NVIDIA ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/))
## 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 AceReason-Nemotron-1.1-7B (Q4_K_M, needs ~4.68 GB, from [huggingface.co/bartowski](https://huggingface.co/bartowski/nvidia_AceReason-Nemotron-1.1-7B-GGUF/tree/7b4f7f68d4c66933c7a5d376db8a413cbc6b49b1))
```sh
llama cli -hf bartowski/nvidia_AceReason-Nemotron-1.1-7B-GGUF:Q4_K_M
```
3. Or start a local server and open the address it prints (http://localhost:9931)
```sh
llama serve -hf bartowski/nvidia_AceReason-Nemotron-1.1-7B-GGUF:Q4_K_M
```
Other versions: Q8_0 (~8.1 GB) `llama cli -hf bartowski/nvidia_AceReason-Nemotron-1.1-7B-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 AceReason-Nemotron-1.1-7B (Q4_K_M, needs ~4.68 GB, from [huggingface.co/bartowski](https://huggingface.co/bartowski/nvidia_AceReason-Nemotron-1.1-7B-GGUF/tree/7b4f7f68d4c66933c7a5d376db8a413cbc6b49b1))
```sh
lms get https://huggingface.co/bartowski/nvidia_AceReason-Nemotron-1.1-7B-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 (~8.1 GB) `lms get https://huggingface.co/bartowski/nvidia_AceReason-Nemotron-1.1-7B-GGUF@Q8_0 -y` · 4bit (~4.3 GB, Mac only) `lms get https://huggingface.co/mlx-community/AceReason-Nemotron-1.1-7B-4bit -y` · 8bit (~8.1 GB, Mac only) `lms get https://huggingface.co/mlx-community/AceReason-Nemotron-1.1-7B-8bit -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 AceReason-Nemotron-1.1-7B (Q4_K_M, needs ~4.68 GB, from [huggingface.co/bartowski](https://huggingface.co/bartowski/nvidia_AceReason-Nemotron-1.1-7B-GGUF/tree/7b4f7f68d4c66933c7a5d376db8a413cbc6b49b1))
```sh
ollama run hf.co/bartowski/nvidia_AceReason-Nemotron-1.1-7B-GGUF:Q4_K_M
```
Other versions: Q8_0 (~8.1 GB) `ollama run hf.co/bartowski/nvidia_AceReason-Nemotron-1.1-7B-GGUF:Q8_0`
### 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 AceReason-Nemotron-1.1-7B (4bit, needs ~4.3 GB, Mac only, from [huggingface.co/mlx-community](https://huggingface.co/mlx-community/AceReason-Nemotron-1.1-7B-4bit/tree/e7068ba12165480d6c4b643a8c168b63f5cad827))
```sh
mlx_lm.chat --model mlx-community/AceReason-Nemotron-1.1-7B-4bit
```
3. Or start an OpenAI-compatible server at http://localhost:8080/v1
```sh
mlx_lm.server --model mlx-community/AceReason-Nemotron-1.1-7B-4bit
```
Other versions: 8bit (~8.1 GB, Mac only) `mlx_lm.chat --model mlx-community/AceReason-Nemotron-1.1-7B-8bit`
Model repository and documentation: [huggingface.co/nvidia](https://huggingface.co/nvidia/AceReason-Nemotron-1.1-7B)
[interactive version](https://whatmodel.sh/model/acereason-nemotron-1-1-7b) · [JSON](https://whatmodel.sh/api?format=json&all=1)