[whatmodel.sh](../../README.md) / WaveCoder-Ultra-6.7B
# WaveCoder-Ultra-6.7B
Microsoft · released 2024-04 · mit
**score 49.5** ±0.9 · #385 of 732 · from 3 benchmark results across 1 source
Score within the [LMArena (text)](https://whatmodel.sh/?set=lmarena-text&score=set) comparison set only.
## What it's good at
● marks WaveCoder-Ultra-6.7B among every model on that task or test, worst to best.
task vs the others rank counts tests
coding ▁▁▁▃▅▇●▇▅▄▃▁ #291 of 469 100% 3
coding · #291 of 469 · 100% of its score
Beats [Qwen3-VL 32B Instruct](qwen3-vl-32b-instruct.md), [Solar Open 100B (102B-A12B)](solar-open-100b.md), [Qwen3-VL 30B-A3B Instruct](qwen3-vl-30b-a3b-instruct.md) here, though they rank higher overall. Trails [DeepSeek LLM 67B Chat](deepseek-llm-67b-chat.md), [Yi 1.5 9B Chat](yi-1-5-9b-chat.md), [Mistral NeMo Instruct (2407)](mistral-nemo-instruct-2407.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
HumanEval 75.0% ▁·▁▁▃▄▆▅●▃▁▁ beats 70/99 easy · avg 76% 48% sharp
HumanEval+ 69.5% ▁·▁▁▁▃▄▄▄●▃▁ beats 69/99 easy · avg 70% 43% sharp · at its level
MBPP+ 63.5% ▁···▁▁▂▅▇●▆▂ beats 45/75 easy · avg 66% 8.8% at its level
source results share of the score
EvalPlus / EvalPerf published evaluatio… 3 100% ▇▇▇▇▇▇▇▇▇▇▇▇
prior: pull toward the middle 0% ▇
weighted average = 49.5
Licences: EvalPlus / EvalPerf published evaluation runs ([Apache-2.0](../../licenses/evalplus-published-runs-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 WaveCoder-Ultra-6.7B (Q4_K_M, needs ~4.1 GB, from [huggingface.co/lmstudio-community](https://huggingface.co/lmstudio-community/wavecoder-ultra-6.7b-GGUF/tree/b0c5823a17caedf39d912681e88f94dd4c004257))
```sh
llama cli -hf lmstudio-community/wavecoder-ultra-6.7b-GGUF:Q4_K_M
```
3. Or start a local server and open the address it prints (http://localhost:9931)
```sh
llama serve -hf lmstudio-community/wavecoder-ultra-6.7b-GGUF:Q4_K_M
```
Other versions: Q8_0 (~7.2 GB) `llama cli -hf lmstudio-community/wavecoder-ultra-6.7b-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 WaveCoder-Ultra-6.7B (Q4_K_M, needs ~4.1 GB, from [huggingface.co/lmstudio-community](https://huggingface.co/lmstudio-community/wavecoder-ultra-6.7b-GGUF/tree/b0c5823a17caedf39d912681e88f94dd4c004257))
```sh
lms get https://huggingface.co/lmstudio-community/wavecoder-ultra-6.7b-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 (~7.2 GB) `lms get https://huggingface.co/lmstudio-community/wavecoder-ultra-6.7b-GGUF@Q8_0 -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 WaveCoder-Ultra-6.7B (Q4_K_M, needs ~4.1 GB, from [huggingface.co/lmstudio-community](https://huggingface.co/lmstudio-community/wavecoder-ultra-6.7b-GGUF/tree/b0c5823a17caedf39d912681e88f94dd4c004257))
```sh
ollama run hf.co/lmstudio-community/wavecoder-ultra-6.7b-GGUF:Q4_K_M
```
Other versions: Q8_0 (~7.2 GB) `ollama run hf.co/lmstudio-community/wavecoder-ultra-6.7b-GGUF:Q8_0`
### Other ways to run it
1. Run it as published (fp32, needs ~26.95 GB, from [huggingface.co/microsoft](https://huggingface.co/microsoft/wavecoder-ultra-6.7b/tree/57049dba4025d92e99e786081076df44dacc44a1))
```sh
uv run --with torch --with 'transformers<5' --with accelerate python -c "from transformers import pipeline; print(pipeline('text-generation', model='microsoft/wavecoder-ultra-6.7b', torch_dtype='auto', device_map='auto')('Once upon a time', max_new_tokens=40)[0]['generated_text'])"
```
Model repository and documentation: [huggingface.co/microsoft](https://huggingface.co/microsoft/wavecoder-ultra-6.7b)
[interactive version](https://whatmodel.sh/model/wavecoder-ultra-6-7b) · [JSON](https://whatmodel.sh/api?format=json&all=1)