[whatmodel.sh](../../README.md) / OpenCoder-8B-Instruct
# OpenCoder-8B-Instruct
INF (infly) · released 2024-11 · 7.77B params · other (inf)
**score 52.5** ±0.9 · #330 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 OpenCoder-8B-Instruct among every model on that task or test, worst to best.
task vs the others rank counts tests
coding ▁▁▁▃▅▇●▇▅▄▃▁ #249 of 469 94% 3
coding · #249 of 469 · 94% of its score
Beats [Qwen3-VL 32B Instruct](qwen3-vl-32b-instruct.md), [Solar Open 100B (102B-A12B)](solar-open-100b.md), [GLM-4.7-Flash](glm-4-7-flash.md) here, though they rank higher overall. Trails [QwQ-32B-Preview](qwq-32b-preview.md), [InternLM2.5 20B Chat](internlm2-5-20b-chat.md), [Ministral 3 3B Reasoning 2512](ministral-3-3b-reasoning.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
HumanEval 81.7% ▁·▁▁▃▄▆▅●▃▁▁ beats 86/99 easy · avg 76% 44% sharp
HumanEval+ 77.4% ▁·▁▁▁▃▄▄▄█●▁ beats 87/99 easy · avg 70% 41% sharp
MBPP+ 71.4% ▁···▁▁▂▅▇█●▂ beats 66/75 easy · avg 66% 9.3% at its level
other tests (2)
test result vs the others in its run difficulty counts why
EvalPerf correctness (118 tasks, … 76.9% ▂·▂▂▂▆▅●▆▆▃█ beats 11/29 easy · avg 74% 4.9% typical
EuroEval Life in the UK (English … 46.2% ▁▁▁▁▁▁●▂▄█▄▃ beats 18/146 easy · avg 82% 1.0% noisy
source results share of the score
EvalPlus / EvalPerf published evaluatio… 4 99% ▇▇▇▇▇▇▇▇▇▇▇▇
EuroEval leaderboards 1 1% ▇
prior: pull toward the middle 0% ▇
weighted average = 52.5
Licences: EvalPlus / EvalPerf published evaluation runs ([Apache-2.0](../../licenses/evalplus-published-runs-Apache-2.0.txt)) · EuroEval leaderboards ([MIT](https://github.com/EuroEval/leaderboards/blob/1a77f1d2f8ba1ba05ab73287fb090d76bf41b2e0/LICENSE))
## 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 OpenCoder-8B-Instruct (Q4_K_M, needs ~4.7 GB, from [huggingface.co/lmstudio-community](https://huggingface.co/lmstudio-community/OpenCoder-8B-Instruct-GGUF/tree/1ff8b18e7773e3adfbcb269f20ad6afffecad8b0))
```sh
llama cli -hf lmstudio-community/OpenCoder-8B-Instruct-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/OpenCoder-8B-Instruct-GGUF:Q4_K_M
```
Other versions: Q8_0 (~8.3 GB) `llama cli -hf lmstudio-community/OpenCoder-8B-Instruct-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 OpenCoder-8B-Instruct (Q4_K_M, needs ~4.7 GB, from [huggingface.co/lmstudio-community](https://huggingface.co/lmstudio-community/OpenCoder-8B-Instruct-GGUF/tree/1ff8b18e7773e3adfbcb269f20ad6afffecad8b0))
```sh
lms get https://huggingface.co/lmstudio-community/OpenCoder-8B-Instruct-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 (~8.3 GB) `lms get https://huggingface.co/lmstudio-community/OpenCoder-8B-Instruct-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 OpenCoder-8B-Instruct (Q4_K_M, needs ~4.7 GB, from [huggingface.co/lmstudio-community](https://huggingface.co/lmstudio-community/OpenCoder-8B-Instruct-GGUF/tree/1ff8b18e7773e3adfbcb269f20ad6afffecad8b0))
```sh
ollama run hf.co/lmstudio-community/OpenCoder-8B-Instruct-GGUF:Q4_K_M
```
Other versions: Q8_0 (~8.3 GB) `ollama run hf.co/lmstudio-community/OpenCoder-8B-Instruct-GGUF:Q8_0`
### Other ways to run it
1. Run it as published (BF16, needs ~15.54 GB, from [huggingface.co/infly](https://huggingface.co/infly/OpenCoder-8B-Instruct/tree/01badbbf10c2dfd7e2a0b5f570065ef44548576c))
```sh
uv run --with torch --with 'transformers<5' --with accelerate python -c "from transformers import pipeline; print(pipeline('text-generation', model='infly/OpenCoder-8B-Instruct', torch_dtype='auto', device_map='auto')('Once upon a time', max_new_tokens=40)[0]['generated_text'])"
```
Model repository and documentation: [huggingface.co/infly](https://huggingface.co/infly/OpenCoder-8B-Instruct)
[interactive version](https://whatmodel.sh/model/opencoder-8b-instruct) · [JSON](https://whatmodel.sh/api?format=json&all=1)