[whatmodel.sh](../../README.md) / StarCoder2 15B
# StarCoder2 15B
BigCode · released 2024-02 · 15.96B params · bigcode-openrail-m
**score 40.5** ±0.5 · #556 of 732 · from 17 benchmark results across 5 sources
Score within the [LMArena (text)](https://whatmodel.sh/?set=lmarena-text&score=set) comparison set only.
## What it's good at
● marks StarCoder2 15B among every model on that task or test, worst to best.
task vs the others rank counts tests
coding ▁▁▁▃●▇█▇▅▄▃▁ #399 of 469 87% 9
math ▁▁▃▅█●▄█▄▂▁▁ #242 of 431* 2.8% 1
coding · #399 of 469 · 87% of its score
Beats [DeepSeek R1 Distill Qwen 7B](deepseek-r1-distill-qwen-7b.md), [Qwen3.5 2B](qwen3-5-2b.md), [DeepSeek R1 Distill Llama 8B](deepseek-r1-distill-llama-8b.md) here, though they rank higher overall. Trails [Qwen2.5 1.5B Instruct](qwen2-5-1-5b.md), [WizardLM 13B V1.2](wizardlm-13b-v1-2.md), [Falcon3 3B Instruct](falcon3-3b.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
HumanEval 46.3% ▁·▁▁▃▄●▅█▃▁▁ beats 30/99 easy · avg 76% 45% sharp · at its level · several runs
HumanEval+ 37.8% ▁·▁▁▁▃●▄▄█▃▁ beats 27/99 easy · avg 70% 18% sharp · at its level
MBPP 51.2% █·▅▃▃▃▅▃▃▅·● beats 14/15 easy · avg 81% 6.0% at its level · several runs
HumanEvalSynthesize (HumanEvalPac… 44.4% ▁·▂▁▂▆▅█●▄▁▂ beats 26/35 medium · avg 62% 4.8% at its level
DS-1000 (maker) 33.8% ▄▄·▄██▄█·●·▄ beats 10/12 medium · avg 49% 2.9% at its level
HumanEvalExplain (HumanEvalPack, … 17.0% ▄▇●▃▄▇▄▁▇▃·▁ beats 12/35 medium · avg 46% 2.9% at its level
CRUXEval-I 47.4% ▃▅█▃▃▅·▃▃▅·● beats 14/15 medium · avg 56% 2.8% at its level · several runs
HumanEvalFix (HumanEvalPack, 6-la… 21.9% ▁·▁▁▄██●█▁▅▅ beats 20/35 medium · avg 51% 2.7% sharp
CRUXEval-O 46.7% ▃·▃██▅▃·▃▃▅● beats 15/15 medium · avg 54% 2.2% blunt · at its level · several runs
math · #242 of 431 · 2.8% of its score
Beats [GPT-4o (2024-08-06)](gpt-4o-2024-08-06.md), [Command A (03-2025)](command-a.md), [GPT-4o (2024-05-13)](gpt-4o-2024-05-13.md) here, though they rank higher overall. Trails [Gemma 7B (base)](gemma-7b-base.md), [CodeGemma 7B (v1.0)](codegemma-7b.md), [Phi-2 (2.7B)](phi-2.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
GSM8K (maker) 65.1% ▄▄▄·▄█·██·█● beats 12/12 easy · avg 75% 2.8% sharp · at its level
other tests (2)
test result vs the others in its run difficulty counts why
EvoEval (overall) 29.0% ▂▂▃▄●█▁▄▅▃▁▃ beats 13/42 medium · avg 52% 7.2% at its level
BigCodeBench (Complete) (maker) 38.3% ▂▁▁▄▂▅●█▆▂▂▂ beats 22/58 medium · avg 48% 3.0% at its level
source results share of the score
EvalPlus / EvalPerf published evaluatio… 2 41% ▇▇▇▇▇
Top Leaderboard Ranking = Top Coding Pr… 2 21% ▇▇
StarCoder 2 and The Stack v2: The Next … 6 19% ▇▇
Granite Code Models: A Family of Open F… 6 17% ▇▇
BigCodeBench paper (submitted / maker-r… 1 3% ▇
prior: pull toward the middle 0% ▇
weighted average = 40.5
Licences: EvalPlus / EvalPerf published evaluation runs ([Apache-2.0](../../licenses/evalplus-published-runs-Apache-2.0.txt)) · Top Leaderboard Ranking = Top Coding Proficiency ([CC BY 4.0](../../licenses/paper-2403.19114v1-CC-BY-4.0.txt)) · StarCoder 2 and The Stack v2: The Next Generation ([CC BY-SA 4.0](../../licenses/paper-2402.19173v1-CC-BY-SA-4.0.txt)) · Granite Code Models: A Family of Open Foundation Models for Code Intelligence ([CC BY 4.0](../../licenses/paper-2405.04324v1-CC-BY-4.0.txt)) · BigCodeBench paper ([CC BY 4.0](http://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 StarCoder2 15B (Q4_K_M, needs ~9.9 GB, from [huggingface.co/second-state](https://huggingface.co/second-state/StarCoder2-15B-GGUF/tree/4d76ffd0a6da75113a3971639b36309cde2364d7))
```sh
llama cli -hf second-state/StarCoder2-15B-GGUF:Q4_K_M
```
3. Or start a local server and open the address it prints (http://localhost:9931)
```sh
llama serve -hf second-state/StarCoder2-15B-GGUF:Q4_K_M
```
Other versions: Q8_0 (~17 GB) `llama cli -hf second-state/StarCoder2-15B-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 StarCoder2 15B (Q4_K_M, needs ~9.9 GB, from [huggingface.co/second-state](https://huggingface.co/second-state/StarCoder2-15B-GGUF/tree/4d76ffd0a6da75113a3971639b36309cde2364d7))
```sh
lms get https://huggingface.co/second-state/StarCoder2-15B-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 (~17 GB) `lms get https://huggingface.co/second-state/StarCoder2-15B-GGUF@Q8_0 -y` · 4bit (~9 GB, Mac only) `lms get https://huggingface.co/mlx-community/bigcode-starcoder2-15b-4bit -y` · 8bit (~17 GB, Mac only) `lms get https://huggingface.co/mlx-community/bigcode-starcoder2-15b-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 StarCoder2 15B (Q4_K_M, needs ~9.9 GB, from [ollama.com](https://ollama.com/library/starcoder2/tags))
```sh
ollama run starcoder2:15b-q4_K_M
```
Other versions: Q8_0 (~17 GB) `ollama run starcoder2:15b-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 StarCoder2 15B (4bit, needs ~9 GB, Mac only, from [huggingface.co/mlx-community](https://huggingface.co/mlx-community/bigcode-starcoder2-15b-4bit/tree/7b68b8f7cc25665c4cd615b631afbe2701e11380))
```sh
mlx_lm.chat --model mlx-community/bigcode-starcoder2-15b-4bit
```
3. Or start an OpenAI-compatible server at http://localhost:8080/v1
```sh
mlx_lm.server --model mlx-community/bigcode-starcoder2-15b-4bit
```
Other versions: 8bit (~17 GB, Mac only) `mlx_lm.chat --model mlx-community/bigcode-starcoder2-15b-8bit`
Model repository and documentation: [huggingface.co/bigcode](https://huggingface.co/bigcode/starcoder2-15b)
[interactive version](https://whatmodel.sh/model/starcoder2-15b) · [JSON](https://whatmodel.sh/api?format=json&all=1)