[whatmodel.sh](../../README.md) / DeepSeek-Coder 7B Instruct v1.5
# DeepSeek-Coder 7B Instruct v1.5
DeepSeek · released 2024-01 · 6.91B params · deepseek
**score 49.0** ±0.7 · #390 of 732 · from 9 benchmark results across 3 sources
Score within the [LMArena (text)](https://whatmodel.sh/?set=lmarena-text&score=set) comparison set only.
## What it's good at
● marks DeepSeek-Coder 7B Instruct v1.5 among every model on that task or test, worst to best.
task vs the others rank counts tests
coding ▁▁▁▃▅●█▇▅▄▃▁ #297 of 469 85% 7
coding · #297 of 469 · 85% 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), [WizardLM 70B V1.0](wizardlm-70b-v1-0.md), [Yi 1.5 9B Chat](yi-1-5-9b-chat.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
HumanEval 75.6% ▁·▁▁▃▄▆▅●▃▁▁ beats 74/99 easy · avg 76% 49% sharp · at its level · several runs
HumanEval+ 71.3% ▁·▁▁▁▃▄▄▄●▃▁ beats 75/99 easy · avg 70% 27% sharp · at its level
MBPP+ 62.2% ▁···▁▁▂▅▇●▆▂ beats 42/75 easy · avg 66% 5.4% at its level
CodeReviewQA: change localisation… 4.6% █▂▁▁●▂▂▃▅▅▅▇ beats 14/47 hard · avg 33% 1.6% sharp · at its level · noisy
CodeReviewQA: solution identifica… 11.4% ▃··▁▂●▃▂█▃▄▂ beats 9/47 medium · avg 51% 1.6% sharp · at its level · noisy
CodeReviewQA: automated code refi… 36.3% ▁▁▁▁▁▁▂▂▃█●▄ beats 35/47 hard · avg 32% 1.3% at its level
CodeReviewQA: change type recogni… 58.1% ▁▁▁······▁●█ beats 9/47 easy · avg 67% 0.0% blunt · at its level · noisy
other tests (1)
test result vs the others in its run difficulty counts why
EvoEval (overall) 48.8% ▂▂▃▄▄█▁▄●▃▁▃ beats 34/42 medium · avg 52% 14% at its level
source results share of the score
EvalPlus / EvalPerf published evaluatio… 3 62% ▇▇▇▇▇▇▇
Top Leaderboard Ranking = Top Coding Pr… 2 33% ▇▇▇▇
CodeReviewQA: The Code Review Comprehen… 4 5% ▇
prior: pull toward the middle 0% ▇
weighted average = 49.0
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)) · CodeReviewQA: The Code Review Comprehension Assessment for Large Language Models ([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 DeepSeek-Coder 7B Instruct v1.5 (Q4_K_M, needs ~4.2 GB, from [huggingface.co/Edmon02](https://huggingface.co/Edmon02/deepseek-coder-7b-instruct-v1.5-GGUF/tree/295e7c005ee33cf633ef66e24f51ad641915a1e7))
```sh
llama cli -hf Edmon02/deepseek-coder-7b-instruct-v1.5-GGUF:Q4_K_M
```
3. Or start a local server and open the address it prints (http://localhost:9931)
```sh
llama serve -hf Edmon02/deepseek-coder-7b-instruct-v1.5-GGUF:Q4_K_M
```
Other versions: Q8_0 (~7.3 GB) `llama cli -hf Edmon02/deepseek-coder-7b-instruct-v1.5-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 DeepSeek-Coder 7B Instruct v1.5 (Q4_K_M, needs ~4.2 GB, from [huggingface.co/Edmon02](https://huggingface.co/Edmon02/deepseek-coder-7b-instruct-v1.5-GGUF/tree/295e7c005ee33cf633ef66e24f51ad641915a1e7))
```sh
lms get https://huggingface.co/Edmon02/deepseek-coder-7b-instruct-v1.5-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 (~7.3 GB) `lms get https://huggingface.co/Edmon02/deepseek-coder-7b-instruct-v1.5-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 DeepSeek-Coder 7B Instruct v1.5 (Q4_K_M, needs ~4.2 GB, from [huggingface.co/Edmon02](https://huggingface.co/Edmon02/deepseek-coder-7b-instruct-v1.5-GGUF/tree/295e7c005ee33cf633ef66e24f51ad641915a1e7))
```sh
ollama run hf.co/Edmon02/deepseek-coder-7b-instruct-v1.5-GGUF:Q4_K_M
```
Other versions: Q8_0 (~7.3 GB) `ollama run hf.co/Edmon02/deepseek-coder-7b-instruct-v1.5-GGUF:Q8_0`
### Other ways to run it
1. Run it as published (BF16, needs ~13.82 GB, from [huggingface.co/deepseek-ai](https://huggingface.co/deepseek-ai/deepseek-coder-7b-instruct-v1.5/tree/2a050a4c59d687a85324d32e147517992117ed30))
```sh
uv run --with torch --with 'transformers<5' --with accelerate python -c "from transformers import pipeline; print(pipeline('text-generation', model='deepseek-ai/deepseek-coder-7b-instruct-v1.5', torch_dtype='auto', device_map='auto')('Once upon a time', max_new_tokens=40)[0]['generated_text'])"
```
Model repository and documentation: [huggingface.co/deepseek-ai](https://huggingface.co/deepseek-ai/deepseek-coder-7b-instruct-v1.5)
[interactive version](https://whatmodel.sh/model/deepseek-coder-7b-instruct-v1-5) · [JSON](https://whatmodel.sh/api?format=json&all=1)