Best open source LLM for coding in 2025
Ollama's Llama 3.2 due to its state-of-the-art architecture, strong coding benchmarks, and permissive open-source license. It offers robust performance for code generation and understanding without API costs.RECOMMENDATION
Ollama's Llama 3.2 for coding tasks in 2025 because it combines cutting-edge model quality with open-source freedom, enabling local deployment and customization without vendor lock-in.| Use case | Best choice | Why | Runner-up |
|---|---|---|---|
| Code generation and completion | Ollama Llama 3.2 | High accuracy on coding benchmarks and open-source flexibility | Meta Llama 3.1-70b |
| Local development and privacy | Ollama Llama 3.2 | Runs locally with no cloud dependency, ensuring data privacy | llama.cpp |
| Lightweight coding assistant | llama.cpp | Extremely efficient for small-scale coding tasks on edge devices | Ollama Llama 3.2 |
| Research and fine-tuning | Ollama Llama 3.2 | Open weights and permissive license enable customization | Meta Llama 3.2 |
| Multilingual coding support | Ollama Llama 3.2 | Strong multilingual capabilities with coding context | Meta Llama 3.1-405b |
Top picks explained
Ollama Llama 3.2 is the top open source LLM for coding in 2025 due to its advanced architecture, strong benchmark performance, and permissive license allowing local use and fine-tuning. Meta Llama 3.1-70b is a close runner-up, offering excellent coding capabilities but with a more restrictive license and larger resource requirements. For lightweight or edge use, llama.cpp provides a minimal footprint solution optimized for local inference.
In practice
Here is an example of using Ollama Llama 3.2 locally for code generation with Python:
import ollama
response = ollama.chat(model="llama-3.2", messages=[{"role": "user", "content": "Write a Python function to reverse a string."}])
print(response.text)def reverse_string(s):
return s[::-1] Pricing and limits
| Option | Free | Cost | Limits | Context |
|---|---|---|---|---|
| Ollama Llama 3.2 | Fully free and open source | No cost | Local hardware limits | Local deployment, no API calls |
| Meta Llama 3.1-70b | Open source | No cost | Requires powerful GPU | Research and commercial use with license |
| llama.cpp | Fully free and open source | No cost | Smaller model size, less accuracy | Edge devices and local inference |
What to avoid
Avoid proprietary or closed-source LLMs for coding if you require full control, privacy, or no recurring costs. Models like gpt-4o or cloud-only APIs limit offline use and can incur significant costs. Also, steer clear of outdated models like gpt-3.5-turbo which are deprecated and less capable.
How to evaluate for your case
Benchmark your coding tasks using open source datasets like HumanEval or CodeContests. Measure latency, accuracy, and resource usage on your hardware. Test fine-tuning ease and integration with your development environment to pick the best fit.
Key Takeaways
- Use
Ollama Llama 3.2for best open source coding LLM performance and flexibility. - Local deployment ensures privacy and zero API costs for coding tasks.
- Avoid deprecated or proprietary models for open source coding workflows.