# Best large language model tools for automated code generation and review?

<p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">I’m helping a few engineering teams experiment with LLMs for generating code, reviewing pull requests, and catching issues earlier in the dev cycle. To see what models teams trust most, I reviewed <strong>G2 data for the Large Language Models category</strong> focused on developer use cases. Here’s what comes up.</p>Top LLM tools (by G2 Score)<ul>
<li>Gemini: Best for teams that want code generation with strong reasoning across large codebases.</li>
<li>Meta Llama 3: Best for teams that want open models they can fine-tune for internal dev workflows.</li>
<li>BERT: Best for teams that want code understanding and classification tasks.</li>
<li>GPT-4: Best for teams that want high-quality code generation and detailed code reviews.</li>
<li>GPT-3: Best for teams that want fast code suggestions and boilerplate generation.</li>
<li>Megatron-LM: Best for teams that want large-scale custom models trained on internal code.</li>
</ul><p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">Anyone relying on LLMs for code reviews today? I also see IDE-native tools mentioned alongside these models. Any other tool to include? What’s been your experience?</p>

##### Post Metadata
- Posted at: 5 months ago
- Author title: SaaS and Software Research
- Net upvotes: 1


## Comments
### Comment 1

&lt;p&gt;Do you let LLMs write production code—or only assist?&lt;/p&gt;

##### Comment Metadata
- Posted at: 5 months ago
- Author title: SaaS and Software Research





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