13 Best LLM for Coding in 2025: Top AI Models for Developers

Modern software teams don’t lose time writing code—they lose it doing everything around it: debugging edge cases, switching between tools, reviewing pull requests, and wrestling with legacy systems. These slowdowns compound quickly, especially in large codebases where one fix can trigger multiple new issues.

No surprise then: 7 in 10 software projects still miss their delivery deadlines.

To close that gap, engineering teams are turning to large language models (LLMs) that can generate, refactor, and document code with contextual precision. The right model doesn’t just autocomplete—it accelerates the entire development cycle, reducing repetitive work and improving quality across the board.

In this guide, we break down the best LLMs for coding, ranked by real-world usability, reasoning ability, performance, and integration with modern engineering workflows.

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Top 13 LLMs for Coding at a Glance

Here’s a glimpse into the top tools discussed in this article, along with their key features, pricing plans, and cost-effectiveness.

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What Should You Look for in the Best LLM for Coding?

You’re racing a deadline, bouncing between writing code, fixing bugs, and testing everything before launch. What’s supposed to help—your digital tools—starts slowing you down instead. Suggestions lag, snippets miss the mark, and fixes take longer than they should.

Choosing the best LLM for coding means picking one that actually fits your workflow. It should help you solve problems faster, not create new ones.

Here’s what to look for in an ideal LLM:

✅ Generates accurate, context-aware code and supports code completion across multiple programming languages, meeting standardized benchmarks
✅ Offers fast responses with low latency, even when handling complex coding tasks
✅ Works seamlessly inside popular IDEs, so you don’t need to switch between tools
✅ Detects bugs and explains syntax errors to improve your overall code quality
✅ Provides clear documentation, tutorials, and pricing that work for real teams

The best LLMs for coding should support real coding workflows and deliver practical utility across every stage of software development.

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The Best 13 LLMs for Coding

With dozens of large language models claiming to support code generation, finding the right one for your use case can be overwhelming. 

So, here’s a list of the best LLMs for coding, based on their performance across coding tasks and real-world usability.

1. ClickUp (Best for generating code snippets and software project management)

As one developer on Reddit put it,

That’s a valid concern with many large language models, especially due to short-term memory or disconnected prompts. But ClickUp addresses this limitation by embedding AI-powered code generation directly within a structured, context-rich workspace.

Generate and manage code with ClickUp Brain

ClickUp Brain transforms how developers interact with their work. Using natural language, you can describe a function or coding task, and the AI will generate code snippets that match your needs.

What sets ClickUp apart is its use of AI Agents that act on live workspace data, allowing developers to automate repetitive coding tasks, assign reviewers, or trigger updates based on real-time task changes.

Top ClickUp Brain features also include support for code completion and explanations, and even help identify potential bugs or logic errors. For example, a developer building a Python-based data parser can type “generate a function to extract date and price from a JSON file,” and ClickUp Brain returns clean, structured output—ready to test.

In fact, by managing end-to-end game development in ClickUp, Yggdrasil has cut total development costs by $120,000, increased productivity by 37%, and lowered development-related expenses by 30%.

Sync seamlessly with Git tools with ClickUp Integration

ClickUp connects with GitHub, GitLab, and Bitbucket, allowing developers to sync pull requests, branches, and commits with tasks automatically. 

This ensures tighter alignment between code and project goals. For example, when a dev pushes a hotfix, the task it relates to can update its status instantly.

Code block formatting for clean communication using ClickUp Docs

Sharing code snippets with product or QA teams can get messy in typical task managers. ClickUp solves this with code block formatting and syntax highlighting inside ClickUp Docs, comments, and even task descriptions.

For example, you can embed versioned pseudocode in Docs during sprint planning or add Python examples inline with test specs for reviewers to reference.

Reporting tools built for engineering visibility with ClickUp Dashboards

ClickUp Dashboards give engineering managers and product owners real-time visibility into sprint progress, code quality trends, and developer throughput. 

Custom charts can show how many bugs were reopened in the last sprint, which devs are overloaded, or how long PRs are taking to merge. This is critical for managing large codebases and optimizing team performance over time.

With low-latency dashboards and time tracking tied to each task, dev teams can eliminate guesswork and focus on shipping high-quality code faster.

Templates and ClickUp Automation for recurring development workflows

If your team spans product, engineering, design, and QA and needs a single source of truth for building software, ClickUp’s Software Development template is your best bet.

This software development template helps cross-functional teams align on a single workflow, making it easier to plan roadmaps, ship features, and fix bugs without switching tools.

You can even use ClickUp Automations to assign reviewers when a GitHub PR is linked or trigger standup reports when a sprint ends. These features help enforce structure without slowing teams down.

ClickUp best features

• Generate and explain code snippets with ClickUp Brain using plain language
• Sync pull requests and commits with tasks through GitHub and GitLab integrations
• Use code block formatting for clean, readable snippets across Docs and comments
• Track sprint velocity, bug counts, and team performance with real-time dashboards
• Automate task assignments, sprint updates, and more with flexible no-code rules

ClickUp limitations

• Steeper learning curve due to the depth of features and customization options
• Some developer-specific use cases may still require external dev tools for CI/CD or code testing

ClickUp pricing

ClickUp ratings and reviews

• G2: 4.7/5 (6,000+ reviews)
• Capterra: 4.7/5 (3,000+ reviews)

What users have to say about ClickUp

A G2 review says:

2. Claude 3.7 Sonnet (Best for advanced reasoning and real-world coding tasks)

Claude 3.7 Sonnet is built for developers tackling more than just code completion. If you’re debugging legacy systems, planning full-stack architecture, or have multiple tools open on your PC, Claude brings both speed and structure to your process.

Claude’s Extended Thinking Mode is one of its standout capabilities. Developers can toggle between rapid responses and step-by-step reasoning for problems that demand deeper analysis. This feature is great for learning how to use AI in test-driven software development, recursive logic, or large-scale refactoring.

The Extended Thinking Mode also significantly boosts performance on coding benchmarks, such as SWE-bench Verified and TAU-bench, where Claude 3.7 outperforms all prior versions.

Claude 3.7 Sonnet best features

• Enable Extended Thinking Mode to improve accuracy on complex coding tasks, debugging, and algorithmic reasoning
• Use Claude Code via CLI to edit files, write tests, run commands, and collaborate directly from your terminal
• Connect to GitHub repositories and work across actual project files for structured output and reliable code changes
• Achieve state-of-the-art results on SWE-bench and TAU-bench, excelling in agentic tool use and advanced reasoning capabilities
• Maintain context across sessions for long, multi-step engineering workflows or continuous improvement cycles

Claude 3.7 Sonnet limitations

• Extended Thinking Mode is locked behind paid plans, reducing access for free-tier users
• Still evolving in real-time collaborative features when compared to full-stack platforms like ClickUp

Claude 3.7 Sonnet pricing

• Free
• Pro: $20/month
• Max: $100/month

Claude 3.7 Sonnet ratings and reviews

• G2: 4.4/5 (50+ reviews)
• Capterra: 4.5/5 (20+ reviews)

What users have to say about Claude 3.7 Sonnet

This G2 review highlighted:

3. GPT-5 (Best for fast, general-purpose code generation across multiple languages)

If you’re moving quickly across design, development, and deployment, GPT-5 offers the balance of speed and accuracy that most developers need in real time.

GPT-5 can generate code, explain logic, complete unfinished functions, and handle code snippets in multiple programming languages, showcasing the power of artificial intelligence. Developers often use it to solve mostly basic Python problems, convert logic into executable code, or write helper functions based on plain-language descriptions.

Plus, this AI platform performs well in debugging and is easily accessible, too.

GPT-5 best features

• Generate and explain code across Python, JavaScript, Java, and other popular programming languages
• Complete partial functions and solve basic coding problems with high accuracy
• Identify syntax issues and improve code quality through inline suggestions
• Handle code completion and documentation based on natural language prompts
• Available for free through ChatGPT with faster response times than previous GPT-4 models

GPT-5 limitations

• Cannot connect to GitHub or directly manage project files
• Less effective than specialized models on advanced coding benchmarks like SWE-bench

GPT-5 pricing

• Free
• Go: $4/month
• Plus: $20/month per user
• Pro: $200/month per user

GPT-5 ratings and reviews

• G2: 4.7/5 (790+ reviews)
• Capterra: 4.5/5 (190+ reviews)

What users have to say about GPT-5

This Reddit review highlighted:

4. Gemini (Best for integrating code with web, app, and cloud-based development tasks)

Unlike other models that operate in isolation, Gemini can reference Google Docs, Sheets, and even Drive files to support more collaborative, context-aware coding tasks.

This makes it especially useful for engineers working closely with product teams, data analysts, or content workflows.

Moreover, Gemini 2.5 handles code generation, explanation, and code completion across popular programming languages like Python, JavaScript, Java, and more. It’s built to help with complex coding tasks such as API scaffolding, data transformations, and cloud deployment scripting.

Gemini best features

• Generate, explain, and complete code across Python, JavaScript, and other major programming languages
• Connect to Google Workspace apps to inform code responses with live data or documentation context
• Manage and reason over complex code and multiple files using native file upload and Drive linking
• Support software development use cases including backend automation, API integration, and Google Cloud deployments
• Enable structured output and detailed formatting for documentation, workflows, and process automation

Gemini limitations

• Requires a Google Workspace account for full integration features
• Still less widely adopted than GPT-4 or Claude in open-source and developer forums

Gemini pricing

• Free
• Google AI Pro: $19.99/month per user
• Google AI Ultra: $249.99/month per user

Gemini ratings and reviews

• G2: 4.4/5 (170+ reviews)
• Capterra: Not enough reviews

What users have to say about Gemini

This G2 review captured:

5. Replit Code (Best for end-to-end app development with AI-powered automation)

Imagine you’re a solo developer with a deadline looming. You need to design a login flow, connect a database, and write deployment scripts that typically span days across different software development tools.

With Replit Code, you open your browser and describe what you need in natural language. Within minutes, the AI agent generates the backend code, sets up authentication, and even suggests deployment configs.

Powered by Claude 3.5 Sonnet and GPT-4, this AI code tool combines code completion, debugging, and AI-powered automation.

Replit Code best features

• Automate project scaffolding, bug fixes, and feature builds using Replit Agent
• Access both Claude Sonnet and GPT-4o for code generation, debugging, and code completion
• Write, deploy, and host apps in multiple programming languages—all from a single interface
• Secure cloud environment with built-in database, auth, and integration modules
• Support for team features like SSO, role-based access control, and private deployments

Replit Code limitations

• Credit-based pricing can become costly during complex development iterations
• LLMs sometimes fail to handle detailed debugging or complex instructions reliably
• Lacks seamless GitHub repo syncing for large, modular codebases

Replit Code pricing

• Starter: Free
• Replit Core: $25/month per user
• Teams: $40/month per user
• Enterprise: Custom pricing

Replit Code ratings and reviews

• G2: 4.5/5 (110+ reviews)
• Capterra: 4.4/5 (80+ reviews)

What users have to say about Replit Code

This G2 review praised:

When you’re managing fast-moving sprints, alignment isn’t a one-time act—it’s a living system. That’s where ClickUp Brain and ClickUp Brain MAX help.

ClickUp Brain lives inside your workspace, surfacing blockers, missed dependencies, and context you might’ve overlooked—all while keeping every conversation and task connected.

Meanwhile, ClickUp Brain MAX brings those same capabilities to the desktop with Talk-to-Text—letting you capture ideas, sprint notes, or post-mortem insights hands-free. Together, they make collaboration between developers and PMs effortless, translating every update or discussion into a structured, actionable context that keeps the roadmap aligned.

6. Mistral AI (Best for open-source, enterprise-ready AI customization)

Most developers and data teams face a common trade-off: choose powerful, large language models with zero visibility into how they work, or settle for open-source options that lack performance.

Mistral AI breaks that deadlock. The code editor delivers high-performing, fully transparent LLMs that you can customize, fine-tune, and deploy on your terms.

Its open-weight models—like Mistral 7B and Mixtral 8x7B—are designed for teams that want to self-host, integrate with existing stacks, and fine-tune on proprietary datasets.

Mistral AI best features

• Support multimodal, multilingual use cases across code, documents, and voice
• Allow on-premise, cloud, and hybrid deployment with complete data control
• Build AI agents that orchestrate real-time actions using your apps and APIs
• Fine-tune open-source models (Mistral 7B, Mixtral 8x7B, etc.) for specialized use
• Enable 128K context window for complex, long-form reasoning tasks

Mistral AI limitations

• Offer limited plug-and-play integrations compared to more mature ecosystems
• Require technical expertise for fine-tuning or on-prem deployment
• Reserve the most advanced models for commercial/API access, not open weights

Mistral AI pricing

• Free
• Pro: $14.99/month per user
• Team: $24.99/month per user
• Mistral Code: Custom pricing
• Enterprise: Custom pricing

Mistral AI ratings and reviews

• G2: Not enough reviews
• Capterra: Not enough reviews

What users have to say about Mistral AI

This G2 review shares:

7. DeepSeek (Best for open-source developers who need deep code reasoning with complete model control)

DeepSeek is one of the few models that can generate WordPress plugins, debug JavaScript routines, and rewrite regular expressions with solid logic.

Unlike many generic code generators, DeepSeek goes beyond surface-level output and is capable of building full plugin structures, rewriting functions with edge-case validation, and tracking logic across long prompts.

If your team needs a transparent, developer-focused LLM that handles complex coding tasks without locking you into a proprietary ecosystem, DeepSeek is worth considering.

DeepSeek best features

• Support complex coding tasks with high reasoning accuracy
• Offer complete transparency with open-source model access
• Execute code generation, debugging, and plugin development reliably
• Enable agentic workflows with JSON output and function calling
• Maintain long-range context with a 64K token window

DeepSeek limitations

• Struggles with niche tools like AppleScript or Keyboard Maestro
• Generates overly verbose outputs that may require refinement
• Requires a +86 phone number for signup in some regions

DeepSeek pricing

• Free trial available
• Pro/Team: Pricing is usage-based token fees
• Enterprise: Custom pricing

DeepSeek ratings and reviews

• G2: Not enough reviews
• Capterra: Not enough reviews

What users have to say about DeepSeek

This Reddit review noted:

8. Code Llama (Best for open-source coding with flexible deployment)

Not every developer wants to rely on proprietary models for sensitive code tasks.

Code Llama by Meta is a powerful open-source large language model built on Llama 2, designed specifically for code generation, debugging, and instruction-following.

Teams can deploy high-performing LLMs without vendor lock-in, as Code Llama is available in multiple sizes up to 70B parameters and offers variants for Python code and natural language instructions.

Code Llama best features

• Support multiple code tasks, including generation, completion, and debugging
• Enable fill-in-the-middle prompting for editing existing code
• Offer specialized variants like Code Llama—Python and Code Llama—Instruct
• Handle long context windows (up to 100K tokens in some variants)
• Allow local deployment and fine-tuning for private environments

Code Llama limitations

• Lack of built-in tooling or hosted playgrounds
• Requires technical setup for inference and model serving
• May underperform on domain-specific tasks compared to tuned proprietary models

Code Llama pricing

• Free

Code Llama ratings and reviews

• G2: Not enough reviews
• Capterra: Not enough reviews

9. LLaMA (Best for open-source AI experimentation at scale)

For individual developers and indie builders, one of the biggest hurdles in AI is usability, often due to insufficient training data.

LLaMA provides robust reasoning, coding, and multilingual capabilities, yet achieving these capabilities often necessitates navigating various obstacles, such as model downloads, framework compatibility, GPU constraints, and API toggling.

Meta presents LLaMA as a cutting-edge, open-source alternative to proprietary LLMs, capable of multimodal understanding.

LLaMA best features

• Support multimodal input (vision + text) via LLaMA 4 preview releases
• Offer native long-context reasoning with up to 128K context
• Achieve competitive performance in benchmarks like LiveCodeBench and GPQA
• Enable advanced multilingual support and math reasoning
• Provide open-weight models for full customization and local deployment

LLaMA limitations

• Require complex setup with heavy GPU demands (A10 or higher recommended)
• Developer documentation and tooling are fragmented and not beginner-friendly
• Implicit push toward Meta’s paid APIs, even for open-source users

LLaMA pricing

• Free 
• Custom pricing

LLaMA ratings and reviews

• G2: 4.3/5 (140+ reviews)
• Capterra: Not enough reviews

What users have to say about LLaMA

This G2 review featured:

10. Grok (Best for lightning-fast reasoning and contextual depth)

If you’ve ever waited on an AI tool to finish a simple request like fixing a bug or completing a script, you know how frustrating sluggish responses and shallow answers can be. That’s where Grok stands out.

Built by xAI and integrated into the X platform, it delivers fast, human-like reasoning that feels more like pair programming than querying a chatbot.

Whether you’re debugging a Python script, generating content, or translating logic across languages, Grok moves with you.

Grok best features

• Deliver near-instant responses to complex coding queries and logic puzzles
• Support advanced context retention for better continuity in iterative coding sessions
• Handle multilingual coding documentation and cross-language translation tasks with ease
• Generate full code snippets and business logic in coding tools like Python or JavaScript with minimal prompts
• Analyze abstract reasoning tasks such as sarcasm detection and long-form pattern recognition

Grok limitations

• Produce overly cautious or generic output in high-stakes or creative edge cases
• Depend on paid API access or platform integration for production-level use
• Lack standout performance in image generation compared to specialized tools

Grok 3 pricing

• Super Grok: $30/month per user
• Super Grok Heavy: $300/month per user

Grok 3 ratings and reviews

• G2: Not enough reviews
• Capterra: Not enough reviews

What users have to say about Grok

This G2 review highlighted:

11. GitHub Copilot (Best for seamless in-IDE automation and code edits)

Writing repetitive code blocks, debugging someone else’s functions, or just trying to keep up with daily tickets can drain your focus.

GitHub Copilot lightens that load by acting like an always-available teammate inside your IDE.

Whether you’re writing from scratch or editing across multiple files, this AI tool for developers delivers real-time suggestions, automatically detects ripple effects, and lets you approve changes with a click, directly within your environment.

GitHub Copilot best features

• Offer real-time code suggestions that learn your coding style as you work
• Enable agent mode to plan, write, test, and deliver pull requests autonomously
• Allow in-editor prompts for multi-file edits and consistent project-wide changes
• Integrate with popular IDEs like VS Code, Visual Studio, Xcode, JetBrains, and Neovim
• Support multiple model options, including Claude Sonnet, GPT-4.1, and Gemini 2.5 Pro
• Provide code review capabilities that flag bugs and suggest fixes before manual QA

GitHub Copilot limitations

• Require structured codebases for best performance
• Generate suggestions that still need human review
• Offer less value for solo developers who write and understand all their own code
• Limit completions in the free plan (2,000/month)

GitHub Copilot pricing

• Free
• Pro: $10/month per user
• Pro+: $39/month per user

GitHub Copilot ratings and reviews

• G2: 4.5/5 (140+ reviews)
• Capterra: 4.7/5 (20+ reviews)

What users have to say about GitHub Copilot

12. Tabnine (Best for secure, private AI code assistance)

Developers often struggle with privacy concerns, particularly when sharing sensitive code with AI tools. Every engineer has had that uneasy moment wondering if the next autocomplete suggestion might leak proprietary logic.

Tabnine is designed to put those worries to rest. It offers an on-premise, air-gapped solution that keeps your code exactly where you want it.

With models that are exclusively trained on permissively licensed code, Tabnine is your trusted partner for fast, context-aware code completions that increase developer productivity.

Tabnine best features

• Support fully private, air-gapped deployments with zero data retention
• Generate and explain code with context-aware suggestions tailored to your projects
• Build AI agents for testing, documentation, and Jira implementation
• Validate code against internal standards with custom review agents
• Use multiple LLMs or fine-tune Tabnine models on your own repositories

Tabnine limitations

• Limited features in the free or basic plans
• Can consume more system resources during local model execution
• Requires setup and IT support for enterprise-level deployment

Tabnine pricing

• Tabnine Agentic Platform: $59/month per user (billed annually)

Tabnine ratings and reviews

• G2: 4.0/5 (40+ reviews)
• Capterra: Not enough reviews

What users have to say about Tabnine

This G2 review shares:

13. WizardLM (Best for instruction-following and reasoning across complex code tasks)

Writing clean code is hard enough when it comes to explaining and testing it. Avoid the added pressure of maintaining it whenever possible.

WizardLM steps in as an open-source LLM fine-tuned specifically for instruction-following and logical reasoning, making it a strong coding assistant for devs who want more clarity in complex tasks without relying on proprietary black boxes.

WizardLM best features

• Interpret vague or abstract prompts with logical, stepwise reasoning
• Follow complex instructions for multi-turn coding tasks
• Break down nested code logic in a clear, readable format
• Support open-ended Q&A and code explanations across many languages
• Enable offline, secure deployment as a fully open-source solution

WizardLM limitations

• Performance may lag behind proprietary models like GPT-4 or Claude 3.5
• Struggles with highly domain-specific codebases without fine-tuning
• Slower inference speeds on larger models unless optimized

WizardLM pricing

• Custom pricing

WizardLM ratings and reviews

• G2: Not enough reviews
• Capterra: Not enough reviews

What users have to say about WizardLM

This Reddit review highlighted:

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Additional Helpful Tools

Here are three additional LLM tools for coding that are not covered in the blog but are similar in purpose and functionality:

• Amazon CodeWhisperer: Offers code suggestions tailored to AWS services, built-in security scans for vulnerabilities, and seamless integration with IDEs like VS Code and JetBrains
• Cody by Sourcegraph: Integrates deeply with your codebase to answer questions about code, generate explanations, and refactor logic
• Magic.dev: Lets you describe software in natural language and returns deployable full-stack code scaffolds

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LLM(e) Tell You a Secret: Coding Gets Easier with ClickUp

LLMs have completely redefined how modern teams approach software development.

However, as this guide has demonstrated, not all LLMs are equal.

Some excel at reasoning but struggle with real-time collaboration. Others deliver swift code suggestions but lack integration with your actual development workflow. Most require developers to jump between IDEs, chatbots, and task managers just to get one clean output.

ClickUp distinguishes itself in this regard.

By embedding LLM-powered features directly into your project workspace, ClickUp lets teams generate code, manage tasks, and collaborate in one place. ClickUp eliminates the need for disconnected prompts—no context switching.

If your current toolchain is slowing you down, it might be time to sign up for ClickUp!

Everything you need to stay organized and get work done.

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