AI & LLM Coding Model Comparison

Compare LLM models for coding: Claude, GPT-4, Gemini, and open-source alternatives. Strengths, pricing, and use cases.

Overview

Different LLM models have different strengths for coding tasks. This comparison covers the major models available in 2025-2026 and their relative strengths for various programming tasks.

Model Comparison

Model	Context	Best For	Available In
Claude 3.5 Sonnet	200K	Large codebases, careful reasoning	Claude Code, Cursor, API
GPT-4o	128K	Multi-turn conversation, broad knowledge	Copilot, Cursor, ChatGPT, API
Gemini 1.5 Pro	1M+	Massive context, multimodal	AI Studio, select editors, API
DeepSeek Coder V2	128K	Code completion, self-hosting	Open-source, Ollama
Llama 3.1 405B	128K	Self-hosted, privacy, fine-tuning	Open-source, Ollama, API

Claude (Anthropic)

Strong at: large codebase understanding, careful reasoning, following complex instructions, and long-form code generation. 200K token context window. Available via API, Claude Code CLI, and integrated in Cursor. Best choice for complex refactoring and multi-file tasks.

GPT-4 / o1 (OpenAI)

Strong at: multi-turn conversations, broad knowledge, and tool use. o1 models add explicit chain-of-thought reasoning for complex logic. Available via API, ChatGPT, GitHub Copilot, and Cursor.

Open-Source LLMs

DeepSeek Coder V2

Excellent code completion and generation. 128K context. Strong performance for an open model.

Llama 3.1

Meta's open LLM. Available in 8B, 70B, and 405B sizes. Good for self-hosted coding assistance.

CodeLlama

Code-specialized Llama variant. Optimized for code completion, infilling, and instruction following.

StarCoder 2

Trained on The Stack v2. Strong at code completion across many languages. Good for fine-tuning.

Frequently Asked Questions

Which LLM is best for coding?

It depends on the task. Claude excels at large context and careful reasoning, GPT-4 is strong at multi-turn conversations, and Gemini has the largest context window. Try multiple models for your specific use case.

Are open-source LLMs good enough for coding?

For many tasks, yes. DeepSeek Coder V2, Llama 3.1, and CodeLlama are excellent for completions and simple tasks. For complex multi-file reasoning, commercial models still lead.