GitHub Copilot charges $10/month for individuals, but its real value lies in the new model flexibility. You are no longer forced to use OpenAI’s default models; you can now drive the assistant with Anthropic’s Claude 3.7 Sonnet or Google’s Gemini 2.0 Flash directly inside VS Code. For a developer making 500 autocomplete calls and 20 chat queries daily, the $10 flat fee is a steal compared to paying consumption rates on an API, which could easily run $20–$30/month for equivalent usage of high-end models like Sonnet.
The tool has evolved from a simple autocomplete engine into a comprehensive workflow assistant. The new "Copilot Edits" feature is a direct answer to Cursor’s Composer, allowing you to edit multiple files simultaneously via natural language. It works well: you can ask it to "refactor the auth logic and update all controllers," and it will stage changes across your workspace. The latency is excellent, particularly for autocomplete, which feels near-instantaneous (sub-200ms) thanks to aggressive caching and smaller speculative models running alongside the heavy hitters.
However, Copilot still suffers from "plugin syndrome." Unlike Cursor, which is a forked VS Code that controls the entire editor state, Copilot is strictly an extension. It fights for screen real estate, occasionally loses context of the file tree, and requires awkward mode switching (Chat vs. Edits vs. Inline). The "Free" tier is essentially a trial; the 2,000 completion limit will be exhausted by a full-time developer in less than two weeks.
If you are in a corporate environment, this is the only choice your security team will likely approve. It offers IP indemnity, SOC2 compliance, and zero-retention guarantees on the Business plan ($19/user/month). For individual power users who want the AI to "own" the editor, Cursor is a superior product. But if you want reliable, compliant, multi-model AI without changing your IDE, Copilot has successfully caught up to the competition.
Pricing
The "Free" tier is misleadingly named—it's a trial. You get 2,000 code completions and 50 "premium" requests (Chat/Agent) per month. A typical developer hits 'Tab' 50-100 times a day, meaning the free completions will vanish in roughly 3 weeks of work. The 50 premium requests are barely enough for two days of debugging. The $10/month Pro plan is the mandatory baseline for real work, offering unlimited completions and 300 premium requests. Compared to Cursor ($20/mo) or paying per-token API costs, the $10 Pro plan is arguably the best value-for-money in the market if you don't need deep context.
Technical Verdict
Reliability is rock solid with 99.9% uptime. The extension is easy to install but heavy; it runs a local server for context indexing which can spike RAM usage in large repos. Autocomplete latency is best-in-class (~150ms). API integration via the SDK is minimal as it's primarily an IDE tool, but the CLI extension brings AI to your terminal effectively.
Quick Start
# Install: pip install python-dotenv openai
import os, openai
# Copilot works via IDE, but you can access models via GitHub Models API if enabled
client = openai.OpenAI(api_key=os.getenv("GITHUB_TOKEN"), base_url="https://models.inference.ai.azure.com")
response = client.chat.completions.create(
model="gpt-4o", messages=[{"role": "user", "content": "Refactor this class."}]
)
print(response.choices[0].message.content)Watch Out
- The 2,000 completion limit on the free tier includes every accepted 'Tab', not just full lines.
- 'Copilot Edits' (multi-file) is separate from 'Chat' and often requires manually adding files to context.
- Switching models (e.g., to Claude) is not sticky; it often reverts to GPT-4o in new sessions.
- JetBrains integration lags behind VS Code features by several months (e.g., Edit mode is limited).