Amp vs Gptme (2026): Which Vibe Coding App Is Better?

Both are popular terminal coding agents. Here is how Amp and Gptme stack up on price, strengths and weaknesses, and which one we would pick.

Amp

Frontier coding agent for the terminal and editor, from the makers of Sourcegraph

8.2 /10

Pricing: Free plan, paid from $20/mo

Pros

Strong results on hard, multi-step tasks
Shared threads for team review
Subagents and AGENTS.md built in

Cons

Usage-based costs add up on large tasks
Fewer configuration knobs by design

Visit Amp ↗

Gptme

Provider-agnostic terminal AI agent with shell, Python, file and browser tools

7.5 /10

Pricing: Open source

Pros

Model-agnostic (Anthropic, OpenAI, Google, xAI, DeepSeek, OpenRouter, local llama.cpp) rather than locked to one vendor
Mature and actively maintained: MIT, ~4.4k stars, 4,500+ commits, recent v0.33.0 release (Aug 2026) adding sandboxed execution
Broad tool set out of the box: shell, Python REPL, incremental file patching, browser automation, vision, plus a plugin/skills/hooks system

Cons

Executes arbitrary shell and Python commands on your machine at the model's direction — real risk if run unsupervised without its guardrail features enabled
Autonomous/persistent-agent mode needs careful configuration (task selectors, pre-commit checks) to use safely

Visit Gptme ↗

Amp vs Gptme at a glance

	Amp	Gptme
Editor score	8.2 / 10	7.5 / 10
Pricing model	Freemium	Open source
Starting price	$20/mo	Free
Reader upvotes	0	0
Best for	terminal, agent	terminal-agent, cli, python
Agent Skills support	Yes	No
Subagents support	Yes	No
MCP support	Yes	No
AGENTS.md support	Yes	No
Plugins support	Yes	No
Hooks support	No	No
Rules support	No	No
Agent skills in this directory	47	0
Subagents & agents in this directory	9	3
MCP servers in this directory	72	0

Our pick

Amp edges it with a score of 8.2 versus 7.5. Amp is the better fit if you value: strong results on hard, multi-step tasks, shared threads for team review. Choose Gptme instead if you need: model-agnostic (anthropic, openai, google, xai, deepseek, openrouter, local llama.cpp) rather than locked to one vendor, mature and actively maintained: mit, ~4.4k stars, 4,500+ commits, recent v0.33.0 release (aug 2026) adding sandboxed execution.