Compare / Amp vs OpenAI Codex
Head-to-head
Amp vs OpenAI Codex.
Side-by-side on ratings, pricing, pros, cons, and the honest take on which to pick. Both are in our coding agent category — direct competitors.
| Amp | OpenAI Codex | |
|---|---|---|
| Rating | 4.0 / 5 | 3.5 / 5 |
| Category | Coding Agent | Coding Agent |
| Tech level | developer | developer |
| Open source | No | Yes (Apache 2.0) |
| Pricing | Free tier with meaningful usage allowance. Paid tiers $19–$49/month for individuals. Enterprise pricing for teams bundled with Sourcegraph Code Search. Token-based usage on top of subscription tiers. | Pro $20/month base + usage-based credits ($20/mo of frontier model included). Pro+ $60/month (3× usage). Ultra $200/month (20× usage). No free tier. Rolling 5-hour credit limits frustrate heavy users. |
| Best for | Engineering teams already paying for Sourcegraph Code Search who want to add an AI agent that reuses the existing codebase index. Strong for large enterprise codebases (1M+ lines) where context retrieval is the bottleneck. Free tier is generous enough for individual evaluation. | Developers committed to GPT-5+ models who want a Claude Code equivalent without leaving the OpenAI ecosystem. Teams that prioritise the most recent OpenAI features. |
| Not for | Teams not on Sourcegraph — the standalone story is less differentiated than Claude Code or Augment Code. Solo developers and small projects where the codebase-context advantage doesn't compound. Builders who want a simpler CLI or terminal-first experience. | Anyone who needs predictable monthly costs (rolling credit limits cause unpredictable workflow blocks) or who wants to use Claude or Gemini in their workflow. |
Our verdict on Amp
Sourcegraph's agentic coding tool built on years of code-search investment. The codebase-context story is genuinely differentiated for teams already running Sourcegraph at scale. As a standalone vs Cursor or Claude Code, it's solid but less obvious — the strategic moat is the Sourcegraph install base, not the agent itself.
Full Amp review →Our verdict on OpenAI Codex
3M weekly active users and 70%+ MoM token growth. Rolling 5-hour credit limits are a real operational pain. Best if you're in the OpenAI ecosystem.
Full OpenAI Codex review →Amp
What works
- Built on Sourcegraph's mature code-search and indexing infrastructure
- Free tier with meaningful usage allowance for individual evaluation
- Strong codebase-context story without separate indexing setup
- Native integration with Sourcegraph Code Search
- Sourcegraph's enterprise compliance (SOC 2, on-prem options) carries over
- Cross-repo awareness that single-repo tools miss
- Active product velocity — feature gap vs Cursor is closing fast
What doesn't
- Standalone value less compelling than Claude Code or Augment Code for non-Sourcegraph teams
- Newer to agentic coding (launched mid-2025) than competitors with longer track records
- Smaller community vs Cursor or Copilot
- Locked into Sourcegraph as the indexing/context layer
- Best fit narrows to enterprise teams already paying for Sourcegraph
- Editor support skews VS Code-centric; JetBrains story less mature
OpenAI Codex
What works
- Fastest-growing tool in the category — 3M weekly active users
- Multi-agent v2 workflows with inter-agent messaging
- Integrated terminal reader — sees stdout/stderr from your dev server
- Rust-based for speed and efficiency
- Strong cross-platform: Windows native, macOS, Linux, WSL2
- Open source CLI — Apache 2.0 licensed
What doesn't
- Rolling 5-hour credit limits cause unpredictable workflow blocks
- OpenAI model lock-in — can't use Claude or Gemini
- No model selection — system chooses automatically
- Pricing increased ~20% in 2026 even though models got more efficient
- MCP server support unclear — limited extensibility vs Claude Code
Which to pick
We'd default to Amp (4.0/5 vs 3.5/5) for most builders. Pick OpenAI Codex if you fit its best-for case specifically: developers committed to gpt-5+ models who want a claude code equivalent without leaving the openai ecosystem. teams that prioritise the most recent openai features.
Honest middle: most serious operators end up using more than one tool. If you're early in your AI agent journey, our five-question picker recommends a starting platform from your specific situation.
Common questions
Amp vs OpenAI Codex — which should I pick?
We rate Amp 4.0/5 vs 3.5/5 for OpenAI Codex. Amp wins for engineering teams already paying for sourcegraph code search who want to add an ai agent that reuses the existing codebase index. strong for large enterprise codebases (1m+ lines) where context retrieval is the bottleneck. free tier is generous enough for individual evaluation. — but pick OpenAI Codex if you fit its specific best-for case (Developers committed to GPT-5+ models who want a Claude Code equivalent without leaving the OpenAI ecosystem. Teams that prioritise the most recent OpenAI features.). See the head-to-head table above for the full breakdown.
Is Amp or OpenAI Codex cheaper?
Amp's pricing: Free tier with meaningful usage allowance. Paid tiers $19–$49/month for individuals. Enterprise pricing for teams bundled with Sourcegraph Code Search. Token-based usage on top of subscription tiers. OpenAI Codex's pricing: Pro $20/month base + usage-based credits ($20/mo of frontier model included). Pro+ $60/month (3× usage). Ultra $200/month (20× usage). No free tier. Rolling 5-hour credit limits frustrate heavy users. The right "cheaper" pick depends on usage volume and what's included — see the pricing row in the table above.
What's Amp best for?
Engineering teams already paying for Sourcegraph Code Search who want to add an AI agent that reuses the existing codebase index. Strong for large enterprise codebases (1M+ lines) where context retrieval is the bottleneck. Free tier is generous enough for individual evaluation.
What's OpenAI Codex best for?
Developers committed to GPT-5+ models who want a Claude Code equivalent without leaving the OpenAI ecosystem. Teams that prioritise the most recent OpenAI features.
Are Amp and OpenAI Codex direct competitors?
Yes — both are coding agent options. They target similar builders, which is why the head-to-head matters.
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