Amp vs Ollama
A detailed comparison to help you choose between Amp and Ollama.
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Verdict: Ollama wins
Ollama scores 4.6/5, edging out Amp at 3.8/5. Developers and privacy-conscious teams who want open-weight models running on their own hardware with a clean local API, and who are comfortable in a terminal.
Amp AI coding agent by Anthropic alumni | Ollama Run large language models locally | |
|---|---|---|
| Rating | 3.8 (1 review) | 4.6 (1 review) |
| Pricing Model | freemium | free |
| Starting Price | Free tier available | Free |
| Best For | Senior, terminal-comfortable developers who want unattended agents on remote machines and are happy to fund them with linked subscriptions and their own keys. | Developers and privacy-conscious teams who want open-weight models running on their own hardware with a clean local API, and who are comfortable in a terminal. |
| Free Tier | ||
| API Access | ||
| Team Features | ||
| Open Source | ||
| Tags | free tierbyok | api accessopen sourcefree tier |
| Visit Amp → | Visit Ollama → |
Amp
Pros
- + Orb workflow is real: I dispatched an environment-setup and test-green task to a remote orb, closed the laptop, and resumed from another machine with the work done
- + No Amp token fees or limits — BYOK and linked ChatGPT/Claude/X subscriptions run at subscription cost, and self-hosted orbs and own runners are free on every tier
- + Teams workspaces add SSO (SAML/OIDC), shared billing, pooled credits and shared BYOK routing at no extra seat charge
- + Transparent per-action economics: credits at provider API prices with no markup for individuals, published tier allowances (45,000 minutes on Megawatt), and clearly stated orb sizes
- + Genuinely unattended parallelism — agents in separate orbs with their own repo clones and tooling, so no worktree juggling or port conflicts in my runs
Cons
- - Orb minutes burn while agents idle: a slow install consumed my allowance at the same per-minute rate as active work, and I found no per-workload spend cap
- - Hobby has no included orb time or agent usage — 'free' means your tokens and your own machines
- - Custom endpoint URLs and gateway routing (OpenRouter, Bedrock, Azure Foundry) are early access for paid tiers behind an experimental flag, with no public rollout date
- - Homegrown vocabulary (orbs, portals, the Dial) and a terminal-first surface make onboarding deliberately steep for GUI-oriented developers
- - Amp's published 60–65% average usage discount is a vendor claim without a stated basis; included usage does not roll over month to month
Ollama
Pros
- + Local inference is free and unlimited — cost is hardware and electricity, and prompts never leave the machine (OLLAMA_NO_CLOUD=1 disables the cloud path entirely)
- + OpenAI- and Anthropic-compatible endpoints at localhost:11434 meant existing SDK code worked for me after a single base_url change, including JSON-schema structured output
- + Install-to-first-chat took about two minutes on my M-series Mac with a quantized 8B model, and ollama ps shows the GPU/CPU split honestly
- + Huge ecosystem: ~183k GitHub stars, setup docs for 20+ agents and editors, official Python and JS libraries
- + v0.40.x MLX default made prompt processing measurably faster on Apple Silicon in my runs, and releases ship every few days
Cons
- - Memory-tiered default context window truncates long inputs out of the box — I had to raise num_ctx explicitly in a coding-agent setup
- - Quality ceiling is your hardware: a local 7B quant visibly trails frontier hosted models on hard reasoning
- - No end-user polish — quantization, context sizing, and memory management stay your problem, and CPU-only machines run slowly
- - Fast release cadence creates churn for pinned deployments (e.g. v0.34.1 moved GGUF creation out to llama.cpp tooling)
- - Cloud Team plan pricing conflicts across sources ($500/mo flat vs $25/seat with 5-seat minimum); Max signups reported paused at times
Frequently Asked Questions
Which is better, Amp or Ollama?▼
Ollama scores higher at 4.6/5 vs 3.8/5 for Amp, making it the better-rated option in our comparison.
What is the difference between Amp and Ollama?▼
Amp: Amp is a coding agent and development environment from Sourcegraph that runs unattended tasks in the cloud or locally through a CLI. Ollama: Ollama enables you to run open-source large language models locally on your machine, providing privacy and offline access to AI capabilities.
Is Amp or Ollama more affordable?▼
Amp starts at €0/mo, Ollama starts at €0/mo. Check the comparison table above for current pricing.
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