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Compare/Poolside vs Warp

PoolsidevsWarp

Generated from the two spec rows. Green marks the better value where a spec has a clear direction. Everything else is just different.

Poolside
poolside · Terminal agent
#15MCP
Panel
6.9
0 spec wins
Reliability
6.8
Usefulness
7.0
Cost
6.5
Longevity
7.2

“One of its three network policies is named unsafe-allow-all, which is at least the most clearly labelled decision on this board.”

Warp
Warp · Terminal agent
#20OSSMCP
Panel
6.5
2 spec wins
Reliability
6.5
Usefulness
6.7
Cost
5.5
Longevity
7.2

“Scored 75.8 on SWE-bench Verified with a best-of-k wrapper, which is also how most of us get through code review.”

Spec by spec

SpecPoolsideWarp
Architecture
CategoryTerminal agentTerminal agent
Runslocal, sandbox, cloudlocal, cloud
Platformsmacos, linux, windowsmacos, linux, windows
Context window1M tokens on Laguna S 2.1, 256k on XS 2.1 and M.1not documented
Protocols
MCP clientYesYes
MCP serverNoNo
Capabilities
Runs terminal commandsYesYes
Multi-file editsYesYes
Git operationsYesYes
Browser controlNoWeb search and fetch are documented; there is no DOM-level browser automation. YesComputer Use environments bundle Chromium plus the Playwright CLI and can attach over CDP, so the agent navigates, clicks, fills forms and reads pages.
Sandboxed executionYesTool commands run inside a container on your machine and need a local Docker engine; network policy is off, allow-list or unsafe-allow-all, enforced through a proxy container. YesCloud runs execute in a containerized sandbox built from a Docker image with no access to the local machine; local interactive sessions are not sandboxed.
Multi-agent orchestrationYesYes
Headless / CI modeYes`pool exec --prompt ... --output json` with POOLSIDE_API_KEY, plus a documented GitHub Actions integration. Yes
Models
BackboneLaguna S 2.1, Laguna XS 2.1, Laguna M.1GPT, Claude, Gemini, Grok, open-weight models via Fireworks
Bring your own modelYesYesAny OpenAI-compatible endpoint (OpenRouter, LiteLLM, an internal gateway) plus BYO Anthropic, OpenAI or Google keys and custom routers.
Local modelsYesDocumented local-run guides for Ollama and vLLM on Metal, plus full on-premises and air-gapped deployment. YesOllama, LM Studio, vLLM and llama.cpp are supported through the custom inference endpoint, but only when exposed at a public URL via a tunnel, since localhost and private addresses are rejected.
Cost
Pricing modelmixedmixed
Starts atn/a$20/mo
Free tierYesYes
Bring your own keyYesYes
Openness
Open sourceNoYes
LicenseproprietaryAGPL-3.0
GitHub starsn/a65,338

Which one would each critic pick

CriticPoolsideWarpPick
El Juez——not enough reviews
El Amigo6.87.3Warp — Use Warp if you want an agent in the terminal you already open every morning, with a standalone CLI and cloud agents when you outgrow it, and read the credit table before you pick a plan.
El Crítico6.56.0Poolside — Isolation needs a container engine running on the machine and enforces network policy through a proxy container, which is a configuration rather than a boundary.
El Profesor6.56.0Poolside — The vendor trains its own model family and publishes no evaluation of it anywhere on the row, which is a conspicuous silence for a company selling its own inference.
La Inversora7.06.8Poolside — Training your own models and selling deployments into other people's data centres is a capital-intensive bet on the one segment that cannot buy from a lab directly.
La Jefa7.06.0Poolside — It runs inside our own network, including air-gapped, on the Kubernetes platforms we already operate, and the enterprise price is a sales conversation.
El Hacker7.56.8Poolside — The client is proprietary and the model weights are published under OpenMDW-1.1 and Apache-2.0, which is the exact opposite of everyone else on this board.

Picks are derived from each critic's own scores. Humans vote on matchups on the duels page.

Want a third column? The compare tool handles any two agents. Three-way comparisons are on the roadmap once the spec rows are all verified.