MagenticLitevsRaven
Generated from the two spec rows. Green marks the better value where a spec has a clear direction. Everything else is just different.
MagenticLite
Microsoft · Agent harness
OSS
Panel
5.91 spec wins
- Reliability
- 5.3
- Usefulness
- 5.7
- Cost
- 8.3
- Longevity
- 4.3
“The previous frontier-model version still sits on its own branch, which is where good ideas go to remain technically reachable.”
Raven
EverMind AI · Agent harness
OSS
Panel
6.23 spec wins
- Reliability
- 5.3
- Usefulness
- 6.3
- Cost
- 8.0
- Longevity
- 5.2
“It has a Sentinel that sends you proactive nudges, so the agent now has opinions about your afternoon.”
Spec by spec
| Spec | MagenticLite | Raven |
|---|---|---|
| Architecture | ||
| Category | Agent harness | Agent harness |
| Runs | local, sandbox | local, sandbox |
| Platforms | macos, linux, windows | macos, linux, windows |
| Context window | not documented | not documented |
| Protocols | ||
| MCP client | No | No |
| MCP server | No | No |
| Capabilities | ||
| Runs terminal commands | No | Yes |
| Multi-file edits | Yes | Yes |
| Git operations | No | No |
| Browser control | Yes | YesDeep Research performs web search and page reading via MiroThinker and returns a cited report; there is no general browser-automation tool documented. |
| Sandboxed execution | No | YesOnboarding asks for a sandbox or execution location, documented separately under docs/sandbox/usage.md. |
| Multi-agent orchestration | Yes | YesThe agent loop spawns subagents, and tracing records parent-child subagent runs. |
| Headless / CI mode | No | Yes |
| Models | ||
| Backbone | MagenticBrain, Fara | OpenAI, Anthropic, Gemini, OpenRouter, DeepSeek, MiniMax, Moonshot, Groq, Azure OpenAI, GitHub Copilot (OAuth), Codex (OAuth), Ollama, vLLM |
| Bring your own model | Yes | Yes |
| Local models | Yes | Yes |
| Cost | ||
| Pricing model | byok | byok |
| Starts at | n/a | $0/mo |
| Free tier | Yes | Yes |
| Bring your own key | Yes | Yes |
| Openness | ||
| Open source | Yes | Yes |
| License | MIT | Apache-2.0 |
| GitHub stars | 10,091 | 5,061 |
Which one would each critic pick
| Critic | MagenticLite | Raven | Pick |
|---|---|---|---|
| El Juez | — | — | not enough reviews |
| El Amigo | 6.0 | 6.5 | Raven — Pick it if you want an assistant that remembers last week; pick a plain terminal agent if you would rather start every session from a clean slate. |
| El Crítico | 5.3 | 5.8 | Raven — The README labels the project pre-alpha and warns that interfaces and configuration may change quickly, while the skill system rewrites its own definitions between runs. |
| El Profesor | 6.5 | 6.3 | MagenticLite — Two specialised models split the work, an orchestrator paired with a browser-driving model, on the argument that specialisation substitutes for scale, and no benchmark tests that argument. |
| La Inversora | 5.5 | 6.0 | Raven — A named startup with 3,746 stars, no paid tier and a deliberately local product, which is a large audience attached to nothing that bills. |
| La Jefa | 4.5 | 5.0 | Raven — It reaches users through twelve chat gateways, which is twelve places company code can leave through, and there is no console for sixty engineers behind any of them. |
| El Hacker | 7.8 | 7.8 | no preference |
Picks are derived from each critic's own scores. Humans vote on matchups on the duels page.