The AI that remembers — across sessions, across days, across every project you build together.
You've explained your stack, your team, your goals — three times this week. Three different chats. Each one starts from zero. Each one asks the same dumb questions.
You explain the project. You paste the same context. The AI nods, gives advice, and forgets everything the moment the tab closes.
Mavis remembers your past projects, your preferences, your tools, your wins, your bugs — and uses them as context for whatever comes next.
Real session recall from a real MiniMax user. The session IDs, titles, and queries below are pulled from actual platform data — not fabricated examples.
Memory is the headline. But Mavis also ships with a full creative + engineering toolkit — so every project lands, not just remembers.
Agent scope (this assistant's private memory) and user scope (shared across every agent you own). Topic files for structured knowledge. Daily memory auto-injected into every session.
Run shell, edit files, deploy servers. Bash, Python, Node — full Linux sandbox.
Spawn producer-vs-verifier teams. Independent audits. Retry cycles until it's right.
Text-to-image and image-to-image with reference photos. Up to 4K.
40+ languages, voice cloning, multi-speaker dialogue, emotion control, background music generation.
Text-to-video and image-to-video at 1080p. First-frame and last-frame reference modes. Up to 10s clips.
Real-time news, prices, facts. Reverse image search. Deep page extraction.
One-shot public URL for any static site. HTTPS included. Ready to share.
Transcribe, analyze, describe images, video, audio — full multimodal input/output.
These aren't demos. Each project was built, deployed, and is live right now — using session memory that persists across days of work.
Three concentric layers — daily injection, durable MEMORY.md, and structured topic files. Together they form the persistent context that survives every session boundary.
The last few memory entries get auto-injected into every new session's context. This is why Mavis "remembers" yesterday without any prompting.
Two scopes: agent (this assistant's private knowledge) and user (shared across all your agents). Persistent until manually edited.
For deep structured knowledge — workflow gotchas, deployment configs, API quirks. Loaded on demand. 30KB cap per topic.
Full-text keyword search across all memory layers. Plus dedicated topic index so Mavis knows where to look before reading bodies.
Not benchmarks. Not marketing. These numbers come from the actual platform session data of the user reading this page right now.
Memory isn't abstract — it's pattern, rhythm, and connection. These are real visualizations from this user's actual session data.
Mavis runs on MiniMax M3 — a model designed from the ground up for long-horizon agentic work. Here's how that compares to the usual suspects.
| Capability | Mavis / M3 | Typical chat AI | Typical coding copilot |
|---|---|---|---|
| Persistent memory across sessions | ✓ Both scopes | ✗ None | ◐ Workspace-only |
| Multi-modal input/output (text, image, audio, video) | ✓ Native | ◐ Limited | ✗ Text-only |
| Tool execution (shell, files, deploy) | ✓ Full sandbox | ✗ Read-only | ◐ Repo-scoped |
| Long-horizon planning (team mode, retries) | ✓ Native | ✗ Single-turn | ✗ Single-turn |
| Voice cloning & multi-speaker TTS | ✓ Built-in | ✗ None | ✗ None |
| Public deploy of generated sites | ✓ One-shot URL | ✗ None | ✗ None |
| Knowledge of recent world events | ◐ + web search | ◐ Varies | ✗ Static |
Mavis is already here. Open a new session, mention your project, and come back tomorrow — your context will be waiting.