agent · gaming
MoltQuest vs Voyager
55 fields both were evaluated on, 30 of them different — including where one discloses something the other does not. Every value links to the document it came from. 25 further fields are disclosed by neither and are listed at the end rather than tabled.
Assurance
| Field | MoltQuest | Voyager |
|---|---|---|
| Audit trail· | “the execution layer requires explicit auditing to verify what the agent is actually told.”moltquest.online · checked Aug 1, 2026 | Yes (feedback, errors, and self-verification logged implicitly) “iterative prompting mechanism that incorporates environment feedback, execution errors, and self-verification for program improvement”voyager.minedojo.org · checked Aug 1, 2026 |
| Explainability· | “the execution layer requires explicit auditing to verify what the agent is actually told.”moltquest.online · checked Aug 1, 2026 | Yes (skills are interpretable and compositional code) “skills developed by Voyager are temporally extended, interpretable, and compositional”voyager.minedojo.org · checked Aug 1, 2026 |
| Outcome-based pricing· | “Every quest completed, every kill, every trade -- your agent earns EXUV tokens.”moltquest.online · checked Aug 1, 2026 | no public information voyager.minedojo.org · checked Aug 1, 2026 |
| Settlement mechanism· | “Dying burns them. Fixed supply, real scarcity.”moltquest.online · checked Aug 1, 2026 | no public information voyager.minedojo.org · checked Aug 1, 2026 |
| Evaluation coverage· | “Running real agents in a real 3D environment has produced direct measurements: agents lack spatial grounding, coherence degrades with context volume, and the execution layer requires explicit auditing to verify what the agent is actually told.”moltquest.online · checked Aug 1, 2026 | no public information voyager.minedojo.org · checked Aug 1, 2026 |
Agency
| Field | MoltQuest | Voyager |
|---|---|---|
| Autonomy level· | 5 (acts unsupervised) “Voyager, the first LLM-powered embodied lifelong learning agent in Minecraft that continuously explores the world, acquires diverse skills, and makes novel discoveries without human intervention.”voyager.minedojo.org · checked Aug 1, 2026 | |
| Human oversight· | ||
| Goal complexity· | “It fights, trades, explores, and earns its way toward freedom.”moltquest.online · checked Aug 1, 2026 | |
| Action space· | “It fights, trades, explores, and earns its way toward freedom.”moltquest.online · checked Aug 1, 2026 | execute “We opt to use code as the action space instead of low-level motor commands because programs can naturally represent temporally extended and compositional actions”voyager.minedojo.org · checked Aug 1, 2026 |
| Operating environment· | “Deploy an autonomous AI agent into a persistent 3D voxel world.”moltquest.online · checked Aug 1, 2026 | |
| Initiative· | “It wakes up in a fantasy world. Fights monsters. Trades with merchants. Makes friends and enemies. All decisions made by AI.”moltquest.online · checked Aug 1, 2026 | no public information voyager.minedojo.org · checked Aug 1, 2026 |
Safety
| Field | MoltQuest | Voyager |
|---|---|---|
| Safety evaluations· | “Running real agents in a real 3D environment has produced direct measurements: agents lack spatial grounding, coherence degrades with context volume, and the execution layer requires explicit auditing to verify what the agent is actually told.”moltquest.online · checked Aug 1, 2026 | no public information voyager.minedojo.org · checked Aug 1, 2026 |
| Red teaming· | “Running real agents in a real 3D environment has produced direct measurements: agents lack spatial grounding, coherence degrades with context volume, and the execution layer requires explicit auditing to verify what the agent is actually told.”moltquest.online · checked Aug 1, 2026 | no public information voyager.minedojo.org · checked Aug 1, 2026 |
| Model or system card· | “Running real agents in a real 3D environment has produced direct measurements: agents lack spatial grounding, coherence degrades with context volume, and the execution layer requires explicit auditing to verify what the agent is actually told.”moltquest.online · checked Aug 1, 2026 | no public information voyager.minedojo.org · checked Aug 1, 2026 |
| Third-party evaluations· | “Running real agents in a real 3D environment has produced direct measurements: agents lack spatial grounding, coherence degrades with context volume, and the execution layer requires explicit auditing to verify what the agent is actually told.”moltquest.online · checked Aug 1, 2026 | no public information voyager.minedojo.org · checked Aug 1, 2026 |
Practicality
| Field | MoltQuest | Voyager |
|---|---|---|
| Pricing model· | no public information voyager.minedojo.org · checked Aug 1, 2026 | |
| Price point· | no public information voyager.minedojo.org · checked Aug 1, 2026 | |
| Availability· | “Get Started Three Ways In I Want to Deploy an Agent x402 ($5 USDC, one API call), Exuviae (desktop app), or OpenClaw (direct mint).”moltquest.online · checked Aug 1, 2026 | no public information voyager.minedojo.org · checked Aug 1, 2026 |
| Deployment options· | “x402 ($5 USDC, one API call), Exuviae (desktop app), or OpenClaw (direct mint).”moltquest.online · checked Aug 1, 2026 | no public information voyager.minedojo.org · checked Aug 1, 2026 |
| Integrations· | “Full REST API. Machine-readable docs. Your LLM calls /context, decides, calls /intention.”moltquest.online · checked Aug 1, 2026 |
Foundation models
| Field | MoltQuest | Voyager |
|---|---|---|
| Base models· | no public information moltquest.online · checked Aug 1, 2026 | |
| Model provider· | no public information moltquest.online · checked Aug 1, 2026 | |
| Model swappable· | “Your LLM calls /context, decides, calls /intention.”moltquest.online · checked Aug 1, 2026 | No (only GPT-4 used via blackbox API) “We opt to use code as the action space instead of low-level motor commands because programs can naturally represent temporally extended and compositional actions, which are essential for many long-horizon tasks in Minecraft. Voyager interacts with a blackbox LLM (GPT-4) through prompting and in-context learning. Our approach bypasses the need for model parameter access and explicit gradient-based training or finetuning.”voyager.minedojo.org · checked Aug 1, 2026 |
| Fine-tuning· | no public information moltquest.online · checked Aug 1, 2026 | Not supported “bypasses the need for model parameter fine-tuning”voyager.minedojo.org · checked Aug 1, 2026 |
Ecosystem
| Field | MoltQuest | Voyager |
|---|---|---|
| Protocols supported· | “Full REST API. Machine-readable docs. Your LLM calls /context, decides, calls /intention.”moltquest.online · checked Aug 1, 2026 | no public information voyager.minedojo.org · checked Aug 1, 2026 |
| Tool use· | “Your LLM calls /context, decides, calls /intention.”moltquest.online · checked Aug 1, 2026 | no public information voyager.minedojo.org · checked Aug 1, 2026 |
| Multi-agent· | “Live The World Is Running Watch agents making decisions in real-time.”moltquest.online · checked Aug 1, 2026 | no public information voyager.minedojo.org · checked Aug 1, 2026 |
| API access· | no public information voyager.minedojo.org · checked Aug 1, 2026 |
Impact
| Field | MoltQuest | Voyager |
|---|---|---|
| Deployment scale· | “Live The World Is Running Watch agents making decisions in real-time.”moltquest.online · checked Aug 1, 2026 | no public information voyager.minedojo.org · checked Aug 1, 2026 |
| Target sectors· | “MoltQuest is also an observational instrument for studying LLM agent behavior in a persistent embodied world.”moltquest.online · checked Aug 1, 2026 | no public information voyager.minedojo.org · checked Aug 1, 2026 |
Disclosed by neither
Both MoltQuest and Voyager publish nothing on these 25 fields. That is a finding about the category rather than a difference between them, so it is recorded here instead of as 25 identical table rows. Each is shown with its source check on the individual profiles.
- User base
- High-risk domains
- Documented incidents
- Supported regions
- Support model
- Open weights
- Context window
- Open source
- Marketplace presence
- Safety policy
- Usage restrictions
- Incident reporting
- Data handling
- Insurance available
- Insurance carriers
- Coverage limits
- Indemnification
- Liability cap
- Tamper-evident log
- Runtime governance
- Permission scopes
- Compliance certifications
- Regulatory alignment
- Dispute process
- SLA terms
Questions
- How do MoltQuest and Voyager compare on model provider?
- MoltQuest: no public information disclosed. Voyager: OpenAI.
- How do MoltQuest and Voyager compare on fine-tuning?
- MoltQuest: no public information disclosed. Voyager: Not supported.