Models / NAVIN RESEARCH
Introducing afaxxaq-000 — unname
A pre-release note on afaxxaq-000 — unname, the open-weight multimodal model Navin Research is testing and preparing to announce.
A pre-release note on afaxxaq-000 — unname, the open-weight multimodal model Navin Research is testing and preparing to announce.
Short answer: afaxxaq-000 — unname is the temporary designation for a Navin Research model being tested and prepared for announcement. It is designed to learn from conversations, retain user-controlled memory, adapt across users and work, and support high customization through knowledge retrieval, tools, workflows, fine-tuning, and adapters. It is not publicly released yet; pricing, benchmarks, and numerical specifications are not announced.
afaxxaq-000 — unname is waiting for its public introduction.
afaxxaq-000 — unname is the temporary working designation for a Navin Research model that is being tested and prepared for public announcement. It is not a released product yet, but it is a real model program with a defined direction: multimodal capability, broad customization, and behavior that can improve through use and deliberate tuning.
The name is provisional. The release record will replace this working designation with the final public identity when the model is ready.
- STATUS: TESTING AND WAITING FOR ANNOUNCEMENT
- WORKING DESIGNATION: afaxxaq-000 — unname
- RELEASE FORM: OPEN-WEIGHT
Learning means becoming more useful without simply becoming larger.
afaxxaq-000 is being designed to learn at several levels. Within a conversation, it can use the current exchange as context. With user-controlled memory, it can retain relevant information across conversations. With private data, fine-tuning, or adapters, it can be adapted for a domain, organization, or workflow.
The model can also be deliberately adjusted after deployment. That means intervening in behavior and objectives so the system acts more correctly, consistently, and precisely. It does not mean claiming that the base model becomes larger every time it learns.
- IN-CONVERSATION LEARNING
- USER-CONTROLLED LONG-TERM MEMORY
- PRIVATE-DATA FINE-TUNING OR ADAPTERS
- POST-DEPLOYMENT BEHAVIOR REFINEMENT
The model is meant to fit the work, not force every user into one behavior.
Customization is a central part of the model direction. Users will be able to configure how afaxxaq-000 works for them, with memory, retrieval from a knowledge base, tools, workflows, fine-tuning, and adapters forming different layers of control.
Those layers serve different purposes. Memory carries user-relevant continuity. Retrieval brings governed external knowledge into a task. Tools and workflows connect the model to action. Fine-tuning and adapters change behavior for a domain or operating pattern. The user should be able to choose and combine these mechanisms instead of treating customization as one opaque setting.
- CONFIGURABLE BY THE USER
- MEMORY AND KNOWLEDGE RETRIEVAL
- TOOLS AND WORKFLOWS
- FINE-TUNING AND ADAPTERS
Text, speech, and vision belong in one model direction.
The planned model supports text, speech and audio, vision and images, and multimodal work across these inputs. That gives it a foundation for personal assistance, research, enterprise work, and workflow automation rather than one narrow interface.
Moyi remains a separate project. Moyi focuses on speech technology and its own research direction; it is not the name of afaxxaq-000 and should not be presented as a component of this model.
- TEXT
- SPEECH AND AUDIO
- VISION AND IMAGES
- MULTIMODAL INPUTS AND OUTPUTS
- MOYI: SEPARATE PROJECT
The release is planned for more than one way of working.
afaxxaq-000 is planned as an open-weight model. The intended release direction includes multiple forms of access and use rather than a single locked surface. The exact packages, APIs, runtimes, hardware guidance, and access conditions will be stated in the release record when they are ready.
Open weights can support inspection, local control, domain adaptation, and independent experimentation. They also make the operator responsible for the runtime, data boundary, permissions, safety controls, and maintenance around the model.
- OPEN-WEIGHT DIRECTION
- MULTIPLE PLANNED FORMS OF USE
- EXACT PACKAGES AND ACCESS: NOT YET ANNOUNCED
- PRICING: NOT ANNOUNCED
A model announcement must show what was tested.
The model is currently being tested, but benchmark results, internal test figures, supported language coverage, context window, speed, and other numerical specifications have not been approved for publication. This article therefore describes the confirmed direction without turning testing into a performance claim.
Before release, the evaluation record should separate model behavior from memory, retrieval, tools, workflow orchestration, runtime, and human review. It should also show where the system abstains, fails, or needs a person to decide.
- TESTING: IN PROGRESS
- BENCHMARKS AND NUMBERS: NOT ANNOUNCED
- LANGUAGE COVERAGE: NOT ANNOUNCED
- CONTEXT, SPEED, AND HARDWARE: NOT ANNOUNCED
One adaptable foundation, many accountable uses.
The intended scope covers personal assistance, research, enterprise work, workflow automation, and broad multi-domain use. Those categories describe the direction, not a guarantee that every task is solved equally well. The correct configuration, data, tools, permissions, and review boundary will depend on the work being done.
The model should help people and organizations shape a useful system around their needs while keeping important actions inspectable and controllable.
- PERSONAL ASSISTANCE
- RESEARCH
- ENTERPRISE WORK
- WORKFLOW AUTOMATION
- MULTI-DOMAIN USE
The final announcement will turn the direction into a verifiable release.
When afaxxaq-000 is ready to launch, Navin Research should publish the final name, version, artifacts, access paths, license, supported configurations, evaluation evidence, safety boundaries, known limitations, and maintenance expectations together.
Until then, the accurate description is simple: afaxxaq-000 — unname is a tested, open-weight, multimodal Navin Research model waiting for public announcement, designed to learn from interaction, adapt to users and work, and remain highly configurable. It is not yet available, and no price or performance number should be inferred.
- FINAL NAME AND VERSION: PENDING ANNOUNCEMENT
- ACCESS, LICENSE, AND PACKAGES: TO BE PUBLISHED
- PRICING: NOT ANNOUNCED
- PERFORMANCE NUMBERS: NOT ANNOUNCED
