Kronumos/Kronumos-Kairos-v2

TEXT GENERATIONPricing:Input $0.4 / Cached $0.08 / Output $0.8Concurrent Unit Cost:1Model Size:7.6BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Sep 27, 2026License:apache-2.0Architecture:Transformer0.0K Open Weights Featherless Exclusive Cold

Kronumos/Kronumos-Kairos-v2 is a 7.6 billion parameter cybernetic autonomous program repair (APR) model developed by Tokenectomy Labs, fine-tuned from Qwen/Qwen2.5-Coder-7B-Instruct with a 32768 token context length. It integrates a neural cortex for semantic reasoning with a deterministic Rust-based sub-cortex for AST validation and healing. This model is optimized for high-precision code remediation on real-world production software bugs, achieving significant token efficiency and local execution capabilities on the SWE-bench Verified benchmark.

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Kronumos 2 Kairos: Dual-Brain Autonomous Program Repair

Kronumos 2 Kairos, developed by Tokenectomy Labs, is a 7.6 billion parameter open-weight model designed for autonomous program repair (APR). Fine-tuned from Qwen/Qwen2.5-Coder-7B-Instruct, it uniquely combines a parametric neural "Cortex" with a deterministic, native Rust "Sub-Cortex" for high-precision code remediation. This architecture enables efficient, local bug fixing on production software.

Key Capabilities

  • Cybernetic Dual-Brain Architecture: Integrates neural reasoning (5-step CoT, code hunk generation) with a deterministic Rust Sub-Cortex (Tree-sitter AST slicing, auto-bracket/indent healing, Merkle causal ledger).
  • High-Precision Code Remediation: Specifically fine-tuned for fixing real-world production software bugs, demonstrated on the SWE-bench Verified benchmark.
  • Efficiency: Achieves 93.5% token reduction compared to industry multi-turn baselines, processing tasks with an average of 2,512 tokens in a single-pass zero-shot mode.
  • Local Execution: Designed for rapid local bug remediation on workstations and CI/CD gates, with a low VRAM footprint (5.5 GB for 4-bit quantization).
  • Issue De-Noising: Features an integrated Sub-Cortex IssueDeNoiser to strip conversational chaff and extract core problem specifications from GitHub issues.
  • Deterministic Healing: The Rust Sub-Cortex provides sub-microsecond latency (5µs) for tasks like indentation healing and bracket balancing.

Good For

  • Automated Bug Fixing: Ideal for autonomous program repair in CI/CD pipelines or local development environments.
  • Code Quality Assurance: Enhancing code integrity by automatically correcting syntax and structural errors.
  • Reducing Development Costs: Eliminating API costs associated with cloud-based models for code repair.
  • Offline Development: Enabling robust code repair capabilities on offline laptops and edge devices.

Finetunes
2 models