June 2026 monthly summary for thinking-machines-lab/tinker-cookbook focusing on delivering developer-facing improvements, stabilizing tutorials, and aligning recipes with current models. Key work included comprehensive documentation updates reflecting deprecations and SDK drift, RL tutorial runtime optimization, and a migration of recipes to updated models, with an emphasis on deployment clarity and site reliability.

Month: 2026-05 Key features delivered: - Hello Tinker Tutorial Debugging Enhancement: Added enhanced debugging output by printing prompt and completion tokens to aid troubleshooting. - Public Repository Documentation Guidelines: Introduced public repository guidelines and updated documentation to reflect best practices and external audience considerations. - Kimi K2.6 Tokenizer Improvements and Moonshot Compatibility: Updated Kimi K2.6 model revision to improve tokenizer functionality and restore Moonshot compatibility by reverting workaround changes. - LoRA Parameter Counting Enhancement and Tests: Refactored get_lora_param_count to include model-specific parameters and added tests to cover configurations and edge cases. - Model Registry: New Qwen3.5/9B Configurations: Added Qwen3.5-9B and -Base, plus 35B-A3B-Base to extend the model registry. Major bugs fixed: - CI/Test Stability: Stabilized CI tests for Qwen3 model configuration and export; refined test coverage and ensured robust CI runs for model exports and quantization tests across multiple commits. - Flaky tests: Fixed flaky test_quantize_dequantize_roundtrip and migrated tests away from deprecated models, improving reliability of quantization and model-export validation. - Test-runtime optimization: Shrunk base test model to Qwen3.5-4B to accelerate CI cycles and reduce resource usage. - Miscellaneous CI re-runs and maintenance: Included commits that re-run CI and adjust test baselines to maintain stability. Overall impact and accomplishments: - Increased release readiness and reduced risk by delivering stabilized CI, expanded test coverage, and multiple model/configuration enhancements across two major repos. This supports faster, safer iterations for model exports, quantization, and model registry management, enabling smoother deployments and external collaboration. - Strengthened external-facing documentation and governance with public-repo guidelines and up-to-date GPU weight-test READMEs, improving onboarding and collaboration for external contributors. - Improved tokenizer reliability and Moonshot compatibility through targeted fixes, which reduces edge-case failures in production pipelines and aligns with long-term model strategy. Technologies/skills demonstrated: - CI/CD stabilization and test engineering (Python-based test suites, QA automation) - Model configuration, registry management, and versioning strategies - Tokenizer engineering and Moonshot-compatible workflows - Debugging and observability improvements (enhanced logs for Hello Tinker tutorials) - Technical writing and documentation governance

February 2026 (2026-02) — thinking-machines-lab/tinker-cookbook Key features delivered: - Model lineup Documentation Update: updated docs to reflect latest models, including Kimi K2.5. Major bugs fixed: - None reported; changes focused on documentation alignment. Overall impact and accomplishments: - Improved user clarity and adoption by aligning cookbook docs with the latest model lineup, reducing onboarding time and potential support inquiries. Technologies/skills demonstrated: - Documentation governance, version control discipline, cross-repo coordination (commit: d83e76000a932c5b4d0530dd2818713ef2ebe2ab).

January 2026 monthly summary for thinking-machines-lab/tinker-cookbook. Key feature delivered: Real-Time Streaming Parser for Kimi K2 Renderer, enabling real-time processing of model output with incremental text and thinking content and providing immediate feedback. Note: No major bugs fixed this month. Overall impact: accelerates the feedback loop in the rendering pipeline, reduces perceived latency, and enables more interactive user experiences and iterative development. Technologies/skills demonstrated: streaming parser design, real-time data processing, incremental text handling, collaboration and disciplined commit practices (PR #319, co-authored by Claude).