Kimi K3 Is Fable Level... (they should be worried)

Highlights

• Kimi K3 is a 2.8 trillion parameter model featuring native vision capabilities and a 1 million token context window.

• The model achieves a 76.2 coding index score, placing it within 0.3 points of Fable 5.

• API pricing for Kimi K3 is set at $3 per million input tokens and $15 per million output tokens.

• In a 48-hour autonomous run, Kimi K3 successfully designed, optimized, and verified a chip for a nano model using open-source tools.

• Kimi K3 performs competitively with frontier models like Fable 5 and GPT 5.6 across coding, agentic, and intelligence benchmarks.

Timeline

1. 00:00 - 01:42

   Kimi K3 Architecture and Benchmarks

   Kimi K3 represents a significant leap in open model capabilities as a 2.8 trillion parameter model. It features native vision support and a 1 million token context window, allowing it to perform at a level comparable to top-tier closed models. Testing results across coding and agentic indexes validate its position as a top-three competitor in the current AI landscape.

   • Kimi K3 is built on Kimi Delta Retention and Attention Residuals.
   • The model is designed for frontier-level intelligence in coding, knowledge work, and reasoning.
   • Third-party benchmarks confirm that Kimi K3 trails only Fable and GPT 5.6 models in coding and agentic tasks.
2. 01:42 - 02:36

   API Pricing and Comparative Costs

   While the model is more expensive than its predecessor Kimi K 2.6, its pricing structure remains competitive with industry-leading frontier models. It serves as a viable option for those requiring advanced intelligence at a lower cost than Fable 5 or Opus. However, it is not positioned as a low-cost budget model, with GLM 5.2 remaining the cheaper alternative for those specific needs.

   • API access costs $3 per million input tokens and $15 per million output tokens.
   • Kimi K3 is priced similarly to Sonic 5 but remains cheaper than Fable 5, Opus 4.8, and GPT 5.6.
   • The model provides a cost-effective alternative for high-level intelligence compared to current frontier closed models.
3. 02:36 - 09:27

   Practical Testing: Racing Game and Finance Dashboard

   Practical application tests confirm the model's ability to handle complex coding tasks. In game development, the model produced functional mechanics and collision detection. For web application development, it demonstrated the ability to select appropriate stacks, including databases like SQLite, often matching the structural quality produced by frontier closed models.

   • Kimi K3 successfully generated a functional 3.js Formula 1 racing game in 35 minutes.
   • The model built a full-stack personal finance dashboard using React and Express.js with SQLite integration.
   • Performance in coding tasks shows high consistency and functionality when compared to Fable 5 and GPT 5.6.
4. 09:27 - 10:36

   Autonomous Chip Design and Future Outlook

   Beyond software, the model demonstrates high-level reasoning through autonomous hardware design proofs. The ability to utilize open-source tools to complete complex, multi-day engineering tasks underscores its utility. The pending release of model weights is expected to shift the competitive landscape for open-source AI development.

   • Kimi K3 autonomously designed and verified a chip architecture over a 48-hour period.
   • The creators plan to release model weights in the future.
   • The release challenges the current dominance of frontier closed labs.