EmbeddingGemma 2: an open, lightweight multimodal embedding model
deepmind.google·6d ago
AI Engineering
Hacker News·Jul 29·5 min read
Kimi K3-256k
TL;DR
Kimi Code has introduced the Kimi K3-256k model, which offers enhanced performance for everyday tasks like Q&A and code completion within a 256k context. Users can easily switch between K3 and K3-256k models in various clients.
✦ Why It Matters
Switch to Kimi K3-256k today for improved performance in coding tasks without video input.
Key Takeaways
- Switch to K3-256k for reduced quota usage.
- Compact context before switching models to preserve information.
- Use specific Model IDs to avoid errors during model calls.
- Start new sessions when switching models for optimal performance.
How It Works
Kimi Code's models utilize context windows to manage input size, allowing users to switch between models based on their needs. The K3-256k model effectively compresses context to fit within a 256k limit, ensuring efficient resource usage while maintaining performance.