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Kimi K2.7 Code is generally available in GitHub Copilot
21 days ago
- Kimi K2.7 Code, an open-weight model, is now generally available in GitHub Copilot as a selectable option, offering more choice and lower cost.
- It is hosted on Microsoft Azure and billed at provider list pricing under usage-based billing.
- Rolling out initially to Copilot Pro, Pro+, and Max plans, with expansion to Business, Enterprise, and other surfaces planned over coming weeks.
- Available in various tools including Visual Studio Code, Visual Studio, Copilot CLI, GitHub Copilot app, and mobile platforms.
- For Copilot Business and Enterprise, administrators must enable the Kimi K2.7 Code policy in settings, as it is off by default, with recommendations to review security and compliance requirements.
Gemma 4 on Cerebras - The Fastest Inference Is Now Multimodal
23 days ago
- Gemma 4 31B runs at over 1,800 tokens per second on Cerebras Inference, enabling fast multimodal applications.
- It is the first Google DeepMind model on Cerebras with image input support for screenshots, documents, charts, and UI states.
- Cerebras achieves record speed and low latency, making Gemma 4 suitable for real-time visual and agentic workflows.
- Gemma 4 31B matches Claude Haiku 4.5 in intelligence but runs 18x faster and is open-weight under Apache 2.0.
- The model's high speed transforms product development, allowing instant iteration and complex multimodal loops.
- As a dense, efficient model, Gemma 4 31B is designed for quality without the large footprint of MoE models.
- Example applications include real-time screenshot analysis, long-context summarization, and UI debugging.
- Gemma 4 31B is available on the Cerebras Inference Cloud in public preview for multimodal workloads.
Solar Open 2: Korea's Sovereign Foundation Model, Built for Agentic Use
11 hours ago
- Solar Open 2 is an open-weight foundation model optimized for agentic use, designed to serve as a base model for agents in real work environments.
- It uses a Mixture-of-Experts (MoE) architecture with 250B total parameters but activates only 15B per token, improving both capability and inference efficiency.
- The model supports a 1M-token context window and runs on two NVIDIA H200 GPUs with quantization, making it practical for enterprise deployment.
- It officially supports Korean, English, and Japanese, with a tokenizer optimized for Korean efficiency (50–80% of tokens compared to global models).
- Training data focused on agent scenarios including search, tool calling (MCP), coding, and office work, with a custom data synthesis and verification pipeline.
- Solar Open 2 achieved top scores among comparable models on MMLU-Pro (86.2), LiveCodeBench (92.4), and Korean benchmarks (85.4 average).
- On Korean office work benchmark Ko-GDPval, it scored 86.8, nearly matching a model six times larger (DeepSeek-V4-Pro) while using only 15B active parameters.
- The model uses Selective Weight Transfer from Solar Open 100B for efficient training, reaching target loss with 58% of the tokens needed by random initialization.
- Weights are released on Hugging Face under a commercially usable license, with a technical report covering architecture, training methodology, and evaluation conditions.
- Solar Open 2 is built for long-horizon tasks, long-context processing, and reliable tool calling, addressing the unique demands of agentic workflows.

Hasty Briefsbeta

#open-weight model

Kimi K2.7 Code is generally available in GitHub Copilot

Gemma 4 on Cerebras - The Fastest Inference Is Now Multimodal

Solar Open 2: Korea's Sovereign Foundation Model, Built for Agentic Use