LLMs & Models Articles
Browse 579 articles about LLMs & Models.
Local AI vs Cloud AI for Agents: The Hybrid Routing Strategy That Saves Money
Learn when to run AI models locally and when to route to cloud APIs. A practical hybrid strategy for reducing costs without sacrificing quality.
What Is a 26M Parameter Function Calling Model? Cactus Needle Explained
Cactus Needle is a 26M parameter model built purely for function calling. Learn its architecture, use cases, and how to fine-tune it on a CPU.
Gemini 3.5 Pro vs GPT-5.6 Sol: What to Expect from Google's Next Frontier Model
Gemini 3.5 Pro is rumored to launch with a 2M token context window. Here's how it's expected to compare to GPT-5.6 Sol on coding, agents, and multimodality.
How to Use Grok 4.5 as a Cheaper Sub-Agent in Multi-Model AI Workflows
Grok 4.5 matches GPT-5.5 on coding benchmarks at $2 per million input tokens. Learn how to route tasks to it from a smarter orchestrator model.
What Is GPT-5.6 Ultra Mode? Multi-Agent Coordination for Demanding Tasks
GPT-5.6 Ultra spawns four or more coordinated agents to tackle complex tasks. Learn when to use it, what it costs, and how it compares to standard modes.
What Is Meta Muse Spark 1.1? Meta's New Frontier-Competitive LLM Explained
Meta Muse Spark 1.1 is Meta's return to competitive AI with terminal bench scores matching GPT 5.5. Here's what it can do and how to access it.
Grok 4.5 vs Claude Opus 4.8: Cost, Speed, and Real-World Coding Results
Grok 4.5 scores 83% on Terminal Bench at a fraction of Opus 4.8's cost. Compare both models on coding, legal tasks, and real-world professional work.
What Is Recursive Self-Improvement in AI? How GPT-5.6 Sol Post-Trained Luna
OpenAI used GPT-5.6 Sol to autonomously post-train the smaller Luna model. Here's what recursive self-improvement means and why it matters for AI builders.
What Is Grok 4.5? xAI's Frontier-Level Coding Model at Half the Cost
Grok 4.5 delivers near-Opus-level intelligence at $2 input and $6 output per million tokens. Here's what it excels at and where it still falls short.
How to Use Fable 5 as Architect and Grok 4.5 as Construction Crew in Multi-Agent Workflows
Use frontier models for planning and cheaper models for execution. This real example built a 50-district 3D city for $8 using this split-model pattern.
Grok 4.5 vs Claude Opus 4.8: Which Model Wins for Agentic Coding?
Grok 4.5 trained on Cursor data now rivals Claude Opus 4.8 on coding benchmarks. Compare cost, speed, and real-world agentic performance.
Hunyuan-3 vs GLM 5.2: Which Open-Weight Model Is Better for AI Agents?
Compare Tencent's Hunyuan-3 and GLM 5.2 on agentic coding, tool use, context length, and cost to find the right open model for your workflows.
What Is Anthropic's J-Space? The Global Workspace Inside Claude Explained
Anthropic discovered a 'J-space' inside Claude where conscious-like reasoning happens. Learn what it is, what it means for AI safety, and how it works.
What Is Grok 4.5? xAI and Cursor's First Jointly Trained Coding Model
Grok 4.5 is the first model trained using Cursor's real-world coding data and xAI's compute. Learn what makes it different and when to use it.
What Is Tencent Hunyuan-3? The 295B MoE Model Built for Agentic Tasks
Tencent's Hunyuan-3 is a 295B mixture-of-experts model optimized for agentic tool use, structured outputs, and local enterprise deployment.
How to Use Model Routing to Cut AI Agent Costs by 60%
Learn how to route tasks to cheaper models like Sonnet and Haiku instead of always using frontier models, without sacrificing output quality.
What Is Claude's J-Space? Anthropic's Global Workspace Discovery Explained
Anthropic discovered a hidden internal workspace inside Claude called J-Space. Learn what it reveals about how AI models actually think and reason.
AI Model Routing: How to Cut Costs 60% by Matching Tasks to the Right Model
Learn how to route AI tasks to the right model tier—frontier for planning, cheaper for execution—and cut your AI bill by up to 60%.
What Is Diffusion Language Modeling? How NVIDIA's Two-Tower Architecture Works
NVIDIA's Two-Tower diffusion LLM generates text in parallel blocks instead of token-by-token, achieving 2.4x speed gains with 98.7% quality retention.
What Is MiniCPM-5? The 1B On-Device AI Model Built for Agentic Tool Use
MiniCPM-5 is a 1B parameter model with 128K context, strong tool-use capabilities, and token efficiency that beats larger reasoning models.