Compare AI models and understand their capabilities, running costs and deployment requirements.
Use this hub alongside Swarm Signal Resources, AI Agent Systems and AI Safety, Evals & Guardrails.
Choosing a model for a real workload
Define the tasks and failure limits first. Use the model evaluation guide to compare candidates on those tasks, then check their hosting and memory requirements.
For deployment choices, compare MoE and dense models on memory, latency and task quality. If the model needs your documents, use the RAG, fine-tuning and long-context decision guide. Measure the full workflow with the cost-per-accepted-task example.
Start here
- Llama 4 vs Qwen 3 vs DeepSeek V3 vs Mistral Large: Open-Weight Models 2026
- Open-Weight Model Tradeoffs: Llama, Qwen, and DeepSeek
- Mixture of Experts Explained: The Architecture Behind Every Frontier Model
- Best Open-Weight Models for Production AI Agents 2026
- The UAE's AI Gamble: $148 Billion, Open-Source Models, and the Race to Leave Oil Behind
- MoE Models Run 405B Parameters at 13B Cost
- Inference Optimization in 2026: Where the Compute Actually Goes
- Small-Model Routing With Frontier Fallback: The Production Cost Pattern
- Browser-Use Agents After the Computer-Use Benchmarks
Frontier model competition
- Open Source AI Impact: Who Wins When Models Get Cheap
- Open Weights, Closed Minds: The Paradox of 'Open' AI
- China's Qwen Just Dethroned Meta's Llama as the World's Most Downloaded Open Model
- DeepSeek Explained: How a Chinese Lab Rewrote AI Economics
- The Frontier Model Wars: Gemini 3 vs GPT-5 vs Claude 4.5
Inference, scaling and compute
- Inference-Time Scaling: Why AI Models Now Think for Minutes Before Answering
- Scaling Laws Explained for Practitioners: What Actually Matters in 2026
- Inference-Time Compute Is Escaping the LLM Bubble
- Test-Time Compute: Methods, Costs and Evaluation — includes a runnable example showing the difference between finding a correct answer and selecting it.
- The Inference Budget Just Got Interesting
- MoE's Dirty Secret Is Load Balancing
Benchmarks and evaluation
- The First Model Trained to Swarm: What the Benchmarks Actually Show
- How to Evaluate AI Models Without Trusting Benchmarks
- When Your Judge Can't Read the Room
- Multimodal Agents Are Still Missing the Workflow
- AI Evaluation Frameworks 2026: Why Benchmarks Keep Lying
Open-weight and deployment choices
- The Training Data Problem: Why What Models Learn From Matters More Than How Much
- Model Selection Guide: How to Pick the Right AI Model for Your Use Case
- Transformer Architecture Explained: The Engine Behind Every AI Model