# Blog — Swarnava Dutta

> Notes from building production AI systems: agentic workflows, RAG pipelines, evaluation, and the engineering lessons that come with shipping them.

- Blog home: https://swarnava.dev/blogs
- RSS feed: https://swarnava.dev/blogs/feed.xml
- Posts published: 58

## [How to Install FlashAttention-3 on NVIDIA Hopper GPUs](https://swarnava.dev/blogs/install-flash-attention-3)

Learn how to install Flash Attention 3 on NVIDIA Hopper GPUs, match CUDA and PyTorch, build from source, verify the package, and fix common errors.

- Published: 2026-09-06 · 9 min read
- Tags: Nvidia H100, Nvidia H800, Hopper Architecture
- Markdown version: https://swarnava.dev/blogs/install-flash-attention-3/index.md

## [How to Use QLoRA Hugging Face on a Single GPU](https://swarnava.dev/blogs/qlora-hugging-face-tutorial)

Learn how to use QLoRA Hugging Face to fine-tune Llama 3 in 4-bit NF4 with PEFT and TRL, then compare VRAM use against LoRA and DoRA adapters.

- Published: 2026-09-05 · 8 min read
- Tags: Hugging Face Peft, Bitsandbytes, Trl Sfttrainer
- Markdown version: https://swarnava.dev/blogs/qlora-hugging-face-tutorial/index.md

## [Flash Attention vs Grouped Query Attention in PyTorch](https://swarnava.dev/blogs/flash-attention-vs-grouped-query-attention)

Learn how Flash Attention vs grouped query attention affects latency, VRAM, and KV cache size, with PyTorch benchmarks and implementation guidance.

- Published: 2026-09-04 · 8 min read
- Tags: Flashattention-2, KV Cache, Multi-head Attention
- Markdown version: https://swarnava.dev/blogs/flash-attention-vs-grouped-query-attention/index.md

## [How to Implement Paged Attention in PyTorch and vLLM](https://swarnava.dev/blogs/implement-paged-attention-pytorch)

Learn how to implement paged attention in PyTorch with a block KV cache, decoding tests, memory math, benchmarks, and a clear mapping to vLLM.

- Published: 2026-09-03 · 8 min read
- Tags: Vllm, Pytorch, Cuda
- Markdown version: https://swarnava.dev/blogs/implement-paged-attention-pytorch/index.md

## [Fix LM Studio Speculative Decoding Not Working on GGUF](https://swarnava.dev/blogs/lm-studio-speculative-decoding-fixes)

LM Studio speculative decoding not working? Learn how to fix draft model compatibility, tokenizer mismatches, backend limits, and low token acceptance.

- Published: 2026-09-02 · 10 min read
- Tags: Draft Model, Target Model, Gguf
- Markdown version: https://swarnava.dev/blogs/lm-studio-speculative-decoding-fixes/index.md

## [Flash Attention Error Compiling Objects for Extension Fix](https://swarnava.dev/blogs/flash-attention-extension-build-error)

Fix the Flash Attention error compiling objects for extension. Learn to diagnose CUDA, PyTorch, Ninja, GCC, build isolation, ComfyUI, and WSL2 failures.

- Published: 2026-09-01 · 8 min read
- Tags: Pytorch, Cuda Toolkit, Nvidia Nvcc
- Markdown version: https://swarnava.dev/blogs/flash-attention-extension-build-error/index.md

## [Implement LLM Function Calling in OpenAI, Claude, Gemini](https://swarnava.dev/blogs/implement-llm-function-calling)

Learn how to implement function calling in LLM APIs with Python, JSON Schema, Pydantic validation, parallel tools, retries, and provider-ready loops.

- Published: 2026-08-31 · 8 min read
- Tags: Openai Responses API, Anthropic Tool Use, Gemini Function Calling
- Markdown version: https://swarnava.dev/blogs/implement-llm-function-calling/index.md

## [Grouped Query Attention vs Multi-Query Attention in PyTorch](https://swarnava.dev/blogs/grouped-query-attention-vs-mqa)

Compare grouped query attention vs multi query attention in PyTorch. Learn how KV-cache memory, throughput, head settings, and model quality differ.

- Published: 2026-08-30 · 7 min read
- Tags: Multi-head Attention, KV Cache, Flashattention-2
- Markdown version: https://swarnava.dev/blogs/grouped-query-attention-vs-mqa/index.md

## [Prefix Caching vs KV Cache for Production vLLM Serving](https://swarnava.dev/blogs/prefix-caching-vs-kv-cache)

Learn prefix caching vs KV cache in vLLM, including setup, memory behavior, cache-hit diagnostics, benchmarks, and workload-specific tradeoffs.

- Published: 2026-08-29 · 9 min read
- Tags: Prefix Caching vs KV Cache, Openai Prompt Caching, Sglang Radixattention
- Markdown version: https://swarnava.dev/blogs/prefix-caching-vs-kv-cache/index.md

## [How to Install FlashAttention-2 for PyTorch and ComfyUI](https://swarnava.dev/blogs/install-flash-attention-2)

Learn how install Flash Attention 2 with compatible PyTorch, CUDA, and ComfyUI commands, then verify the version and fix common build and kernel errors.

- Published: 2026-08-28 · 7 min read
- Tags: Cuda 12.8, Nvidia Ampere Gpus, Nvidia Hopper Gpus
- Markdown version: https://swarnava.dev/blogs/install-flash-attention-2/index.md

## [SGLang vs vLLM Deployment for Production LLM Serving](https://swarnava.dev/blogs/sglang-vs-vllm-deployment)

Compare SGLang vs vLLM on throughput, latency, memory use, model support, and APIs. Discover benchmark methods and choose an engine for production.

- Published: 2026-08-28 · 8 min read
- Tags: Sglang vs Vllm, Tensorrt LLM, Llama Cpp
- Markdown version: https://swarnava.dev/blogs/sglang-vs-vllm-deployment/index.md

## [Synthetic Data vs Real Data for ML Training Decisions](https://swarnava.dev/blogs/synthetic-vs-real-training-data)

Discover how synthetic data vs real data for training compares on accuracy, privacy, rare-class coverage, and cost, with an SDV benchmark workflow.

- Published: 2026-08-27 · 9 min read
- Tags: Synthetic Data vs Real Data, Synthetic Data For Training, Synthetic Training Data LLM
- Markdown version: https://swarnava.dev/blogs/synthetic-vs-real-training-data/index.md

## [How to RLHF an LLM with Hugging Face TRL and PPO Steps](https://swarnava.dev/blogs/how-to-rlhf-llm-trl)

Learn how to RLHF an LLM with Hugging Face TRL through SFT, reward modeling, and PPO, plus GPU sizing tips and sycophancy evaluation gates before deployment.

- Published: 2026-08-26 · 8 min read
- Tags: RLHF For LLMs, RLHF LLM Example, Hugging Face Trl RLHF
- Markdown version: https://swarnava.dev/blogs/how-to-rlhf-llm-trl/index.md

## [RAGFlow Chunking Methods for Document Parser Selection](https://swarnava.dev/blogs/ragflow-chunking-methods)

Learn RAGFlow chunking methods by file type, configure parser and chunk size settings, and test retrieval quality for PDFs, tables, and documents.

- Published: 2026-08-25 · 8 min read
- Tags: Ragflow Chunking Methods, Ragflow Document Parsing, Ragflow Parser Selection
- Markdown version: https://swarnava.dev/blogs/ragflow-chunking-methods/index.md

## [Fixing LangChain Error Code 429 in Agents and Tools](https://swarnava.dev/blogs/langchain-error-code-429)

Learn how to trace LangChain error code 429 to provider limits, then fix retries, concurrency, token budgets, tool loops, and exhausted quota in Python.

- Published: 2026-08-25 · 7 min read
- Tags: Langchain Error Code 429, Langchain Error Codes, Langchain Tool Error
- Markdown version: https://swarnava.dev/blogs/langchain-error-code-429/index.md

## [Fix 'from langchain.agents import create_tool_calling_agent' Error](https://swarnava.dev/blogs/langchain-create-tool-calling-agent-error)

Fix the 'from langchain agents import create tool calling agent' error: learn version checks, API migration, and working LangChain/LangGraph code fixes.

- Published: 2026-08-24 · 8 min read
- Tags: Tool Calling Agent Langchain, AI Agent Error Handling
- Markdown version: https://swarnava.dev/blogs/langchain-create-tool-calling-agent-error/index.md

## [Pi Coding Agent Error “Terminated”: 5 Fixes for 2026](https://swarnava.dev/blogs/pi-coding-agent-terminated-error)

Pi coding agent error terminated? Learn how to trace resource limits, shell exits, provider failures, bad config, and updates - then verify the fix.

- Published: 2026-08-23 · 8 min read
- Tags: Pi Coding Agent Not Working, Pi Coding Agent Alternative, Pi Coding Agent Tutorial
- Markdown version: https://swarnava.dev/blogs/pi-coding-agent-terminated-error/index.md

## [CrewAI vs LangGraph: 7 Production Tradeoffs Before You Build](https://swarnava.dev/blogs/crewai-vs-langgraph-production)

Discover how CrewAI vs LangGraph compare across state, memory, interrupts, recovery, observability, and deployment - then choose the right framework.

- Published: 2026-08-22 · 8 min read
- Tags: Crewai vs Langgraph, Langgraph vs Crewai
- Markdown version: https://swarnava.dev/blogs/crewai-vs-langgraph-production/index.md

## [Why Claude AI Is Not Working: 7 Fixes to Try Today](https://swarnava.dev/blogs/why-claude-ai-not-working)

Discover why Claude AI is not working, identify outages, limits, login, browser, phone, or network issues, and apply the right fix step by step.

- Published: 2026-08-21 · 9 min read
- Tags: Claude AI Not Working Reddit, Claude AI Error Today, Claude AI Is Down
- Markdown version: https://swarnava.dev/blogs/why-claude-ai-not-working/index.md

## [How AutoGen Agents Exchange Messages: 4 Flow Patterns](https://swarnava.dev/blogs/autogen-agents-exchange-messages)

Learn how AutoGen agents exchange messages through direct chats, group routing, handoffs, and shared memory, then debug loops, stalls, and bad recipients.

- Published: 2026-08-20 · 8 min read
- Tags: Autogen Multi Agent Example, Autogen Agent Messaging, Autogen Group Chat
- Markdown version: https://swarnava.dev/blogs/autogen-agents-exchange-messages/index.md

## [DPO vs PPO vs SFT for LLM Alignment: 5 Production Tradeoffs](https://swarnava.dev/blogs/dpo-ppo-sft-llm-alignment)

Discover DPO vs PPO vs SFT for LLM alignment across safety, preference data, compute, stability, and failure modes to choose a production strategy.

- Published: 2026-08-19 · 9 min read
- Tags: DPO Training LLM, DPO vs Ppo, DPO vs Sft
- Markdown version: https://swarnava.dev/blogs/dpo-ppo-sft-llm-alignment/index.md

## [LangChain MCP Integration: 7 Production Failure Fixes](https://swarnava.dev/blogs/langchain-mcp-integration)

Learn LangChain MCP integration with Python: connect servers, map tools, choose HTTP or stdio, secure agents, and debug production failures.

- Published: 2026-08-18 · 8 min read
- Tags: Langchain MCP Integration, Langchain MCP Server, Langchain MCP Client
- Markdown version: https://swarnava.dev/blogs/langchain-mcp-integration/index.md

## [How to Do LoRA Fine-Tuning: Practical LLM Workflow for 2026](https://swarnava.dev/blogs/how-to-lora-fine-tuning)

Learn how to do LoRA fine tuning for LLMs, from low-rank math and dataset setup to rank, alpha, memory, evaluation, adapter merging, and inference.

- Published: 2026-08-17 · 9 min read
- Tags: LoRA Fine Tuning Tutorial
- Markdown version: https://swarnava.dev/blogs/how-to-lora-fine-tuning/index.md

## [How to Evaluate Multi-Agent Systems: 7 Production Tests](https://swarnava.dev/blogs/evaluate-multi-agent-systems)

Learn how to evaluate multi agent systems with metrics for task success, coordination, handoffs, tool calls, cost, latency, and production regressions.

- Published: 2026-08-16 · 9 min read
- Tags: How To Evaluate
- Markdown version: https://swarnava.dev/blogs/evaluate-multi-agent-systems/index.md

## [GraphRAG vs RAG in 2026: 6 Production Tradeoffs That Matter](https://swarnava.dev/blogs/graphrag-vs-rag-production)

Discover GraphRAG vs RAG across quality, latency, indexing cost, and maintenance, then choose the right retrieval architecture for production in 2026.

- Published: 2026-08-15 · 10 min read
- Tags: Graphrag vs RAG, Graphrag Evaluation, Graphrag vs Vector RAG
- Markdown version: https://swarnava.dev/blogs/graphrag-vs-rag-production/index.md

## [GPU Inference vs Training: 7 Tradeoffs That Drive Cost](https://swarnava.dev/blogs/gpu-inference-vs-training)

Learn how GPU inference vs training changes memory, precision, latency, throughput, utilization, and cost - and choose the right hardware for your workload.

- Published: 2026-08-14 · 10 min read
- Tags: GPU Inference vs Training, Nvidia Inference vs Training, GPU Inference Optimization
- Markdown version: https://swarnava.dev/blogs/gpu-inference-vs-training/index.md

## [How to Build Agent Orchestration: 7 Production Steps](https://swarnava.dev/blogs/build-agent-orchestration)

Discover how to build agent orchestration for production, with proven patterns for routing, state, retries, approvals, observability, and scaling.

- Published: 2026-08-13 · 11 min read
- Tags: AI Agent Orchestration, Multi Agent Orchestration
- Markdown version: https://swarnava.dev/blogs/build-agent-orchestration/index.md

## [7 LangGraph Alternatives for Coding Agents in 2026](https://swarnava.dev/blogs/langgraph-alternatives-coding-agents)

Discover the best LangGraph alternatives for production coding agents, compared on state, interrupts, cancellation, debugging, persistence, and control.

- Published: 2026-08-12 · 10 min read
- Tags: Langgraph Alternatives, Langgraph vs Langchain, Langgraph Cancel Run
- Markdown version: https://swarnava.dev/blogs/langgraph-alternatives-coding-agents/index.md

## [How Is Mistral AI Doing in 2026? Models and Outlook](https://swarnava.dev/blogs/mistral-ai-review-2026)

Wondering how is Mistral AI doing in 2026? Discover its model quality, coding results, pricing, ownership, developer sentiment, and outlook.

- Published: 2026-08-12 · 11 min read
- Tags: Mistral AI For Coding, Mistral AI vs Chatgpt
- Markdown version: https://swarnava.dev/blogs/mistral-ai-review-2026/index.md

## [How LLM Quantization Works: 4-Bit, 8-Bit Tradeoffs](https://swarnava.dev/blogs/how-llm-quantization-works)

Learn how LLM quantization works, from numeric mapping to 4-bit and 8-bit deployment, and choose the right balance of memory, speed, and accuracy.

- Published: 2026-08-11 · 11 min read
- Tags: LLM Model Quantization, 4 Bit LLM Quantization, 8 Bit LLM Quantization
- Markdown version: https://swarnava.dev/blogs/how-llm-quantization-works/index.md

## [Computer Use Agent in Copilot Studio: Setup & Limits](https://swarnava.dev/blogs/computer-use-agent-copilot-studio)

Discover how a computer use agent in Copilot Studio automates browser and desktop tasks, from setup and security to limits, licensing, and alternatives.

- Published: 2026-08-10 · 11 min read
- Tags: Computer Use Agents Copilot, Copilot Studio Computer Use, Computer Use Agents Claude
- Markdown version: https://swarnava.dev/blogs/computer-use-agent-copilot-studio/index.md

## [How Flash Attention Works: Tiling, Softmax, GPU I/O](https://swarnava.dev/blogs/how-flash-attention-works)

Learn how flash attention works through tiling, online softmax, kernel fusion, and recomputation, plus see GPU requirements and version differences.

- Published: 2026-08-09 · 10 min read
- Tags: Flash Attention Github, Flash Attention Paper, Flash Attention Formula
- Markdown version: https://swarnava.dev/blogs/how-flash-attention-works/index.md

## [How Gemini AI Works: Multimodal Models, Tools & Images](https://swarnava.dev/blogs/how-gemini-ai-works)

Learn how Gemini AI works across multimodal inputs, context, grounding, tool use, image generation, and editing - and what Google does not disclose.

- Published: 2026-08-08 · 12 min read
- Tags: Gemini Google AI, Gemini Multimodal Model, Gemini AI Architecture
- Markdown version: https://swarnava.dev/blogs/how-gemini-ai-works/index.md

## [How Model Distillation Works: A Practical LLM Guide](https://swarnava.dev/blogs/how-model-distillation-works)

Learn how model distillation works, from teacher-student training and soft targets to synthetic data, loss design, evaluation, and quantization tradeoffs.

- Published: 2026-08-07 · 11 min read
- Tags: AI Model Distillation, Model Distillation In Gen AI
- Markdown version: https://swarnava.dev/blogs/how-model-distillation-works/index.md

## [Prompt Injection Canaries: Detect Attacks in CrewAI](https://swarnava.dev/blogs/prompt-injection-canary-crewai)

Learn how a prompt injection canary detects attacks in CrewAI prompts, RAG, tools, memory, and handoffs - and see its limits and response steps.

- Published: 2026-08-06 · 11 min read
- Tags: Prompt Injection Canary, Prompt Injection Detection, Crewai Security
- Markdown version: https://swarnava.dev/blogs/prompt-injection-canary-crewai/index.md

## [Why Agentic AI Needs CPUs: Cost-Efficient Architecture](https://swarnava.dev/blogs/why-agentic-ai-needs-cpu)

Discover why agentic AI needs CPU capacity for orchestration, tools, retrieval, and concurrency - and how balanced CPU-GPU design cuts inference costs.

- Published: 2026-08-05 · 11 min read
- Tags: Agentic AI Cpu Requirements, Agentic AI Infrastructure, Cpu vs GPU For AI Agents
- Markdown version: https://swarnava.dev/blogs/why-agentic-ai-needs-cpu/index.md

## [How AI Voice Agents Work: Architecture, Latency & IVR](https://swarnava.dev/blogs/how-ai-voice-agents-work)

Learn how AI voice agents work, from streaming speech recognition and LLM tool calls to latency, memory, guardrails, and key differences from IVR.

- Published: 2026-08-04 · 11 min read
- Tags: AI Voice Agent Architecture, Real Time Voice AI
- Markdown version: https://swarnava.dev/blogs/how-ai-voice-agents-work/index.md

## [How Large Language Models Work: Training to ChatGPT](https://swarnava.dev/blogs/how-large-language-models-work)

Learn how large language models work, from tokens and transformer training to next-token prediction, fine-tuning, ChatGPT, and hallucinations.

- Published: 2026-08-03 · 10 min read
- Tags: How Large Language
- Markdown version: https://swarnava.dev/blogs/how-large-language-models-work/index.md

## [Flash Attention vs Sage Attention: Kernel Comparison](https://swarnava.dev/blogs/flashattention-vs-sageattention)

Flash attention vs sage attention: compare speed, memory, accuracy, GPU support, training, and inference. Discover which kernel to choose for your workload.

- Published: 2026-08-03 · 11 min read
- Tags: Flash Attention Alternative
- Markdown version: https://swarnava.dev/blogs/flashattention-vs-sageattention/index.md

## [Why Is DeepSeek So Cheap? AI Cost Economics Explained](https://swarnava.dev/blogs/why-deepseek-so-cheap)

Why is DeepSeek so cheap? Discover how training costs, inference efficiency, API pricing, free access, and business strategy lower its AI costs.

- Published: 2026-08-02 · 10 min read
- Tags: Deepseek Training Cost, Deepseek Inference Cost
- Markdown version: https://swarnava.dev/blogs/why-deepseek-so-cheap/index.md

## [vLLM for Windows: WSL2 Setup, Support & Alternatives](https://swarnava.dev/blogs/vllm-for-windows-guide)

Learn vLLM for Windows support in 2026, install it with WSL2 or Docker, test the API server, and compare native builds, remote Linux, and alternatives.

- Published: 2026-08-01 · 10 min read
- Tags: Vllm For Windows, Vllm Windows, Vllm Windows Support
- Markdown version: https://swarnava.dev/blogs/vllm-for-windows-guide/index.md

## [Does RLHF Use PPO? How LLM Alignment Works in 2026](https://swarnava.dev/blogs/does-rlhf-use-ppo)

Does RLHF use PPO in 2026? Learn where PPO fits in LLM alignment, why it became standard, and when teams choose DPO, SFT, or other alternatives.

- Published: 2026-07-31 · 10 min read
- Tags: RLHF vs DPO, RLHF vs DPO vs Ppo
- Markdown version: https://swarnava.dev/blogs/does-rlhf-use-ppo/index.md

## [AutoGen vs OpenAI Agents SDK: Production Guide 2026](https://swarnava.dev/blogs/autogen-vs-agents-sdk)

Discover how AutoGen vs Agents SDK compares for orchestration, tools, state, tracing, deployment, and migration - and choose the right production framework.

- Published: 2026-07-30 · 11 min read
- Tags: Autogen vs Agents Sdk, Openai Agents Sdk vs Autogen, Autogen vs Agent Framework
- Markdown version: https://swarnava.dev/blogs/autogen-vs-agents-sdk/index.md

## [Is Ollama Safe? Privacy Risks & Hardening Guide 2026](https://swarnava.dev/blogs/is-ollama-safe-security-guide)

Is Ollama safe for private AI? Discover how data flows, where local API and model risks hide, and how to harden Ollama on desktops and servers.

- Published: 2026-07-29 · 10 min read
- Tags: Ollama Security, Ollama Privacy, Ollama Local API Security
- Markdown version: https://swarnava.dev/blogs/is-ollama-safe-security-guide/index.md

## [Is RAG Still Relevant in 2026? When to Use or Replace It](https://swarnava.dev/blogs/is-rag-still-relevant)

Is RAG still relevant in 2026? Discover where retrieval wins, when long context or agentic search is better, and how to choose for production AI.

- Published: 2026-07-28 · 10 min read
- Tags: RAG vs Long Context, RAG vs Agentic Search
- Markdown version: https://swarnava.dev/blogs/is-rag-still-relevant/index.md

## [How Do State Space Models Work in Modern AI? S4 to Mamba](https://swarnava.dev/blogs/how-state-space-models-work)

How do state space models work in AI? Discover how equations become efficient S4 and Mamba layers, with selective scans, training, uses, and limits.

- Published: 2026-07-28 · 11 min read
- Tags: State Space Models For LLMs, State Space Models And Mamba
- Markdown version: https://swarnava.dev/blogs/how-state-space-models-work/index.md

## [How Attention Works in Transformer Architecture Explained](https://swarnava.dev/blogs/transformer-attention-mechanism-explained)

Learn how attention mechanism works in transformer architecture, from query-key-value intuition and formulas to multi-head attention in a worked example.

- Published: 2026-07-28 · 11 min read
- Tags: Attention Mechanism Formula, Scaled Dot Product Attention, Query Key Value Attention
- Markdown version: https://swarnava.dev/blogs/transformer-attention-mechanism-explained/index.md

## [How LLM Guardrails Work: Architecture & Testing Guide](https://swarnava.dev/blogs/how-llm-guardrails-work)

Learn how LLM guardrails work across input checks, policy enforcement, output filters, tool controls, testing, monitoring, benefits, and limits.

- Published: 2026-07-27 · 11 min read
- Tags: LLM Guardrails Limitations
- Markdown version: https://swarnava.dev/blogs/how-llm-guardrails-work/index.md

## [When Was Retrieval-Augmented Generation Invented, Exactly?](https://swarnava.dev/blogs/when-was-rag-invented)

Discover when retrieval augmented generation was invented, who coined RAG in 2020, its earlier roots, how it works, and where agentic RAG is headed.

- Published: 2026-07-27 · 10 min read
- Tags: When Was Retrieval
- Markdown version: https://swarnava.dev/blogs/when-was-rag-invented/index.md

## [Reranking Vector Search: How Rerankers Improve RAG](https://swarnava.dev/blogs/reranking-vector-search-rag)

Learn how reranking vector search rescoring improves RAG relevance, where rerankers fit, and how to balance retrieval accuracy, latency, and cost.

- Published: 2026-07-27 · 12 min read
- Tags: Reranking Vector Search, Reranking Semantic Search, Reranking AI Search
- Markdown version: https://swarnava.dev/blogs/reranking-vector-search-rag/index.md

## [Is Model Distillation Legal? Copyright Risks in 2026](https://swarnava.dev/blogs/is-model-distillation-legal)

Is model distillation legal? Learn how copyright, contracts, trade secrets, and platform terms affect AI training, plus steps to reduce your risk.

- Published: 2026-07-27 · 10 min read
- Tags: LLM Output Distillation, Model Distillation Copyright
- Markdown version: https://swarnava.dev/blogs/is-model-distillation-legal/index.md

## [Synthetic Training Data for AI: A Safe Pipeline Guide](https://swarnava.dev/blogs/synthetic-training-data-for-ai)

Learn how synthetic training data for AI is generated, filtered, validated, and mixed with real data to reduce collapse, bias, and privacy risks.

- Published: 2026-07-26 · 12 min read
- Tags: Synthetic Training Data
- Markdown version: https://swarnava.dev/blogs/synthetic-training-data-for-ai/index.md

## [Is Text-to-Image AI Free? Costs and Limits in 2026](https://swarnava.dev/blogs/is-text-image-ai-free)

Is text-to-image AI free? Discover how credits, usage limits, image rights, privacy, watermarks, and local hardware affect the true cost in 2026.

- Published: 2026-07-26 · 13 min read
- Tags: Free Text To Image AI, Open Source Text To Image AI
- Markdown version: https://swarnava.dev/blogs/is-text-image-ai-free/index.md

## [KV Cache Optimization: Strategies for Faster LLM Inference](https://swarnava.dev/blogs/kv-cache-optimization-llm-inference)

Master KV cache optimization techniques for LLM inference. Learn when to quantize vs offload, how vLLM implements caching, and reduce memory by 80%.

- Published: 2026-07-26 · 10 min read
- Tags: KV Cache Optimization LLM, KV Cache Optimization Vllm
- Markdown version: https://swarnava.dev/blogs/kv-cache-optimization-llm-inference/index.md

## [Best Chunking Strategies for RAG: Sizes, Methods & Benchmarks](https://swarnava.dev/blogs/best-chunking-strategies-rag)

Discover the best chunking strategies for RAG in 2026. Learn optimal chunk sizes, compare semantic vs recursive methods, and see real benchmark results.

- Published: 2026-07-25 · 9 min read
- Tags: Chunking Strategies For RAG, Chunking Method In Ragflow, Semantic Chunking
- Markdown version: https://swarnava.dev/blogs/best-chunking-strategies-rag/index.md

## [Is Flash Attention Stable? Production Guide 2026](https://swarnava.dev/blogs/is-flash-attention-stable-production-guide)

Is Flash Attention stable for production LLMs? Discover numerical precision findings, platform compatibility fixes, and when to use Flash Attention in 2026.

- Published: 2026-07-25 · 9 min read
- Tags: Candle Flash Attention
- Markdown version: https://swarnava.dev/blogs/is-flash-attention-stable-production-guide/index.md

## [What Is Text to Video AI? How It Works & Best Tools (2026)](https://swarnava.dev/blogs/what-is-text-to-video-ai)

Discover what text to video AI is, how diffusion models generate clips from prompts, and which tools are best. Learn to create your first AI video for free.

- Published: 2026-07-25 · 10 min read
- Tags: Best Text To Video AI
- Markdown version: https://swarnava.dev/blogs/what-is-text-to-video-ai/index.md

## [Are State Space Models Better Than Transformers? A Technical Comparison](https://swarnava.dev/blogs/state-space-models-vs-transformers)

Discover whether state space models like Mamba outperform transformers for long-context tasks, inference speed, and memory efficiency. Learn when each wins.

- Published: 2026-07-25 · 9 min read
- Tags: Mamba Architecture
- Markdown version: https://swarnava.dev/blogs/state-space-models-vs-transformers/index.md