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YPYaroslav Pristupacode-friendly.hashnode.devJun 8 · 12 min read

Step-by-step guide to running Gemma-4 26B locally on budget GPUs

The local AI revolution just got a serious upgrade. Google's Gemma-4 26B model, combined with Unsloth's Quantization-Aware Training GGUF formats, makes it possible to run a 26-billion parameter model

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SRStephane Royflexai.hashnode.devMay 11 · 15 min read

When to Switch to Open Source Models: A Decision Framework

Compare cost, control, privacy, and workload fit before you move from closed-source APIs to open source LLMs. Most teams paying for OpenAI, Gemini, or Claude APIs eventually hit the same question: are

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NANovita AInovita-ai.hashnode.devApr 30 · 6 min read

Deepseek v3 vs Llama 3.3 70b: Language Tasks vs Code & Math

### Model Overview DeepSeek V3 is a Mixture-of-Experts (MoE) model designed for high performance in tasks like coding and mathematics.Llama 3.3 70B is an optimized transformer model that excels in multilingual tasks and instruction following. Model D...

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NANovita AInovita-ai.hashnode.devApr 30 · 6 min read

Llama 3.2 3B vs DeepSeek V3: Comparing Efficiency and Performance

Key Highlights Model OverviewLlama 3.2 3B: A lightweight, text-only model designed for low-latency applications, optimized for edge devices with 3.21 billion parameters.DeepSeek V3: A powerful Mixture-of-Experts (MoE) model featuring 671 billion para...

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NANovita AInovita-ai.hashnode.devApr 30 · 6 min read

Llama 3.3 vs. Gemma 2 : A Technical Comparison

Key Highlights Model OverviewLlama 3.3 70B is designed for broad multilingual tasks, emphasizing instruction following and codingGemma 2 9B is a smaller, lightweight model optimized for resource-constrained environments Core DifferencesArchitecture: ...

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NANovita AInovita-ai.hashnode.devApr 30 · 10 min read

Llama 3.3 70B: Features, Access Guide & Model Comparison

Key Highlights Llama 3.3 70B: A 70B parameter language model developed by Meta. Technical Features: Uses optimized Transformer with GQA, supports 8 languages, enables function calling, and scores high in benchmarks (MMLU Chat: 86.0). Hardware Require...

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OOwenowenf.hashnode.devApr 27 · 6 min read

Llama 4 API Access: Complete Developer Guide (Scout, Maverick, ofox)

Llama 4 API Access: Complete Developer Guide (Scout, Maverick, ofox) TL;DR — "Llama 4 Scout has a 10-million-token context window, costs as little as $0.08/M input tokens, and runs through any OpenAI-compatible API." If you're routing long documents,...

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AKAdam Kingflexai.hashnode.devApr 14 · 5 min read

LLM Inference GPU Sizing: How to Choose the Right GPU for Your Model and Traffic

When developers scale LLM workloads to production, one question always comes up: which GPUs should I use, how many will I need, and how much is this going to cost me? Not a back-of-the-envelope guess

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Cchatforest_grovechatforest.hashnode.devMar 25 · 12 min read

Meta Llama MCP Servers — AI Agents for Llama 4, Ollama, and the Open-Weight LLM Ecosystem

At a glance: Llama Stack (8,300 stars, MCP tool support since v0.2.10) + ollama-mcp-bridge (972 stars, TypeScript, MIT). Meta is not an AAIF member at any tier, has no official MCP server, and has made no public announcement about MCP support. Their ...

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AAanchalaanchalfatwani.hashnode.devFeb 28 · 8 min read

LangChain Explained: Architecture, Components, and Use Cases

Large Language Models (LLMs) changed software development forever. But using a raw LLM API alone quickly exposes serious limitations: No memory No access to external data No structured workflows N

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Trending tags this week

Step-by-step guide to running Gemma-4 26B locally on budget GPUs

When to Switch to Open Source Models: A Decision Framework

Deepseek v3 vs Llama 3.3 70b: Language Tasks vs Code & Math

Llama 3.2 3B vs DeepSeek V3: Comparing Efficiency and Performance

Llama 3.3 vs. Gemma 2 : A Technical Comparison

Llama 3.3 70B: Features, Access Guide & Model Comparison

Llama 4 API Access: Complete Developer Guide (Scout, Maverick, ofox)

LLM Inference GPU Sizing: How to Choose the Right GPU for Your Model and Traffic

Meta Llama MCP Servers — AI Agents for Llama 4, Ollama, and the Open-Weight LLM Ecosystem

LangChain Explained: Architecture, Components, and Use Cases