Can Open Source LLMs Models Perform Common Business Tasks?

Can open source AI models actually handle real business work? 👉 https://localaibench.com 👉 https://bit.ly/dailyai-join Join the channel Can open source AI models actually handle real business work? No synthetic benchmarks. No PhD-level math problems. Just practical tasks like turning meeting notes into action items—the kind of work that eats up hours every week. 📊 SEE THE FULL RESULTS: https://localaibench.com In this video: - Why I built LocalAI Bench - The testing setup (Promptfoo + LM Studio + local hardware) - How I'm using 3 AI judges for consistent scoring - First results: which models passed and which struggled - What's coming next MODELS TESTED: ✅ Google Gemma 3n - 80% ✅ OpenAI OSS 20B - 80% ⚠️ Meta Llama 3.1 8B - 60% ⚠️ Qwen 3 - 60% ❌ DeepSeek R1 - 53% ❌ Mistral 7B - 20% (Claude Sonnet 4 included as cloud baseline) This is Phase 1—meeting notes extraction. More use cases coming soon: → Email response drafting → Document summarization → RFP to quote conversion → Code review assistance 🔔 Subscribe for updates as I add more models and test cases. CHAPTERS: 0:00 - Why I'm doing this 1:00 - The testing setup 2:00 - First results breakdown 3:30 - What worked, what didn't 4:30 - What's next --- Hardware: AMD Strix Halo, 128GB RAM Inference: LM Studio Evaluation: Promptfoo Judges: Claude, GPT-4, Gemini #OpenSourceAI #LocalAI #LLMBenchmark #AIForBusiness