
🌍 India’s Own LLM Go Global This might surprise you… India’s Sarvam‑M is now competing shoulder-to-shoulder with China and US AI giants: • 🇺🇸 GPT‑4 (175B) – still the gold standard • 🇨🇳 DeepSeek‑R1 (671B) – MoE, massive context window, ultra cost-efficient • 🇨🇳 Qwen‑3 (Multimodal) – 36T tokens, 119 languages • 🇮🇳 Sarvam‑M (24B) – hybrid model built under IndiaAI Mission And it’s already making waves: • 10K+ GitHub forks & 500K+ Hugging Face downloads – legit dev traction • Benchmark highlights: +20% Indian language, +21.6% math, +17.6% programming improvements—outperforming Mistral‑Small, and rivaling LLaMA‑3.3 70B & Gemma 3 27B And it’s already making waves: -10K+ GitHub forks & 500K+ Hugging Face downloads – legit dev traction -Benchmark highlights: +20% Indian language, +21.6% math, +17.6% programming improvements—outperforming Mistral‑Small, and rivaling LLaMA‑3.3 70B & Gemma 3 27B 📈 Standout stats: -Scored ~0.83 vs LLaMA’s 0.58 on Indic Q&A -Trails ~1% on English benchmarks like MMLU 🤔 Why the small gap? * Token diet is India-centric, needs more global English fine-tuning * Infrastructure is growing (IndiaAI now supports 34K GPUs), but still early-stage 💡 What this means Sarvam‑M is a “holy f*ffing airball” for Indian AI—showing we can build world-class LLMs at home. But to truly go global, we need: • Expanded datasets • More compute • Developer support and real-world use 🌱 Want to help it grow? Star it on GitHub, test it on Hugging Face, and contribute to its ecosystem. Let’s build India’s global AI story—together. 👇
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