This might be my new favorite all-purpose local AI model. Fits nicely into 16GB of VRAM for an RTX 5060/5070TI. The new SparkX2.6-4B beats Qwen3.5-9B in 80% of shared benchmarks and 97% of Gemma4-12Bs. Stats 💾 official Q4_K_M → 3.54GB 🧠 only 4B parameters 📚 native 1M context 💭 none / low / high thinking budgets 🤖 trained for local agents 🔓 Apache 2.0 It already runs with: ⚙️ llama.cpp 🦙 Ollama 🖥️ LM Studio 🍎 MLX 🚀 vLLM / SGLang In the team's reported benchmark suite Averages: Spark-X2.6-4B → 63.3 Spark-X2.5-4B → 52.1 Qwen3.5-9B → 49.1 So they're claiming a 4B model beats their tested 9B comparison overall. For normal local-agent contexts, though, a ~3.5GB reasoning/agent model with this runtime support is very interesting. Link in ALT