Ollama v0.7 introduces a new engine for first-class multimodal AI, starting with vision models like Llama 4 & Gemma 3. Offers improved reliability, accuracy, and memory management for running LLMs locally.
Subscribe
Sign in
Ollama v0.7 introduces a new engine for first-class multimodal AI, starting with vision models like Llama 4 & Gemma 3. Offers improved reliability, accuracy, and memory management for running LLMs locally.
Great product. Have been using this for a while. Now with this update its even better. We have also lauched FilesMagicAI Ai file organizer for mac do check it out and give us feedback. Congrats to your team.
Files Magic AI
@zaczuo Just tried it out. Works great. Congrats on the launch. We also recently lauched FilesMagicAI which organized your macos Files automatically using AI. Do check it out and give us feedback. Thanks.
I wonder. How does these OSS offline LLMs perform with agentic tasks?
@sentry_co It's doable, but I think the result depends on what hardware can handle. For most consumer setups, think smoothly running quantized 7B, maybe up to 13B models, if you want decent speed for agent stuff. If you've got a beefier consumer rig (like 24GB VRAM), it might push a ~30B model. And to smoothly execute agentic workflow, we definitely need something like LangChain to actually build the agent logic on top. Some interesting discussion here.
@zaczuo I use Cline as my daily coding agent. It has support for Ollama. The agentic logic in cline is top notch. just need LLMs. I use gpt 4.1 and sonnet 3.7 for agentic stuff. People use Google gemini pro 2.5 for agentic stuff to. I will try it a bit later. O4 Mini is not good for agentic stuff for instance. too slow. gpt 4.1 mini is too light weight, gets stuck. What Sonnet 3.7 calls a Thinkng model is the best for agentic stuff I think. So thats what we need. Local Opensource thinking models for agentic tasks. MCP is the future 🚀
For those of us who prefer the privacy and control of running LLMs locally, Ollama v0.7's enhanced engine with multimodal capabilities and improved stability makes it an even more compelling platform for exploring the latest AI advancements right on our own machines.