Some deepseek-v4-flash 20260731 opinion review

First of all, I want to apologize if it's off-topic or in the wrong format. Having tried Deepseek Flash with reasoning high on a conceptually difficult task, involving Machine Learning classifiers and graphs. I am extremely impressed. It's on par with Mimo2.5 Pro for a context up to 200K. I don't expect to try it for bigger contexts. ## First topic : Machine learning The method : It knows about machine learning , methods and will go through hypotheses. "Future leaks" "Causal graphs" type of algorithms, it's creative. The reasoning : It thinks step by step, extremely methodical. Collect facts, discuss them. Take partial conclusions. Paragraphs answer to each other, the progression can be felt. When I say something vague he will stay on rails while trying to find a actionable result Consistency : It doesn't lose track or make call mistakes even with big logs or inline python scripts. it handles very well repetitions. Ordering : When it starts something, it continues while keeping track of what's on tab for later. On 200K context I didn't have to remind it Tool calls : i have several tools managing different aspects of the memory. It calls them and it really look like it takes in account the definition of the tool when providing content to them. Some of the tools are redundant in fact(need refactoring) metric : I only interrupted it for context precision, discussing a point he made or giving it path. Never to precise a notion or steering it. It felt like a conversation. For other models, on a 150K session, it happens between 4 to 6 times generally. ## Second topic : A GPU and Model queue manager Coding : while very technical and cohesive, the coding aspect is not as good as bigger models yet. Tests : I feel it understands the important concepts, components write tests for them. submitted by /u/Nyghtbynger [link] [comments]

Source: r/LocalLLaMA | 2026-07-31