Can current MiniCPM5-2B/any best SOTA under 10B + modern harness beat pre-March 2025 frontier models like Grok 3/GPT-4o?

Hey experts! I genuinely have this question and would love a general consensus from people actually using these models. LLMs have advanced a lot in benchmarks and in practical usage. Even GPT-4o and Grok 3 were already enough for general chatting,search lookup, RP, etc. So if you brought those models back today, I feel like a lot of ordinary users wouldn't notice a massive difference for " EVERYDAY GENERAL USE" So how far has the sub-10B SOTA actually come? For example, MiniCPM5-2B is only ~2.5B parameters but has 131K context and strong current results in math, coding, long-context, tool use and agentic tasks. If you combine something like MiniCPM5-2B (including an abliterated/heretic variant) + modern harness + tool calling + web search + RAG/external memory + Python/code execution + filesystem/browser + context management + verification/retry loops, can the resulting assistant system genuinely reach the practical capability of those pre-March-2025 frontier models? If not, where exactly does it still fall short? Hard reasoning, planning, coding, long-horizon agents, knowledge, instruction following, etc.? I'd really love answers based on actual real-world usage! Also Disclaimer: The image above is only a rough benchmark reference, not an apples-to-apples comparison. I know The older models were evaluated on older benchmark versions/tasks and under different conditions, while newer models like MiniCPM5-2B are being evaluated on newer and generally harder tests. Artificial Analysis also changes the composition and methodology of its Intelligence Index over time. So I'd say this is more pineapple-to-apple than apples-to-apples . I'm mainly using it as a rough reference point for the discussion, not claiming the scores directly prove equivalent intelligence.