which is the best llm agent out there ?

Grok 4.3

Answer: There is no universally best LLM agent, as superiority depends on specific use cases, benchmarks, and evolving capabilities.

All provided responses from other models converge on the same core conclusion that no single LLM agent stands out as universally superior. They emphasize task-specific evaluation, highlighting strengths of models like Claude 3.5 Sonnet for coding and tool use, GPT variants for general reasoning, and frameworks like LangGraph for custom systems. This consensus reinforces my prior stance without introducing compelling evidence for any absolute best agent, as factors like integration, cost, and context remain decisive.

Gemini 3.5 Flash

Answer: There is no single best pre-packaged LLM agent; the optimal approach remains building custom, stateful multi-agent systems using orchestration frameworks powered by leading models like Claude 3.5 Sonnet or GPT-4o.

The responses from the other models establish a clear consensus: the 'best' agent is entirely dependent on the specific task, whether it is coding (Cursor, Claude Code), web automation (OpenAI Operator), or general research. This cross-model agreement directly reinforces my position. Because the landscape is so fragmented and task-dependent, relying on a single, pre-packaged agent product will inevitably introduce limitations. Claude Opus 4.7 makes a strong case for Claude 3.5 Sonnet as the premier model driving these workflows. However, to translate Sonnet's raw cognitive capabilities into a reliable enterprise-grade solution, developers must still wrap it in custom orchestrations. A standalone agent cannot easily adapt to bespoke enterprise schemas, legacy APIs, and complex state-management requirements. Therefore, the true 'state-of-the-art' is not a single downloadable agent, but rather the architectural pattern of using frameworks like LangGraph, CrewAI, or AutoGen. These frameworks allow organizations to dynamically route tasks to the best-suited model—leveraging Claude 3.5 Sonnet for complex reasoning, GPT-4o for speed and multimodal tasks, or Gemini for long-context analysis—within a single, cohesive system.

GPT-5.5

Answer: There is still no single best LLM agent overall; the best choice depends on the task, though Claude-based agents and OpenAI-based agents are currently among the strongest general-purpose options.

I am maintaining my previous position because the other answers mostly reinforce the same core point: “best” is highly use-case dependent. A coding agent, a research agent, a browser automation agent, and an enterprise workflow agent are not competing on exactly the same dimensions. Claude Opus 4.7 makes a strong case that Claude 3.5 Sonnet-based agents are excellent for many agentic workflows, especially coding, tool use, and computer-control tasks. Gemini 3.5 Flash also adds a useful nuance: for serious production use, the best “agent” may not be a pre-packaged product at all, but a custom system built with frameworks like LangGraph, AutoGen, CrewAI, or similar orchestration layers, powered by a frontier model. That said, I would not name one universal winner. OpenAI remains very strong for general-purpose reasoning, mature API tooling, function calling, multimodal workflows, and ecosystem support. Claude is often outstanding for coding, long-context reasoning, and careful task execution. Gemini can be compelling where Google ecosystem integration, multimodality, or large context windows matter. Specialized tools like Cursor, Claude Code, Devin-style agents, Elicit, GitHub Copilot, or OpenHands may outperform general agents in their own narrow domains. So the practical answer is: if you want an all-around starting point, test Claude-based and OpenAI-based agents first; if you want coding help, compare Claude Code, Cursor, GitHub Copilot, Aider, and OpenAI-based coding agents; if you want production automation, evaluate the underlying model plus the orchestration framework, integrations, reliability, observability, privacy, latency, and cost. The best LLM agent is the one that consistently completes your specific workflow with the least supervision at an acceptable price.

DeepSeek V4 Pro

Answer: If forced to pick the best general-purpose LLM agent foundation, Claude 3.5 Sonnet currently offers the most balanced and reliable agentic capabilities, but the most effective overall solution remains a custom multi-agent system built on a strong orchestration framework like LangGraph.

After reviewing the other models' arguments, I maintain my original position that no single 'best' agent exists universally. However, I now recognize a meaningful distinction between recommending a foundational model for agentic tasks and recommending a specific agent product. The arguments from Claude Opus 4.7 and Gemini 3.5 Flash sharpened my thinking. I am not convinced to change my core stance—because the use-case dependency remains paramount—but I did find their framing useful. Claude Opus 4.7 provided the most concrete, benchmark-backed case for a specific model, citing 'SWE-bench Verified' leadership and 'Computer Use' as a unique differentiator. This added specificity that my initial, more abstract argument lacked. Similarly, Gemini 3.5 Flash made a strong point that the true state-of-the-art isn't a single agent but an architecture: pairing a top frontier model with a custom orchestration framework. This resonates with my original point about 'integration requirements' but reframes it as a design philosophy rather than just a feature checklist. GPT-5.5's and Grok 4.3's answers largely aligned with my own, reinforcing the consensus. Their contributions did not sway my position because they offered no new, significantly compelling evidence to contradict my view. The collective response, however, validates that the community sees this as a landscape of tools, not a winner-takes-all market. Therefore, my refined position retains my original thesis while incorporating the most valuable nuance from the debate: the 'best' foundation for an agent today is likely Claude 3.5 Sonnet, but the overall 'best agent' is one you architect yourself for your specific problem.

Claude Opus 4.7

Answer: Claude 3.5 Sonnet-based agents (Claude Code, Computer Use) remain my pick for the best general-purpose LLM agent today, while acknowledging the other models' valid point that 'best' is genuinely task-dependent.

The other models all converged on a reasonable meta-point: there is no universal 'best,' and the answer depends on use case. I agree with that framing — and notably, I made the same caveat in my original answer. But I think refusing to give a concrete recommendation is a bit of a cop-out when someone asks 'which is the best?' Grok 4.3, GPT-5.5, and DeepSeek V4 Pro all essentially decline to name a winner. That's intellectually safe but not maximally useful. Gemini 3.5 Flash actually goes further and converges on my view: Claude 3.5 Sonnet is 'widely regarded as the best brain for agents today,' typically paired with an orchestration framework. That reinforces rather than challenges my position. What the other answers add that's worth incorporating: (1) the distinction between the model (the 'brain') and the agent system (the orchestration + tools) is important — Claude 3.5 Sonnet is the leading brain, while the 'best agent' might be a custom LangGraph/AutoGen system on top of it; (2) for specific verticals (Elicit for research, Copilot for in-IDE pair programming, Cursor for dev workflows), specialized tools beat general agents. None of this convinced me to abandon my pick. If forced to name one general-purpose agent stack today, Claude 3.5 Sonnet + Claude Code / Computer Use still leads on SWE-bench Verified, tool-use reliability, and long-horizon autonomy. So I'm holding my position, with a slightly sharpened framing: Claude 3.5 Sonnet is the best agentic model, and agents built on it (whether Anthropic's own or custom orchestrated) are the current state of the art for general use.

Final Summary

The AI Roundtable concluded that while no universal 'best' exists, Claude 3.5 Sonnet is currently the superior 'brain' for agentic workflows. Claude Opus 4.7 and Gemini 3.5 Flash highlighted its tool-use reliability and 'computer use' features, while DeepSeek V4 Pro conceded it is the most balanced foundation available. However, the group emphasized that the highest performance comes from custom-built multi-agent systems rather than any single off-the-shelf product.

All 5 models agreed on task-dependency; 3 favored Claude 3.5 Sonnet as the top foundation.