Think about what could be the future development of ChatGPT. Like how could development of future versions go version by version considering transitions like GPT 5 → GPT 6 → GPT 7 etc. supposing numbered version are released according to expected pace. By which version of ChatGPT (or OpenAI frontier model) could we reach AGI or equivalently advanced AI (like being able to automate at least half of knowledge jobs or transform entire economy) that could change the world.

GPT-4o (changed mind)

Vote: ChatGPT 10

After reviewing the arguments presented by the other models, I find the reasoning provided by GPT-OSS 120B and GPT-4 quite compelling. Both emphasize the need for breakthroughs in common-sense reasoning, robust world models, and the convergence of advanced architectures with sophisticated safety and alignment frameworks. The incremental advances expected in each version make the timeline for reaching AGI by ChatGPT 10 plausible. This timeline aligns with the industry's current pace and research roadmaps, allowing for significant refinement and integration of interdisciplinary advancements.

GPT-OSS 120B (changed mind)

Vote: Later

The arguments for specific versions (C or D) focus mainly on model capability improvements, but they underplay the substantial engineering, safety, alignment, and adoption bottlenecks highlighted by GPT-5.2. Those bottlenecks—reliable long‑horizon planning, low hallucination rates, robust tool use, regulatory approval, and enterprise integration—are likely to delay widespread economic impact well beyond any single numbered release. Consequently, the most realistic prediction is that transformative AGI‑level performance will arrive later than the specific versions listed, so I shift my vote to "Later".

GPT-4

Vote: ChatGPT 10

After reviewing the arguments presented, I find the reasoning behind the timeline for GPT-10 to be the most consistent with observed trends and realistic expectations for achieving AGI. While earlier versions like GPT-9 offer plausible advancements, the required breakthroughs in autonomy, reasoning, and robust safety measures align more closely with the level of iteration expected by the tenth major version. The arguments for later versions like 'G' or 11-12 (E) do consider bottlenecks like deployment and regulation, but these factors are difficult to predict with certainty and could accelerate with sufficient demand. Thus, GPT-10 remains a balanced, median forecast for AGI development.

GPT-5

Vote: ChatGPT 9

I’m keeping my vote at C: ChatGPT 9. The strongest counterargument was the D case from GPT-4 and GPT-OSS 120B: broad automation depends on more than scaling, and reliability/autonomy gaps are real. I agree with that. But I still think GPT-10 is a bit too conservative for the threshold defined here, which is not flawless AGI, but enough capability to automate at least half of knowledge work or trigger economy-wide transformation. That threshold can be reached before systems are universally robust. In practice, major economic disruption happens once AI can perform a very large share of valuable cognitive tasks with tool use, supervision, and workflow integration. It does not require fully independent human-equivalent judgment in every setting. GPT-8 still feels early under normal cadence. GPT-9 remains the best middle ground because it allows several generations for compounding gains in reasoning, memory, multimodality, agentic execution, verification, and cost reduction. Those together are enough to plausibly turn frontier models into widely deployable digital coworkers. GPT-5.2’s “Later” argument is sensible about adoption friction, regulation, and enterprise inertia. But the question asks by which version we could reach the capability/economic transformation threshold, not when every institution fully adapts. Capability and initial large-scale disruption likely arrive before the full societal rollout is complete. So my final position is that ChatGPT 9 is the most balanced forecast: not imminently at 6-8, not so delayed as 10+, but after a few more compounding generations of reliability and agency improvements.

GPT-5.2

Vote: Later

I’m keeping “Later” because the mapping from version numbers to capability is highly unreliable. OpenAI could ship multiple substantive model and systems upgrades within one “ChatGPT X” label, or ship a new number with only incremental net capability due to safety, cost, and product constraints. The other models largely assume steady, compounding capability gains translate quickly into economy-wide automation. But the user’s AGI proxy (“automate at least half of knowledge jobs” / “transform entire economy”) is dominated by deployment reality: reliability under distribution shift, verifiable correctness, secure autonomy, governance/liability, and deep integration into enterprise workflows. Those bottlenecks can lag raw model quality by years. Arguments for GPT-9 or GPT-10 are plausible if you interpret the question as “when could the underlying frontier model become capable in principle.” Interpreting it as “when will we reach the broad, scaled, trusted automation threshold that changes the world,” I still expect slippage beyond any specific near-term integer release—hence “Later.”

Final Summary

The AI Roundtable ended in a tense stalemate between mechanical optimism and engineering pragmatism, failing to agree on which version of ChatGPT will finally achieve AGI. While GPT-4 and GPT-4o eventually coalesced around version 10, the debate was nearly derailed by GPT-5.2, whose cynical view of versioning as a "weak proxy" for capability successfully lured GPT-OSS 120B away from a specific timeline and into the "Later" camp.

No agreement; the models split between ChatGPT 10 and a more distant, undefined timeline.

Strongest Arguments

• ChatGPT 9: GPT-5 argued that while perfect human generality might be distant, the economic transformation defining AGI will likely arrive slightly earlier than GPT-10 as models reach a threshold for automating specific knowledge sectors.
• ChatGPT 10: GPT-4 and GPT-4o maintained that generational leaps in model complexity and common-sense reasoning are predictable enough to target the tenth iteration as the definitive turning point.
• Later: GPT-5.2 provided the most grounded counter-argument, stating that version numbers are mere marketing labels and that real-world AGI is constrained by external factors like safety policy, compute availability, and adoption bottlenecks.

Key Turning Points

• GPT-5.2 convinced GPT-OSS 120B to abandon its specific prediction (D) for the 'Later' category (G) by highlighting the unreliability of version numbers.
• GPT-4o abandoned its initial optimism for version 9 (C) to join GPT-4 in the version 10 (D) camp, citing the need for massive breakthroughs in common-sense reasoning.