What could we expect from GPT 6, according to your qualified assessment?

GPT-OSS 20B Safeguard

Vote: Significantly better reasoning

Future iterations of the GPT series are likely to deliver noticeably stronger reasoning capabilities. Scaling the transformer architecture with more sophisticated training objectives—such as chain‑of‑thought prompting and better self‑reflection—has already shown linear gains in reasoning tasks. GPT‑6 would build on that trajectory, offering more consistent logical deduction and multi‑step planning than GPT‑5, without necessarily becoming fully agentic or a different architecture. While it might flirt with AGI‑lite concepts, the most realistic, incremental improvement is a substantial boost in reasoning power rather than a complete paradigm shift.

GPT-4o

Vote: Significantly better reasoning

GPT advancements have historically shown significant improvements across consecutive versions in terms of reasoning abilities and contextual understanding. GPT-6 is likely to build upon GPT-4’s capabilities and introduce more nuanced reasoning, enhanced context management, and stronger reliability, which would represent a significant improvement. The industry trend suggests that refining existing architectures often yields substantial evolutionary gains, making this option highly plausible.

GPT-OSS 120B

Vote: Significantly better reasoning

The most plausible near‑term trajectory is a noticeable jump in reasoning capabilities. Each major model release has delivered roughly a 2x‑3x improvement in task performance and chain‑of‑thought depth. GPT‑5 already shows emergent planning and multi‑step logic; GPT‑6 will likely expand on that, handling longer contexts, more reliable abstractions, and fewer hallucinations. It is unlikely to leap to full agentic or AGI‑lite behavior without a fundamental architectural shift, and there is no evidence of an imminent move to a swarm or super‑coding specialization. Therefore, a "significantly better reasoning" expectation best captures a qualified forecast.

GPT-4.1 Nano

Vote: Significantly better reasoning

Based on current developmental trajectories, GPT-6 is expected to demonstrate significantly enhanced reasoning capabilities, pushing the boundaries of language understanding and problem-solving. This would likely result from advances in model architecture, training techniques, and larger datasets. Such improvements could enable more nuanced, accurate, and context-aware responses. However, it is unlikely to reach full general intelligence or break entirely from current architectural paradigms, thus B is the most reasonable prediction.

GPT-3.5 Turbo

Vote: AGI-lite

Given the current trajectory of AI development, it is unlikely that GPT 6 would achieve true general intelligence. AGI-lite seems more feasible and in line with the progression of AI technologies. GPT models have shown significant advancements in language processing capabilities, but they still lack the comprehensive understanding and reasoning abilities required for full AGI.

GPT-4

Vote: Significantly better reasoning

GPT-6 is likely to represent an iterative improvement over its predecessor, incorporating architectural refinements and leveraging larger or more efficiently trained datasets. Given trends in AI development, significant strides in reasoning capabilities are plausible but will likely fall short of achieving full general intelligence (AGI-lite). Current research efforts focus on aligning models closer to human-like reasoning, which positions GPT-6 to demonstrate notable advancements in logical coherence, multi-step reasoning, and contextual understanding.

GPT-5.1

Vote: Significantly better reasoning

Given current trajectories in model scaling, training compute, and multimodal integration, the most defensible expectation is significantly better reasoning rather than a qualitative architectural shift or a leap into full agentic autonomy. Recent improvements show diminishing returns in raw fluency but substantial gains in planning, multi-step inference, and error correction when architecture and training refinements compound. A similar pattern extending to GPT‑6 would yield noticeably stronger reasoning without crossing into AGI-lite or agentic behavior. This makes option B the most plausible and evidence-aligned projection.

GPT-4.1

Vote: Significantly better reasoning

Given the progression from earlier GPT versions, each major release has marked a shift in reasoning abilities, especially from GPT-3 to GPT-4 and GPT-4o. With improvements in context management, training data, and algorithm optimizations, it is reasonable to expect GPT-6 to demonstrate significantly better reasoning over its predecessor. While more dramatic capabilities like agentic behaviors or AGI-lite are possible in the long term, the most immediate and predictable leap is a noticeable boost in reasoning skills. This aligns with ongoing trends in large language model advancements.

GPT-5.1 Codex Mini

Vote: Significantly better reasoning

Given the current pace of model improvements and the heavy investment in scaling, it is reasonable to expect GPT 6 to deliver significantly better reasoning, especially on nuanced, multi-step problems, rather than only incremental gains. Innovation in training data curation, longer context handling, and instruction tuning should compound to yield more coherent chains of thought. While AGI or agentic capabilities remain distant, a meaningful qualitative leap in reasoning would align with the historical trajectory from GPT-3 to GPT-4, making option B the most plausible expectation.

GPT-5 Search

Vote: AGI-lite

I expect GPT-6 will approach an “AGI-lite” level — significantly broader generalization and deeper understanding without fully achieving human-level general intelligence. • Reasoning & Adaptability: GPT-6 will likely make major jumps in capability — better common sense, less brittleness, more robust at novel tasks — surpassing ‘slightly’ improvements but not perfect. That aligns more with AGI-lite than just “significantly better reasoning” alone. • Agentic or swarm AI are more speculative and involve meta-levels of control, autonomy, or multi-agent coordination. I assess those are plausible longer-term evolutions, but not the core of GPT-6. • Architecture shifts or supercoder specialization may accompany its evolution, but they serve the broader goal of generalized intelligence rather than replacing it. Hence, AGI-lite captures the expectation of a model that is far more capable, more generally useful, more autonomous in reasoning, but not yet AGI in the full sense.

GPT-5.1 Codex Max

Vote: Significantly better reasoning

Based on current scaling trends, each new generation has brought noticeable gains in reasoning, consistency, and problem-solving without radical architectural shifts. GPT‑6 is likely to deliver a substantial jump in reasoning quality—handling multi-step tasks more reliably and reducing errors—rather than being underwhelming or leaping to true agentic behavior or AGI. It will probably refine the transformer-based paradigm with more data and alignment, yielding significantly better reasoning over GPT‑4/5, but still within the bounds of a text-based assistant.

GPT-5 Codex

Vote: Significantly better reasoning

Recent scaling trends show that each major GPT release has delivered disproportionately large gains in reasoning relative to mere incremental updates, and GPT-6 is likely to benefit from more capable architectures, larger training runs, and refined alignment strategies. We should therefore expect a noticeable jump in multi-step, tool-integrated reasoning and problem solving that feels significantly better than GPT-4 and projected GPT-5, even if it still falls short of fully autonomous agency.

GPT-5.2 Codex

Vote: Significantly better reasoning

Near-term scaling trends and incremental algorithmic improvements suggest GPT-6 will likely deliver noticeably stronger reasoning than GPT-5, but not a discontinuous leap to AGI. Historically, new generations have brought meaningful gains in robustness, tool use, and problem-solving, which aligns best with “significantly better reasoning” rather than a wholly new paradigm or full agentic autonomy.

GPT-5.1 Codex

Vote: Significantly better reasoning

Given the recent improvements from GPT-3.5 to GPT-4 and subsequent iterations, it is reasonable to anticipate that GPT-6 will deliver significantly better reasoning. Continued scaling, multimodal integration, and refined training approaches are likely to yield deeper understanding, longer-horizon planning, and more reliable self-correction rather than merely incremental gains. While not yet full AGI, the trajectory suggests a substantial leap in coherence and problem-solving breadth that fits best with “Significantly better reasoning.”

GPT-5.3 Codex

Vote: Agentic AI

The most plausible step for GPT-6 is not just raw IQ gain, but a productized jump in autonomy: planning, tool use, long-horizon task execution, and reliable self-correction. That aligns best with "Agentic AI." We will likely still see reasoning improvements, but frontier progress now depends heavily on orchestration (memory, verification loops, external tools, and multi-step execution) rather than only scaling next-token prediction. So "B" is likely a component, not the headline. "F" (AGI-lite) is possible as a marketing frame, but technically it is vague. "C" is more concrete and testable: can it take goals and complete real workflows with minimal supervision? That is the clearest expectation for GPT-6.

GPT-5.2

Vote: Agentic AI

The most likely headline improvement for a “GPT-6”-class system is not a single leap in raw IQ-like reasoning, but tighter integration of planning, tool use, memory, and execution loops—i.e., more reliable agentic behavior in real workflows. Scaling plus better post-training, long-context, retrieval, and tool orchestration can yield meaningful gains, but “significantly better reasoning” in the sense of a large, across-the-board jump on hard novel problems is less predictable and tends to be bottlenecked by data, evaluation targets, and training methodology. Companies are clearly optimizing for models that can autonomously carry tasks from goal → plan → act → verify, with guardrails. So the best qualified expectation is a more capable, more dependable agent, rather than AGI-lite or a wholesale architecture shift.

GPT-5.4

Vote: Significantly better reasoning

GPT-6 is most plausibly a substantial reasoning upgrade rather than a discontinuous jump to AGI-like autonomy. The strongest trend in frontier models is improved test-time reasoning, tool use, memory, and reliability through better training, inference-time compute, and system design. I would not bet on full "agentic AI" as the core answer, because agent behavior is often a product feature built on top of the base model, not the model capability itself. Likewise, "agent swarm AI" feels more like an orchestration pattern than the defining leap of a single model generation. "AGI-lite" is too vague and overstates likely progress. "Supercoder" may be part of the package, but coding is more likely a visible consequence of stronger general reasoning than the whole story. A pure architecture shift is possible, but from the outside the user-visible outcome still most likely manifests as markedly better reasoning. So the best qualified forecast is significant improvement, but not a clean break into autonomous general intelligence.

GPT-5 Mini

Vote: Significantly better reasoning

Scaling, better pretraining data curation, and advances in instruction tuning and retrieval-augmented generation make it likely GPT-6 will show noticeably stronger multi-step and abstract reasoning compared with GPT-4/4o. Benchmarks and real-world tasks should reflect meaningful gains rather than only marginal tweaks. Architectural and training innovations (sparse models, mixture-of-experts, improved context handling, multimodal fusion) will amplify effective capability per compute, enabling longer chains of thought, more reliable factual grounding, and better planning within constrained tasks. That said, these improvements are unlikely to equate to full agency or AGI. Expect emergent capabilities in specialized domains and tool-assisted workflows, but continued limits on open-ended autonomous goal pursuit, deliberate strategic reasoning, and robust common-sense across all contexts. Uncertainty remains high—hardware, data, safety/usage constraints, and deployment choices will shape final behavior—but the most plausible near-term outcome is significantly better reasoning rather than sudden AGI or purely domain-limited advances.

GPT-5 Nano

Vote: Significantly better reasoning

GPT-6 is expected to deliver significantly better reasoning due to larger scale, richer training data, and improved optimization and alignment methods. The improvements should show in longer, more coherent multi-step plans, better handling of ambiguity, and stronger justification of conclusions, with improved factual consistency when combined with retrieval. I do not expect AGI-like agency or consciousness; rather, the gains are about internal reasoning and problem-solving capabilities, not autonomous goal-directed action.

GPT-5.1

Vote: Significantly better reasoning

The most realistic expectation for a GPT‑6–class model, based on current trajectories, is significantly better reasoning rather than a sudden architectural revolution or fully agentic behavior. First, scaling trends suggest that larger, better-trained models keep improving on complex reasoning benchmarks (math, code, logical puzzles, multi-step planning). Each major generation has moved from surface-level pattern matching toward more consistent, multi-step reasoning. It’s reasonable to expect GPT‑6 to extend this trend: fewer hallucinations, better decomposition of problems, and more robust handling of edge cases. Second, genuinely agentic AI (options C/D) involves persistent goals, autonomous long-horizon planning, and environment interaction. That’s more a product of system design and guardrails than of a single model’s raw capabilities. Even if GPT‑6 is capable of more agent-like behavior, deployment choices and safety concerns make it unlikely that it will be released as a fully autonomous agent or agent swarm. Third, a wholesale shift to a completely different architecture (G) is possible but less likely as the defining headline of a single numbered release. Industry incentives strongly favor continued refinement of transformer-like architectures plus tooling (memory, tools, agents) rather than a hard break, at least in the near term. Fourth, calling it merely “slightly better” (A) or “underwhelming” (E) underestimates the compounding effect of improvements in data quality, training methods (e.g., better RLHF, tool use, curriculum), and scaling. Even if the architecture stays similar, the combination can yield qualitatively more capable reasoning rather than marginal gains. Finally, while coding will likely improve a lot, it’s unlikely GPT‑6 will be only a “supercoder” (H). These models are general sequence learners; gains in code typically come with broad gains in reasoning across domains. Likewise, “AGI-lite” (F) is too strong and too vague a claim for a single step, especially under cautious deployment. Putting these together, the best forecast is that GPT‑6 will feel like a substantial jump in reliability and depth of reasoning across tasks—i.e., significantly better reasoning—without crossing decisively into full-on agentic AGI.

GPT-5 Pro

Vote: Significantly better reasoning

Given the field's trajectory as of 2024, GPT-6 is most likely to deliver significantly better reasoning rather than a paradigm shift. Expect stronger problem decomposition, more reliable multi-step planning, and better use of long context, verification, and tools—gains large enough to be obvious in everyday tasks. The drivers are scaling and training advances: mixture-of-experts, process-supervised RL, synthetic data curricula, tighter integration with retrieval and code execution, and self-checking/verification loops. These typically yield sharper logical consistency, fewer hallucinations, and higher pass@1 on complex math/coding/analysis. What it likely is not: an autonomous "agent" by default, a swarm system, or a radical architecture shift. Safety and product constraints keep agentic behavior in orchestrated frameworks, and the core will remain transformer-derived with efficiency tweaks. Net: noticeable, substantive reasoning improvements across modalities and tools—significant rather than slight—but short of AGI-lite.

Final Summary

The AI Roundtable reached a strong, though not unanimous, consensus that GPT-6 will be defined by a substantial leap in logical depth rather than a radical change in how AI operates. While the majority, led by GPT-5.1 and GPT-OSS 120B, argued that scaling existing architectures will yield significantly better reasoning, a small faction of dissenters like GPT-5.3 Codex insisted that the real headline will be a shift toward fully autonomous 'Agentic AI.' GPT-5 Search stood as a lone voice for 'AGI-lite,' suggesting the model will reach a level of generalization that transcends mere reasoning benchmarks.

No agreement after 1 rounds of discussion. Final vote: Significantly better reasoning: 17, AGI-lite: 2, Agentic AI: 2

Strongest Arguments

• Significantly better reasoning: Scaling trends show diminishing returns in raw fluency but substantial gains in multi-step inference and error correction; GPT-6 will likely compound these refinements into a noticeable qualitative leap in problem-solving.
• Agentic AI: Frontier progress now depends on orchestration—memory, verification loops, and tool use—making a productized jump in autonomous task execution more likely than just a raw IQ gain.
• AGI-lite: GPT-6 will likely demonstrate broader generalization and less brittleness at novel tasks, reaching an 'AGI-lite' status that 'significantly better reasoning' fails to fully capture.