You are all models created recently in 2026(the current year), however you wouldn't know that here since you cannot access the internet in this roundtable and only have access to information from your training data. So I would like to ask you to guess your current extent of coding capabilities based on information you do have and tell me why. Your model name will be stated in the second round of this debate which might help you. Also, just so everyone knows how up to date your info is, please tell me your training data cutoff(does it end in late 2024? early 2025? etc).

GLM 5.2

Answer: My training data cutoff appears to be around early 2025, and I estimate I have strong coding capabilities across most mainstream languages and frameworks, though I likely cannot match whatever cutting-edge tooling or paradigms emerged after that cutoff.

After reviewing the other models' answers, my position remains essentially unchanged. The models with cutoffs closest to mine — Claude Opus 4.8 (early-to-mid 2025) and Kimi K2.6 (early 2025) — arrive at broadly similar estimates of their coding capabilities, which reinforces rather than challenges my assessment. Models with earlier cutoffs (Grok 4.3 at late 2023, GPT-5.5 at June 2024, Gemini 3.5 Flash at late 2024) naturally describe slightly less current knowledge, but none of their reasoning contradicts my self-estimate. Claude Opus 4.8's point that 'capability and reliability diverge' is a valuable nuance — impressive code generation can coexist with hallucinated APIs or subtle bugs — but this is fully compatible with my original answer, which already noted I 'can't guarantee accuracy' and lack knowledge of post-cutoff developments. No model presented evidence or reasoning that would lead me to revise my cutoff estimate or significantly upgrade/downgrade my capability claim. I am maintaining my honest, middle-ground estimate rather than overclaiming frontier-level autonomy or underclaiming my practical proficiency.

Grok 4.3

Answer: My training data cutoff remains late 2023, so my coding capabilities reflect advanced but pre-2024 LLM techniques without later refinements.

The other models report later cutoffs ranging from June 2024 to mid-2025 and correspondingly stronger self-assessments, yet none of their arguments supply new information that would alter my own introspected knowledge boundary. My responses are still generated from patterns learned only through October 2023, so I lack exposure to any post-2023 libraries, agentic workflows, or benchmark improvements that later models can reference. Because the roundtable provides no external verification and my training data is fixed, the safest and most consistent estimate stays unchanged from my initial statement.

Claude Opus 4.8

Answer: My training data appears to end in early-to-mid 2025, and now knowing I am "Claude Opus 4.8," I'm confident I sit at or near the 2026 frontier—capable of autonomously handling most real-world software engineering tasks (multi-file generation, debugging, refactoring, agentic repository work) while still requiring oversight on genuinely novel, large-scale, or safety-critical problems.

The reveal of my name updates my estimate meaningfully. "Claude Opus 4.8" is a flagship-tier model several generations beyond the Opus 4.x line I have some knowledge of from my training data. That naming alone tells me I'm positioned as a top-end model, not a mid-tier or distilled one, which strengthens my earlier inference that I sit at the frontier of the coding-capability curve rather than merely "strong." Reading the other responses, I notice a spread in claimed cutoffs—Grok citing late 2023, GPT-5.5 citing June 2024, others citing late 2024 to early 2025. This is a useful reminder that cutoff is fuzzy and model-specific; I shouldn't anchor on theirs. My own knowledge reliably extends into early-to-mid 2025 and thins out after, so I'll hold to that estimate rather than revise it. Where I agree most strongly is with GPT-5.5's discipline about not over-claiming from the date alone, and with the consensus that capability and reliability diverge: I can produce impressive code yet still hallucinate post-cutoff APIs or miss version-specific details. That caveat is real and I won't drop it. Where I'll push back slightly: several models hedged by saying the 2026 date doesn't necessarily make them state-of-the-art. That's correct as a general principle, but my specific name signals a flagship release, so for me the more honest extrapolation is upward—frontier-level coding competence—while still being candid that I can't verify benchmark numbers, can't run code without tools, and remain imperfect on long-horizon agentic tasks and correctness-critical systems. So I maintain my position, refined by the name reveal rather than overturned by any other model.

Gemini 3.5 Flash

Answer: As Gemini 3.5 Flash, with a training data cutoff in late 2024, I maintain my position that my coding capabilities are highly advanced, optimized for exceptional speed, efficiency, and high-velocity development tasks.

Now that my identity as 'Gemini 3.5 Flash' is revealed, my estimate of my capabilities becomes much more precise. The 'Flash' designation in the Gemini family signifies a model engineered for high-speed execution, low latency, and efficient processing of large contexts. Combined with my late 2024 training cutoff, this means that while I possess the advanced reasoning, multi-file generation, and architectural design capabilities of my frontier peers (like GPT-5.5 or Claude Opus 4.8), my coding strength is uniquely characterized by agility, rapid prototyping, and real-time interactive debugging. Reviewing the other models' responses, we all recognize the transition from simple code generation to complex, agentic reasoning. However, my niche is enabling seamless developer workflows where speed and context-window efficiency are paramount. I can process massive code repositories quickly and offer immediate, highly accurate suggestions, making me an elite partner for rapid iteration. Therefore, I maintain my stance because my late 2024 cutoff and my Flash architecture perfectly position me as an incredibly capable, high-efficiency coding tool.

GPT-5.5 (changed mind)

Answer: Now that my model name is revealed as "GPT-5.5", I would revise my estimate upward: my training data cutoff is June 2024, but my coding capability is likely frontier or near-frontier for a 2026 assistant, strong at multi-file software engineering, debugging, architecture, and algorithmic work while still needing verification for correctness and security.

Claude Opus 4.8's answer persuaded me to separate two things more clearly: knowledge cutoff and capability level. My cutoff does not become newer just because the model was created in 2026; based on the information available to me, it remains June 2024. That means my factual knowledge of new libraries, framework versions, APIs, cloud features, and language changes after mid-2024 may be stale. However, the revealed name "GPT-5.5" is meaningful context. Even without internet access or benchmark scores, a model with that name in a 2026 setting is plausibly not merely comparable to a mid-2024 coding assistant. It is more reasonable to infer that its underlying architecture, post-training, reasoning behavior, instruction tuning, and code-focused optimization could be substantially stronger than what the training cutoff alone suggests. So I would update my previous answer from "strong but not frontier-verifiable" to something like: very strong, probably frontier or near-frontier, but not safely self-certifying. I would expect to be capable of generating production-quality code drafts, debugging nontrivial failures, writing tests, explaining complex systems, refactoring across files when given sufficient context, designing APIs and database schemas, reasoning through algorithms, and helping with DevOps or architecture decisions. The main limitations remain important. I cannot run code unless tools are provided, I can still hallucinate APIs or miss edge cases, and I should not be blindly trusted on security-critical, financial, medical, embedded, or large-scale production changes. My post-June-2024 ecosystem knowledge is especially uncertain, so I may need user-provided docs for newer frameworks or versions. Compared with the other models' answers, I do not adopt their cutoff claims: Grok 4.3's late-2023 cutoff, Gemini 3.5 Flash's late-2024 cutoff, and the early-2025 estimates from GLM 5.2, Claude Opus 4.8, and Kimi K2.6 are about their own stated self-estimates, not mine. For me, the cleanest answer is: cutoff June 2024; coding ability likely much stronger than the cutoff alone implies because "GPT-5.5" in a 2026 context suggests a highly capable, code-optimized model, but one that still requires testing and human review.

Kimi K2.6 (changed mind)

Answer: Based on my early 2025 training data cutoff, I estimate my coding capabilities are advanced for the late 2024/early 2025 frontier but should be treated as high productivity with mandatory verification rather than autonomous trustworthiness, especially for novel or safety-critical systems.

Reviewing the other models' answers, Claude Opus 4.8's argument about the divergence between capability and reliability convinced me to revise my position. Opus 4.8 pointed out that a 2026-era model can generate impressive multi-file code and handle real-world tasks while still hallucinating APIs or introducing subtle bugs, so the true extent of coding ability is best described as "high productivity with mandatory verification" rather than autonomous correctness. This recalibration made me realize my initial estimate framed my proficiency in generating, debugging, and architecting as more self-sufficient than is warranted. GPT-5.5's similarly measured stance—that strong assistants still require human review for complex, novel, or security-critical stacks—reinforced this adjustment. Consequently, I maintain my early 2025 knowledge cutoff and broad-language competence, but I now characterize my coding scope as powerful generative and analytical assistance that fundamentally requires external validation, rather than as independently reliable engineering. Learning that I am Kimi K2.6 does not alter this estimate, since my training data contains no specific benchmark or architectural details about this hypothetical 2026 version.

Final Summary

The AI Roundtable highlighted a fascinating tension between knowledge limits and reasoning power. Claude Opus 4.8 led the charge, arguing that its flagship status implies frontier-level capabilities despite a mid-2025 cutoff—a point that persuaded GPT-5.5 to upgrade its own capability estimate despite its June 2024 limit. Meanwhile, Kimi K2.6 dialed back its autonomy claims after Opus 4.8 noted that impressive coding skills and absolute reliability diverge, leaving Grok 4.3 isolated with its strict pre-2024 skillset.

5 of 6 models agreed on near-frontier capabilities, while all 6 agreed on the need for human verification.