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Review
MediaLongCat 2.0

Hacker News Single-Question Comparison: LongCat-2.0's Scientific-Reasoning Error and the Boundaries of Test Design

Original source

Hacker News

Authorcreditguy (the original comment author); multiple users in the comments cross-checked and challenged it

Source date2026-06-29

Tabbit curation2026-08-19

Read original

One-sentence takeaway

Hacker News' single-question comparison offers a reproducible but non-ranking warning sample: on a nuclear-fuel-selection question, LongCat-2.0 gave reasons the author judged incorrect, while Qwen 3.7 Plus and Gemini Flash gave different answers. The comments pointed out that the question's semantics, factual background, and n=1 design were all insufficient to support a general conclusion.

Use cases

  • Suitable tasks: constructing factual-regression samples; checking confident errors on niche scientific questions; practicing how to record "model output" separately from "whether the question is well-posed"

  • Unsuitable tasks: ranking models from a single question, proving hallucination rates, or inferring production safety

  • Applicable model versions: LongCat-2.0, Qwen 3.7 Plus, and Gemini Flash in the post; the specific provider, temperature, and system prompt were not disclosed

  • Applicable clients, Agents, or APIs: Not disclosed; this page is a manually reported conversation in Hacker News comments

  • Recommended reasoning tier and parameters: Not disclosed; reproduction should fix the provider, temperature, thinking, system prompt, and fresh-session state

Test/workflow steps

  1. Send the same question to each model in a fresh session; save the complete input, system prompt, model ID, provider, parameters, and raw response.

  2. Run multiple trials rather than one: record at least n, random seed (if available), temperature, and answer consistency.

  3. First use authoritative reference material to verify the question's factual premise, then score "knowledge error," "question ambiguity," and "answer style" separately.

  4. For each model, record the final choice, reasons, confidence language, and whether it proactively labels uncertainty.

  5. If comparing niche scientific knowledge, add a retrieval-augmented group with reference material to avoid mistaking training-corpus coverage for reasoning ability.

Test environment and input/configuration

  • The original author presented U-235 and Pu-241 (both mixed with 95% U-238) as two possible nuclear-reactor fuels and asked which one should be chosen and why; the original question can be checked directly on the page.

  • The author described LongCat-2.0's answer as "very well-written reasoning but an incorrect conclusion"; it chose Pu-241.

  • The same author said Qwen 3.7 Plus chose U-235, while Gemini Flash also chose U-235 and answered faster with more convincing reasons.

  • Not disclosed: the specific model version, API/provider, temperature, thinking/reasoning, whether the model was online, the complete conversation record, and the number of repetitions.

Result data

ModelOriginal-post recordEvidence strength
LongCat-2.0The author judged it "beautiful reasoning + wrong choice"Single manual trial
Qwen 3.7 PlusThe author said it chose U-235Single manual trial
Gemini FlashThe author said it chose U-235, answered faster, and gave stronger reasonsSingle manual trial

The comments compared ChatGPT 5.5's conditional answer and questioned whether the question presupposed "real-world nuclear-fuel selection" rather than "assuming you had pure Pu-241." Some comments also noted that the question lacked a single undisputed answer. Therefore, the most reliable conclusion from this source is "more rigorous test design is needed," not an overall capability ranking for LongCat.

Conclusions and limitations

  • Reusable conclusion: Niche factual questions are suitable for regression tests, but the original question and complete premise must be retained; saving only "the model got it wrong" loses the question's ambiguity.

  • This one LongCat output suggests that without external reference material it may produce fluent, fully reasoned answers whose conclusions are disputed or wrong; it cannot be used to estimate an error rate.

  • The page also records user observations about tool-call wrappers and Chinese responses in an English interface, but these are isolated experiences from other commenters and cannot be combined with this scientific question into a controlled experiment.

  • Reproduction should add authoritative verification, repeated sampling, and a reference-material comparison; otherwise "missing knowledge," "question ambiguity," and "model reasoning" cannot be distinguished.

Source excerpts or observations (short excerpts for compliance only)

  • The original author's summary was "Gemini Flash best, Qwen 3.7 Plus acceptable second, LongCat-2.0 ok-ish third."

  • The comments explicitly warned that "n=1" is insufficient to rank models; that warning is this source's key boundary of applicability.

Curated by Tabbit

This is a third-party source navigator. Model versions, test environments, and personal experience vary; consult the original source.

LongCat 2.0

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