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As the context grows, all LLMs appear to turn into idiots, even just at 32k! > We evaluate 12 popular LLMs that claim to support contexts of at least 128K toke
by consumer451 1y ago
As the context grows, all LLMs appear to turn into idiots, even just at 32k!
> We evaluate 12 popular LLMs that claim to support contexts of at least 128K tokens. While they perform well in short contexts (<1K), performance degrades significantly as context length increases. At 32K, for instance, 10 models drop below 50% of their strong short-length baselines. Even GPT-4o, one of the top-performing exceptions, experiences a reduction from an almost-perfect baseline of 99.3% to 69.7%.
https://news.ycombinator.com/item?id=44107536 https://news.ycombinator.com/item?id=44107536
- rs186 1y agoThis paper is slightly outdated by LLM model standards -- GPT 4.1 or Gemini 2.5 haven't been released at that time.
- consumer451 1y agoYes, I mentioned that in the comment in the linked post. I wish someone was running this methodology as an ongoing project, for new models. Ideally, isn't this a metric that should be included on all model cards? It seems like a crucial metric.
- humpty-d 1y ago[dead]