Expired60% confidenceFactExact time
The cost of output tokens in LLMs is typically 3–6 times that of input tokens, because generation requires autoregressive token-by-token inference.
2
Sources
60%
Confidence
Medium-term (~90 days)
Relevance
7/2/2026
First Seen
Valid until: 9/30/2026(expired)
Sources
Frontier Code Deep Dive: Code That Runs ≠ Code That Merges — A Quality Revolution in Programming Benchmarks
bilibili烟神殿副殿主6/9/2026
Related Claims
UnverifiedOutput tokens are typically more expensive than input tokens because outputs require autoregressive token-by-token generation, which has higher computational intensity and lower GPU utilization.65% similarUnverified在百万级样本的批量预测场景中，LLM的推理成本可能比树模型高出三到四个数量级65% similarUnverifiedLLM生成阶段对词汇表（通常包含32,000至128,000个token）计算Softmax概率分布，形成总和为1的概率向量63% similarUnverifiedThe inference cost of large language models bears an approximately linear relationship to the number of model parameters, and the input token cost of GPT-4-level models is typically 10–30 times that of small specialized models.61% similarUnverifiedIndustry estimates suggest that the inference cost of mainstream frontier models is approximately several times to tens of times the training cost.61% similar
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