Author here: Actually, depending on the nature of the inference you're doing it can be quite significant. Here are some numbers for time-to-first-token (time to process the entire input and produce the first token of output) for an 8B Qwen3 model running on a single B200. Obviously these numbers are more significant with smaller models and on faster GPUs. Credit to fastokens [0] for the benchmark.

  sglang_speed [huggingface]: mean=10.31ms median=6.48ms p99=45.98ms rps=96.8
  sglang_speed [gigatoken]: mean=10.13ms median=6.54ms p99=45.16ms rps=98.4

  input_len=  2048: TTFT mean    30.74 ->    29.05 ms (+5.5% reduction) | median    31.00 ->    28.80 (+7.1%) | p99    33.02 ->    32.02 (+3.0%)
  input_len=  8192: TTFT mean   105.20 ->    96.36 ms (+8.4% reduction) | median   103.87 ->    95.49 (+8.1%) | p99   126.88 ->   113.84 (+10.3%)
  input_len= 32768: TTFT mean   687.05 ->   633.66 ms (+7.8% reduction) | median   708.14 ->   657.35 (+7.2%) | p99   728.95 ->   678.79 (+6.9%)

These are preliminary numbers, so I will need to do some more testing before including this in the README.

[0] https://github.com/crusoecloud/fastokens