Seed

Seed controls the random number generator used for stochastic sampling. A fixed integer makes generation reproducible — the same prompt with the same model and the same parameters produces the same output. The default sentinel maps to a time-based seed, giving non-deterministic output on every run.

Quick reference
Type int
Default 0xFFFFFFFF (sentinel — time-based seed inside llama.cpp)
Range Any int value; default sentinel is a signed-int reinterpretation of 0xFFFFFFFF
Category Core sampling
Field on SamplerParameters.Seed

What it does

Seed initializes the sampler’s pseudo-random number generator. The RNG drives every stochastic choice — which token to pick from the candidate pool when multiple tokens survive filtering.

  • A specific integer (42, 12345, etc.) — deterministic. Two runs with the same seed and identical parameters produce identical token sequences.
  • The default sentinel 0xFFFFFFFF — llama.cpp substitutes a time-based seed. Output varies per run.

Seed only matters when sampling is actually stochastic. At Temperature = 0 the sampler is greedy (always picks the top token), and Seed has no effect.

When to change it

Scenario Value
Default non-deterministic behavior unchecked((int)0xFFFFFFFF) (default)
Reproducible tests and benchmarks A fixed int, e.g., 42
Per-request seeding (rotate value per request) Pass a computed int from your caller

Set Seed when writing tests that assert on specific output, or when building regression suites that catch sampling drift across SDK versions.

Example

var preset = new Qwen25Preset();
preset.SamplerParameters.Temperature = 0.7f;
preset.SamplerParameters.Seed = 42;

using var api = AsposeLLMApi.Create(preset);
string reply1 = await api.SendMessageAsync("Write one short sentence about rain.");
string reply2 = await api.SendMessageAsync("Write one short sentence about rain.");
// reply1 and reply2 are identical because Seed is fixed and history is the same.

For deterministic single-request output:

preset.SamplerParameters.Temperature = 0.0f;
// Temperature 0 = greedy; Seed becomes irrelevant.

Interactions

  • Temperature — at Temperature = 0, Seed has no effect.
  • Mirostat — uses its own adaptive process; Seed still affects the underlying RNG but the entropy target dominates.
  • Session history — a fixed Seed only produces identical output when the entire preceding history is identical. A fresh session and a loaded session with the same history will both honor the seed.

Notes

Reproducibility is deterministic within the same SDK version and BinaryManagerParameters.ReleaseTag. Upgrading the SDK or the llama.cpp release tag may shift token sequences slightly even with the same Seed.

What’s next

MinP MinKeep