Who it is forA researcher or tester who needs evidence that a model gives the same answer regardless of how much memory the machine has.
The problemChanging memory settings can silently change results, which makes benchmarks and bug reports hard to trust.
The outcomeTwo runs with different presets print the same generated text, and only the timing lines differ.
What you need first
- A checkpoint directory of .safetensors shards (1.56 TB on disk for the released checkpoint)
- A packed trunk directory, created in a step the README excerpt does not show
- tiktoken.model and tokenizer_config.json in a directory, for text input
- A machine with a C toolchain for the portable C99 build (build steps are not in the excerpt)
- An HF_TOKEN environment variable if you use download-model.sh
Steps
- Run the laptop preset command with --ids so no tokenizer is needed: ./bin/k3 ~/k3model --ids 1008,10484,318,15383,387 --trunk ~/k3trunk --preset laptop --gen 8 --incremental (inferred, check the README)
- ./bin/k3 ~/k3model --trunk ~/k3trunk --preset server --tok ~/k3model --prompt "def fibonacci(n):" --gen 28 --incremental
- Save the generated text from each run.
- Diff the two outputs and confirm they match.
Prompt for your agent
In the repo FareedKhan-dev/kimi-k3-in-c, run the same prompt with the laptop preset and the server preset, using --incremental. Expect two generated text blocks with timing lines. Verify that the generated text is byte-identical between the two runs.
Caveat. The README reports byte-identical output across machine sizes, but the server run needs a machine with far more memory and is only a timing comparison in practice.
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