Model artifact
Exact model name, revision, parameterization, quantization or precision, tokenizer, and serving configuration.
SPARK does not publish universal latency, throughput, GPU-efficiency, or cost-reduction numbers without the model, hardware, workload, and measurement method needed to interpret them.
Review the protocol ↓Workload-specific reports may be produced during evaluation. A result moves to this public page only after disclosure and publication rights are approved.
Any future benchmark table will link to a test record containing these fields. A chart without them is treated as illustrative UI, not proof.
Exact model name, revision, parameterization, quantization or precision, tokenizer, and serving configuration.
Accelerator model and count, CPU and memory profile, interconnect, region, and tenancy.
Input/output token distributions, context length, concurrency, request rate, warm-up, cache state, and duration.
Time to first token, inter-token latency, end-to-end latency by percentile, throughput, errors, and cost basis.
Task-specific dataset, scoring method, evaluator version, human-review process, and confidence interval.
Date, code or configuration digest, exclusions, raw-output retention, and reviewer approval.