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https://github.com/deepseek-ai/deepseek-harness.git
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Turtle
12c33f6d0c
Record budgeted benchmark endpoints and peak memory, and render a self-contained interactive report that rescales measured times to reviewed laptop and cloud profiles by single-thread CPU rating and default-disk latency, and compares peaks with 4 GB and 8 GB of available memory.
60 lines
4.7 KiB
TypeScript
60 lines
4.7 KiB
TypeScript
/**
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* Reviewed machine profiles for the scaled-scenario benchmark report.
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*
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* `cpuScore` is the PassMark single-thread rating retrieved on 2026-10-07 from cpubenchmark.net. Measured
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* endpoints run on one JavaScript thread, so the report scales their CPU-bound share by the single-thread
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* ratio; core count and memory size are not modelled. PassMark ratings across ISAs, and for burstable or
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* shared vCPUs, are coarse.
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*
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* `ioLatencyUs` is a typical synchronous 4 KiB random-access latency at queue depth 1 for the profile's
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* default storage. Laptop values come from published SSD reviews for the interface generation; cloud values
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* come from the provider's documented latency class for its default system disk. They are estimates.
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*/
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/** Group shown as one row of scenario choices in the report. */
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export type MachineProfileGroup = 'laptop' | 'cloud' | 'reference'
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/** One modelled machine with its CPU and default-storage performance. */
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export interface MachineProfile {
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readonly id: string
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readonly group: MachineProfileGroup
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readonly label: string
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readonly cpu: string
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readonly cpuScore: number
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readonly storage: string
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readonly ioLatencyUs: number
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/** Lower-case substrings of `os.cpus()[0].model` that identify the measuring machine as this profile. */
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readonly cpuModelMatches?: readonly string[]
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}
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/** Profiles in report order. */
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export const MACHINE_PROFILES: readonly MachineProfile[] = [
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{ id: 'laptop-2015-win', group: 'laptop', label: '2015 Windows laptop', cpu: 'Intel Core i5-5200U', cpuScore: 1486, storage: 'SATA SSD', ioLatencyUs: 90 },
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{ id: 'laptop-2015-mac', group: 'laptop', label: '2015 MacBook Pro 13"', cpu: 'Intel Core i5-5257U', cpuScore: 1737, storage: 'PCIe AHCI SSD', ioLatencyUs: 90 },
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{ id: 'laptop-2019-win', group: 'laptop', label: '2019 Windows laptop', cpu: 'Intel Core i5-8265U', cpuScore: 2003, storage: 'NVMe PCIe 3.0 SSD', ioLatencyUs: 70 },
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{ id: 'laptop-2023-win', group: 'laptop', label: '2023 Windows laptop', cpu: 'Intel Core i5-1335U', cpuScore: 3241, storage: 'NVMe PCIe 4.0 SSD', ioLatencyUs: 55 },
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{ id: 'laptop-2023-mac', group: 'laptop', label: '2023 MacBook Air', cpu: 'Apple M2', cpuScore: 4208, storage: 'Apple SSD', ioLatencyUs: 55, cpuModelMatches: ['apple m2'] },
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{ id: 'laptop-2026-win', group: 'laptop', label: '2026 Windows laptop', cpu: 'Intel Core Ultra 5 225H', cpuScore: 4247, storage: 'NVMe PCIe 4.0 SSD', ioLatencyUs: 50 },
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{ id: 'laptop-2026-mac', group: 'laptop', label: '2026 MacBook', cpu: 'Apple M5', cpuScore: 6341, storage: 'Apple SSD', ioLatencyUs: 50, cpuModelMatches: ['apple m5'] },
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{ id: 'aws-t3', group: 'cloud', label: 'AWS t3.medium', cpu: 'Intel Xeon Platinum 8259CL', cpuScore: 1948, storage: 'EBS gp3', ioLatencyUs: 500 },
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{ id: 'aws-m6i', group: 'cloud', label: 'AWS m6i.large', cpu: 'Intel Xeon Platinum 8375C', cpuScore: 2474, storage: 'EBS gp3', ioLatencyUs: 500 },
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{ id: 'aws-m7i', group: 'cloud', label: 'AWS m7i.large', cpu: 'Intel Xeon Platinum 8488C', cpuScore: 3113, storage: 'EBS gp3', ioLatencyUs: 500 },
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{ id: 'aws-m7g', group: 'cloud', label: 'AWS m7g.large', cpu: 'AWS Graviton3 (Neoverse V1)', cpuScore: 1554, storage: 'EBS gp3', ioLatencyUs: 500 },
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{ id: 'gcp-n2', group: 'cloud', label: 'GCP n2-standard-4', cpu: 'Intel Xeon Platinum 8273CL', cpuScore: 2200, storage: 'pd-balanced', ioLatencyUs: 800 },
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{ id: 'azure-d4s-v5', group: 'cloud', label: 'Azure D4s v5', cpu: 'Intel Xeon Ice Lake (8375C rating)', cpuScore: 2474, storage: 'Premium SSD P10', ioLatencyUs: 1000 },
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{ id: 'aliyun-g7', group: 'cloud', label: 'Alibaba Cloud ecs.g7.xlarge', cpu: 'Intel Xeon Ice Lake (8375C rating)', cpuScore: 2474, storage: 'ESSD PL0', ioLatencyUs: 400 },
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{ id: 'github-ubuntu-24.04', group: 'reference', label: 'GitHub ubuntu-24.04 runner', cpu: 'AMD EPYC 7763', cpuScore: 2517, storage: 'Azure managed disk', ioLatencyUs: 300, cpuModelMatches: ['epyc 7763'] },
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{ id: 'github-ubuntu-24.04-genoa', group: 'reference', label: 'GitHub ubuntu-24.04 runner (Genoa)', cpu: 'AMD EPYC 9V74', cpuScore: 2888, storage: 'Azure managed disk', ioLatencyUs: 300, cpuModelMatches: ['epyc 9v74'] },
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{ id: 'reference-m4-pro', group: 'reference', label: 'Calibration reference', cpu: 'Apple M4 Pro', cpuScore: 4547, storage: 'Apple SSD', ioLatencyUs: 55, cpuModelMatches: ['apple m4'] },
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]
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/**
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* Identify the measuring machine among the reviewed profiles.
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* @param cpuModel - `os.cpus()[0].model` of the machine that ran the benchmarks.
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* @returns the matching profile id, or `undefined` when no profile describes the machine.
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*/
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export function matchMachineProfile(cpuModel: string): string | undefined {
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const model = cpuModel.toLowerCase()
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return MACHINE_PROFILES.find(profile => profile.cpuModelMatches?.some(match => model.includes(match)) === true)?.id
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}
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