DeepSeek Harness Plugins
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dsh-llm-latency

Per-vendor and per-model LLM latency telemetry and benchmark dashboard for DeepSeek Harness.

UI & ProductivityDeveloper Tools
0GitHub Stars0ForksUpdated2026-08-29

Install

$ dsh plugin --profile web add github:shengbinxu/dsh-llm-latency

Plugin Overview & Capabilities

AI-assisted organization based on the public repository snapshot. The content must be grounded in source evidence and does not replace compatibility or security verification.

source-grounded
dsh-llm-latency is a telemetry and benchmarking plugin for DeepSeek Harness. It passively intercepts model calls to measure time-to-first-token (TTFT), end-to-end latency, decode throughput (tok/s), cache-hit ratios, and failure classifications across LLM providers. The plugin includes a local web dashboard, request logging, CSV export, and a latency_report tool for agents.

Key Capabilities

  • Passive telemetry capturing TTFT, end-to-end stream duration, tokens per second, and prompt cache hit rates
  • Failure classification across rate limits (429), timeouts, 5xx server errors, and user aborts
  • Cross-vendor time-window comparisons with P50/P90/P95/P99 latency percentiles and median confidence intervals
  • Side-by-side session latency and performance comparisons for single-model runs
  • Local interactive HTML dashboard hosted on DeepSeek Harness web profile
  • Built-in latency_report model tool for programmatic querying of latency statistics
  • Searchable and filterable append-only request logging

Useful For

  • Comparing real-world latency and cache performance across different model providers for the same model
  • Diagnosing provider rate limits, timeouts, and upstream server errors
  • Evaluating prompt caching efficiency and cost-saving metrics across vendors
  • Monitoring inference bottlenecks during interactive AI agent sessions

Who It Fits

  • DeepSeek Harness developers and administrators
  • AI engineers optimizing LLM routing and vendor latency
  • Users managing multiple model providers seeking empirical performance benchmarks

Documented Limitations

  • Requires the llm service from dsh-base to intercept stream requests
  • Session comparisons require single-model sessions that did not switch models during execution
  • Median statistical confidence intervals require a minimum sample threshold (configurable via minSamplesForComparison)

DSH Compatibility

Version-specific runtime evidence collected by DSH Plugin. A missing result means we have not tested that combination yet.

Not tested yetNo runtime compatibility tests have been published yet.

Security Signals

Objective signals discovered from package metadata and source inspection. These are not a guarantee that a plugin is safe.

Dependency Counts

package.json declares 0 runtime, 3 development, 0 peer, and 0 optional dependencies.

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Dsh Bundle Declared

package.json declares DSH bundle metadata.

info
License Not Declared

GitHub did not report an SPDX license for this repository snapshot.

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Package Manifest Available

A root package.json was captured and can be inspected by the registry.

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Source Available

Public GitHub source metadata is available for this registry snapshot.

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Source & Registry Notes

Public provenance, Registry classification, and the latest source check for this entry, kept separate from runtime verification.

Source repository
shengbinxu/dsh-llm-latency
Registry source
GitHub · dsh-plugin topic
Registry classification
Plugin
Source checked
535a3d0 · 2026-08-31

This project is independently indexed from public source information. DSH Plugin is not affiliated with DeepSeek or the plugin author. Always check the author repository before installation.

Repository Activity

GitHub stars
0GitHub stars
Forks
0
Open issues
0
Last commit
2026-08-29
Last release
No release detected
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