Smolbenchmark creator East-Muffin-6472 claims its released benchmark ranks models fitting in 8GB by device-specific decode speed, energy efficiency, and heat, potentially making local model selection reflect hardware constraints rather than server-based leaderboards.
state: watchingheat: lowuncertainty: highconvergesscott: mediumlocal-inference inference-economicsEast-Muffin-6472
What is this?
The case describes Smolbenchmark as a released hardware-specific model-selection benchmark attributed to the handle East-Muffin-6472, who claims it compares models fitting in 8GB by decode speed, energy efficiency, and heat. An evidence title describes initial repository scripts comparing tokens per second, tokens per joule, and power consumption, but neither the repository contents nor the release post is supplied here. None of the web snippets directly corroborates Smolbenchmark, its creator, or its measurement methodology; they establish only the broader context of hardware-constrained model selection, including an existing LLM-Perf leaderboard described as supporting GPU-specific selection.
Why it matters to Scott
Smolbenchmark’s claimed device-specific selection approach converges with Scott’s Hardware-aware local inference practice and could inform model choices for his gamepc/Ollama bulk workloads—not merely illustrate a general preference for better benchmarks. This is a candidate tool to evaluate, not a validated recommendation: the supplied evidence establishes neither methodology nor compatibility with his setup, and the radar’s related benchmarking and power-telemetry cases do not track this same release.
dev:concept.hardware-aware-local-inferencedev:project.gamepcdev:technology.ollamaradar:concept.local-inferenceradar:concept.inference-economicsradar:ctx-cliff-local-inference-benchmarkradar:tracarbon-local-llm-power-telemetryradar:artificial-analysis-mobile-llm-benchmark
queries asked of Scott's wikis
- local inference model selection memory limits quantization
- inference economics tokens per joule power thermal constraints
- hardware-specific benchmarks versus leaderboard rankings
- local agent workloads latency throughput task quality tradeoffs
- local model evaluation harness hardware telemetry
Measured heat
now 0 pts/hpeak 0 pts/hcomments 0/hpeers p14momentum: steady3 platformsage 3314h
points/hour across evidence · reading as of 2026-10-12 02:59:37.977291+11:00 · deterministic, not a model opinion
How the heat travelled
Evidence (5) — ⭐ canonical anchor
Interpretation history
2026-09-21T19:35:45Z
MicroLLM lab adds another independently announced hardware-local benchmark, but neither validates Smolbenchmark nor resolves its missing quality and energy-accounting evidence. This is modest expansion of the surrounding category, not spreading adoption of this release; Smolbenchmark remains a low-attention candidate rather than a dependable selection tool.
2026-09-21T19:22:49Z
evidence attached: hn.story.49791343 — This browser benchmark adds device-specific speed and accuracy evidence to the ongoing local-model evaluation case.
2026-09-17T07:29:00Z
Compute:Arena adds a separate entrant in hardware-specific local-model benchmarking, not independent validation of Smolbenchmark's measurements or energy methodology. It strengthens the surrounding pattern without changing this tool's readiness for Scott's model-selection decisions.
2026-09-17T07:22:35Z
evidence attached: hn.story.49737278 — The open-source Compute:Arena benchmark independently expands device-specific local-model measurement, materially informing the same hardware-aware evaluation question.
2026-09-16T10:25:40Z
The creator now supplies a concrete Jetson result and some protocol details, moving Smolbenchmark from a broad release claim toward an inspectable implementation. This remains single-source evidence, with the energy accounting and usefulness beyond Jetson hardware unresolved.
2026-09-16T10:22:12Z
evidence attached: reddit.post.1wht8zl — Adds protocol and device-level speed, energy, and thermal measurements for the existing small-model hardware benchmark.
2026-09-12T15:27:30Z
grounded: converges/medium — Smolbenchmark’s claimed device-specific selection approach converges with Scott’s Hardware-aware local inference practice and could inform model choices for his
2026-09-12T15:24:44Z
origin walked (codex/luna, conf 0.96): anchor reddit.post.1weekio -> echo.github.7c3941cdc3 by Yuvraj Singh
2026-09-12T15:22:50Z
case created — The creator reports a live chart covering 13 model families and roughly 1,000 configurations on one Jetson device, but broader hardware coverage and measurement validity remain unestablished.
Decision trace
- 10-06 13:20drop_targetsquiet through full ladder or over cap 8
- 09-29 09:02drop_targetsquiet through full ladder or over cap 8
- 09-22 05:35repriceMicroLLM lab adds another independently announced hardware-local benchmark, but neither validates Smolbenchmark nor resolves its missing quality and energy-accounting evidence. This is modest expansio
- 09-22 05:22attachThis browser benchmark adds device-specific speed and accuracy evidence to the ongoing local-model evaluation case.
- 09-22 05:22propose_attachThis browser benchmark adds device-specific speed and accuracy evidence to the ongoing local-model evaluation case.
- 09-19 12:30review_screenThe only change removes a comment asking how cherry-picked or bad runs are detected; it adds no new benchmark result, corroboration, contradiction, release, or access change.
- 09-18 00:41review_screenThe added comment raises a general concern about cherry-picked or unreliable community benchmarks but provides no new evidence or changed assessment.
- 09-17 17:29repriceCompute:Arena adds a separate entrant in hardware-specific local-model benchmarking, not independent validation of Smolbenchmark's measurements or energy methodology. It strengthens the surroundi
- 09-17 17:22attachThe open-source Compute:Arena benchmark independently expands device-specific local-model measurement, materially informing the same hardware-aware evaluation question.
- 09-17 17:22propose_attachThe open-source Compute:Arena benchmark independently expands device-specific local-model measurement, materially informing the same hardware-aware evaluation question.
- 09-16 20:25repriceThe creator now supplies a concrete Jetson result and some protocol details, moving Smolbenchmark from a broad release claim toward an inspectable implementation. This remains single-source evidence,
- 09-16 20:22attachAdds protocol and device-level speed, energy, and thermal measurements for the existing small-model hardware benchmark.
- 09-16 20:21propose_attachAdds protocol and device-level speed, energy, and thermal measurements for the existing small-model hardware benchmark.
- 09-13 09:22review_screenThe only new comment is supportive opinion about the benchmark's relevance and does not add new results, validation, hardware coverage, or other material evidence.
- 09-13 09:20sensor_dirtycomment_update
- 09-13 02:26review_screenThe changes add suggestions and opinions about context limits, reproducibility, output quality, and related work, but provide no new implementation result, validation, hardware coverage, or other mate
- 09-13 02:21sensor_dirtycomment_update
- 09-13 01:27groundSmolbenchmark’s claimed device-specific selection approach converges with Scott’s Hardware-aware local inference practice and could inform model choices for his gamepc/Ollama bulk workloads—not merely
- 09-13 01:24promote_anchororigin walk conf 0.96
- 09-13 01:22createThe creator reports a live chart covering 13 model families and roughly 1,000 configurations on one Jetson device, but broader hardware coverage and measurement validity remain unestablished.