HWBench

Minisforum MS-R1 (as tested by Jeff Geerling): edge AI benchmarks

Vendor (independent test)Form factor independent test systemCompute CPUIndicative price unknownPower envelope unknownPublished rows 3

Key results

Best published result per workload for Minisforum MS-R1 (as tested by Jeff Geerling)
WorkloadBest resultModel · precisionPower · perf/WGrade · dateSource
LLM generation12.12 tok/s CPU-only
batch 1
Llama 3.2:3b
as in linked issue (Ollama default tags are 4-bit) · Ollama / llama.cpp (see linked issue)
35.00 W (measured)
0.346 tok/s/W
C 2026-09-22 (page last edited)Jeff Geerling ai-benchmarks README (Findings tables)

Best published result per workload, across model sizes. For like-for-like groups, open the per-workload tables below.

Show data — per-workload tables

object detection

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No published object detection results for Minisforum MS-R1 (as tested by Jeff Geerling) yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.

instance segmentation

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No published instance segmentation results for Minisforum MS-R1 (as tested by Jeff Geerling) yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.

pose estimation

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No published pose estimation results for Minisforum MS-R1 (as tested by Jeff Geerling) yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.

image classification

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No published image classification results for Minisforum MS-R1 (as tested by Jeff Geerling) yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.

semantic segmentation

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No published semantic segmentation results for Minisforum MS-R1 (as tested by Jeff Geerling) yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.

speech-to-text

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No published speech-to-text results for Minisforum MS-R1 (as tested by Jeff Geerling) yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.

LLM generation

Like-for-like groupBest resultModel · precision · stackGradePowerSource · dateRank in group
LLM 5–14B · b=13.39 tok/s CPU-onlyDeepSeek R1 14b
as in linked issue (Ollama default tags are 4-bit) · Ollama / llama.cpp (see linked issue)
C38.40 W measuredJeff Geerling ai-benchmarks README (Findings tables)
2026-09-22 (page last edited)
50 of 54
LLM ≤4B · b=112.12 tok/s CPU-onlyLlama 3.2:3b
as in linked issue (Ollama default tags are 4-bit) · Ollama / llama.cpp (see linked issue)
C35.00 W measuredJeff Geerling ai-benchmarks README (Findings tables)
2026-09-22 (page last edited)
58 of 65
LLM >40B · b=10.770 tok/s CPU-onlyLlama 3.1:70b
as in linked issue (Ollama default tags are 4-bit) · Ollama / llama.cpp (see linked issue)
C38.20 W measuredJeff Geerling ai-benchmarks README (Findings tables)
2026-09-22 (page last edited)
10 of 11
How to read these numbers
Every number is labelled. Confidence: A MLPerf closed, audited · B documented third-party method · C community / review · D vendor-published, not independently verified · E estimate. Power basis: measured with the result · spec vendor spec/envelope · power n/a not published.

Machine-readable: /find.json (see llms.txt); full tables are in “Show data”. Confidence grades: A audited MLPerf closed · B documented third-party · C community · D vendor-published · E estimate. Unknown values are shown as unknown, never estimated. Generated 2026-10-16 from public sources.