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SYS · ONLINEUPTIME · 100%2026 · operator-owned
RUNLOCALAI · v38
  1. >
  2. Home
  3. /Benchmarks
  4. /Llama 3.3 70B Instruct × Apple M3 Ultra
◯Community submitted
Editorial benchmark

Llama 3.3 70B Instruct on Apple M3 Ultra

Measured this month.

Why trust this benchmark?

Measurement

tok/s
12.0
TTFT
1850 ms
VRAM used
—
RAM used
—
Power
—
Quant
Q4_K_M
Context
4K
Run date
2026-05-13
Source
community

V36.52 rigor detail

Protocol →
Steady-state median
12.00 tok/s
Runs captured
5
Scenario
Single-stream
Editorial notes

Public-source seed (V37 2026-05-13). Cross-referenced from the URL above. Tagged 'medium' confidence — we reserve 'high' for owner-run measurements.

Why this confidence tier?

Moderate confidence

Confidence is rule-based. Every factor below contributed to the tier. We never expose a single numeric score; the tier label is auditable through this explanation alone.

Factors
  • +Source: community submission
How to improve this benchmark's confidence
  • Reproduce this benchmark →An independent reproduction with matching numbers lifts the tier and reduces single-source risk.
  • Read the confidence methodology →Full editorial standards for tiering.
  • Why we don't use percentages →Tier labels — auditable, no opaque score.

Cohort intelligence

How this measurement compares to the rest of the corpus. Only comparable rows (same model + hardware first, with relaxations labelled) are used. We never average across runtimes or quant formats unless explicitly told to.

Insufficient comparison data. Insufficient cohort (0 comparable measurements). Outlier detection requires ≥5.

Same model, different hardware

2 matching rows

What this model looks like on adjacent hardware. Drives the 'should I upgrade?' question.

Median tok/s
11.4
Spread
8.0 – 14.8
  • 14.8 tok/srtx-4090Q4_K_M✓Editorial
  • 8.0 tok/srtx-4090Q4_K_M✓Editorial

Reproduce this benchmark

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Related

Drill into the entity pages for this measurement.

Llama 3.3 70B Instruct model page
Apple M3 Ultra hardware page
All measurements for this exact pair
Try Apple M3 Ultra in the build engine

Cite or export

Reference this benchmark in your work. Multiple formats; CC-BY attribution required.

Cite this benchmark or paste it into a README. Copy-to-clipboard; license is CC-BY-4.0 (attribution to RunLocalAI required).

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<a href="https://runlocalai.co/benchmarks/343" rel="noopener">RunLocalAI: Llama 3.3 70B Instruct on Apple M3 Ultra — 12.0 tok/s</a>

Direct download: .json · .md · .bib · .svg

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