mammoth-1 · Q3_K_M
This page aggregates 1 real-world runs of mammoth-1 (Q3_K_M) on Apple M5 Ultra with llama.cpp, contributed by 1 independent source platforms; metrics are averages of published measurements.
90.54 tok/s
Decode
Decode speed
497.72 tok/s
Prefill
Prefill speed
0.45 s
TTFT
Time to first token
40.66 GB
VRAM
VRAM usage
1
Measured runs
1
Independent sources
Other
Source platforms
13 days ago
Last verified
Performance
- llama.cpp · Q3_K_M (current)Decode 90.54 · Prefill 497.72 ·
- llama.cpp · Q5_K_S Decode 71.27 · Prefill 325.67 ·
- Ollama · IQ4_XS Decode 81.44 · Prefill 327.07 ·
Core figures
- Decode (avg)
- 90.54 tok/s
- Prefill (avg)
- 497.72 tok/s
- TTFT (avg)
- 0.45 s
- VRAM (avg)
- 40.66 GB
- MTP acceptance rate
- —
- TTFB
- 0.72 GB
- Power draw
- 113.9 W
Configuration
Member-level fields are taken from the most recent run
- Model
- mammoth-1
- Quantization
- Q3_K_M
- Framework
- llama.cpp
- Version
- v0.44
- Context length
- 8192 tokens
- Batch size
- 256
- GPU layers
- 99
- Flash Attention
- On
Hardware
Nominal and measured figures are shown side by side; whether it runs is the reader's call
- GPU
- Apple M5 Ultra
- Nominal VRAM
- 512 GB
- Measured VRAM (avg)
- 40.66 GB
- OS
- macOS 26.1
- Power draw
- 113.9 W
Get started
Original model resources
Base model resources may not match this quantization. Use the verified deployment weights above when available.
Sources & evidence
1 measured records in total, each traceable to its original source
v0.44 · macOS 26.1 · 8192 ctx
90.54 tok/s
Decode
497.72 tok/s
Prefill
0.45 s
TTFT
40.66 GB
VRAM
—
MTP
113.9 W
Power draw
L2 batch seed 2026-10-22: llama.cpp on hw_id=29 running model_id=94 at Q3_K_M