deepseek-r1:70b
llama · 70.6B · Q4_K_M
NVIDIA NVIDIA_DGX_Spark (Cortex-X925)
122 GB · Ubuntu 24.04.4 LTS
Tested on June 27, 2026
Global Score
47 /100
Not Rec.
Hardware Fit
51/100
Quality
45/100
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Hardware
- Machine
- NVIDIA NVIDIA_DGX_Spark
- CPU
- Cortex-X925
- Cores
- 20 total (20 perf)
- Frequency
- 3.35 GHz
- RAM
- 122 GB
- GPU
- Device 2e12
- OS
- Ubuntu 24.04.4 LTS
- Arch
- arm64
- Power Mode
- performance
Performance
- Tokens/sec
- 4.7
- Standard deviation
- ±0.0
- First chunk latency
- 557 ms
- Time to first token
- 557 ms
- Load time
- 52.6 s
- Memory usage
- 49.5 GB (41%)
- Total tokens
- 1066
Score breakdown
Speed
4/50
Time to first token
20/20
Memory
27/30
Quality
Reasoning
3/20
Coding
1/20
Instruction following
14/20
Structured output
9/15
Math
8/15
Multilingual
10/10
Category levels
Reasoning: Poor Coding: Poor Instruction Following: Adequate Structured Output: Adequate Math: Adequate Multilingual: Strong
Metadata
- Spec version
- 0.2.1
- Runtime
- Ollama 0.30.10
- Model format
- GGUF
- Hardware profile
- HIGH-END
- Result hash
- 1cea48589e703b5ab049d10316edd85957b25560d7f28e899b646272de68f04e
Interpretation
Hardware fit: 51/100. Overall suitability: NOT RECOMMENDED (Global 47/100). Category profile: Reasoning: Poor, Coding: Poor, Instruction Following: Adequate, Structured Output: Adequate, Math: Adequate, Multilingual: Strong.
Disqualifiers
- Token speed too low: 4.7 tok/s (minimum: 7 tok/s for HIGH-END profile)
Bench Environment
Thermal: nominal Swap delta:
+0.2 GB
CPU load: avg 15% (peak 32%)
Run yours now
$
npm install -g metrillm@latest$
metrillmRequires Node 20+ and Ollama or LM Studio running
Or run without installing: npx metrillm@latest