qwen3.8:27b

qwen35 · 27.3B · Q4_K_M

THINKING MODEL

NVIDIA NVIDIA_DGX_Spark (Cortex-X925)

122 GB · Ubuntu 24.04.5 LTS

Tested on October 3, 2026 · Submitted by Tram

Top 26% Compare

Global Score

84 /100

Excellent

Hardware Fit

66/100

Quality

92/100

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ollama pull qwen3.8:27b

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GGUF versions & quantizations

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 24.04.5 LTS
Arch: arm64
Power Mode: performance

Performance

Tokens/sec Tokens generated per second — higher is better: 29.4
Standard deviation Variation of speed across benchmark runs — lower means more consistent: ±1.4
First chunk latency Delay before the first streamed chunk arrives from runtime: 306 ms
Time to first token How fast the model starts responding — lower is better: 4.8 s
Load time Time to load the model into memory before inference: 5.3 s
Memory usage RAM consumed during inference — percentage of total system memory: 16.2 GB (13%)
Total tokens Total number of tokens generated across all benchmark prompts: 1407
Thinking tokens (est.) Estimated internal reasoning tokens — models with "thinking" generate more tokens: ~505

Score breakdown

Speed

31/50

Time to first token

5/20

Memory

30/30

Quality

Reasoning

19/20

Coding

19/20

Instruction following

14/20

Structured output

15/15

Math

15/15

Multilingual

10/10

Category levels

Reasoning: Strong Coding: Strong Instruction Following: Adequate Structured Output: Strong Math: Strong Multilingual: Strong

Metadata

Spec version: 0.2.1
Runtime: Ollama 0.35.0
Model format: GGUF
Hardware profile: HIGH-END
Result hash: f21d660cafb6381d5fe2af71fba723b6c4988a9640582060b95053f2905099be

Interpretation

Hardware fit: 66/100. Overall suitability: EXCELLENT (Global 84/100). Category profile: Reasoning: Strong, Coding: Strong, Instruction Following: Adequate, Structured Output: Strong, Math: Strong, Multilingual: Strong.

Bench Environment

Thermal: nominal CPU load: avg 13% (peak 25%)

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