hf.co/empero-ai/Qwen3.8-2B-Distill-GGUF:BF16
OLLAMA GGUFqwen35 · 1.94B · BF16
Aug 25, 2026 · Apple M1 Pro
glm-4.7-flash:bf16
OLLAMA GGUFdeepseek2 · 29.9B · F16
Jun 26, 2026 · Cortex-X925
Global Score
76 vs 76
Hardware Fit
100 vs 73
Quality Score
66 vs 77
Hardware
hf.co/empero-ai/Qw… glm-4.7-flash:bf16
MachineMacBook ProNVIDIA NVIDIA_DGX_Spark
CPUApple M1 ProCortex-X925
Cores1020
RAM16 GB122 GB
GPUApple M1 ProDevice 2e12
OSmacOS 26.6.2Ubuntu 24.04.4 LTS
Archarm64arm64
Power Modebalancedperformance
Performance
hf.co/empero-ai/Qw… glm-4.7-flash:bf16
Tokens/sec40.325.8
First chunk101 ms605 ms
TTFT101 ms605 ms
Load time2.7 s44.2 s
Memory usage4.5 GB57.0 GB
Memory %28%47%
HW Fit Score Breakdown
hf.co/empero-ai/Qwen3.8…
Speed
50/50
TTFT
20/20
Memory
30/30
glm-4.7-flash:bf16
Speed
27/50
TTFT
20/20
Memory
26/30
Quality
hf.co/empero-ai/Qwen3.8…
Reasoning
11/20
Coding
10/20
Instruction
12/20
Structured
15/15
Math
8/15
Multilingual
10/10
Reasoning: Adequate Coding: Weak Instruction Following: Adequate Structured Output: Strong Math: Adequate Multilingual: Strong
glm-4.7-flash:bf16
Reasoning
13/20
Coding
17/20
Instruction
12/20
Structured
15/15
Math
10/15
Multilingual
10/10
Reasoning: Adequate Coding: Strong Instruction Following: Adequate Structured Output: Strong Math: Adequate Multilingual: Strong
Run yours and compare
$
npm install -g metrillm@latest$
metrillmRequires Node 20+ and Ollama or LM Studio running
Or run without installing: npx metrillm@latest