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hf.co/empero-ai/Qwen3.8-2B-Distill-GGUF:BF16

OLLAMA GGUF

qwen35 · 1.94B · BF16

Good

Aug 23, 2026 · Apple M1 Pro

smollm2-1.7b-instruct

LM-STUDIO MLX

llama · 1.7B · bf16

Good

Mar 4, 2026 · Apple M4

Global Score
66 vs 65
Hardware Fit
100 vs 99
Quality Score
52 vs 51

Hardware

hf.co/empero-ai/Qw… smollm2-1.7b-instr…
MachineMacBook ProMacBook Air
CPUApple M1 ProApple M4
Cores1010
RAM16 GB32 GB
GPUApple M1 ProApple M4
OSmacOS 26.6.2macOS 26.3
Archarm64arm64
Power Modebalancedbalanced

Performance

hf.co/empero-ai/Qw… smollm2-1.7b-instr…
Tokens/sec40.428.5
First chunk93 ms393 ms
TTFT93 ms393 ms
Load time2.7 sN/A
Memory usage4.7 GB3.2 GB
Memory %30%10%

HW Fit Score Breakdown

hf.co/empero-ai/Qwen3.8…

Speed
50/50
TTFT
20/20
Memory
30/30

smollm2-1.7b-instruct

Speed
50/50
TTFT
20/20
Memory
29/30

Quality

hf.co/empero-ai/Qwen3.8…

Reasoning
15/20
Coding
9/20
Instruction
8/20
Structured
1/15
Math
15/15
Multilingual
4/10
Reasoning: Adequate Coding: Weak Instruction Following: Weak Structured Output: Poor Math: Strong Multilingual: Weak

smollm2-1.7b-instruct

Reasoning
10/20
Coding
10/20
Instruction
13/20
Structured
11/15
Math
2/15
Multilingual
5/10
Reasoning: Weak Coding: Adequate Instruction Following: Adequate Structured Output: Adequate Math: Poor Multilingual: Adequate

Run yours and compare

$ npm install -g metrillm@latest
$ metrillm

Requires Node 20+ and Ollama or LM Studio running

Or run without installing: npx metrillm@latest