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qwen3.8:27b-bf16

OLLAMA GGUF

qwen35 · 27.3B · BF16

Excellent

Aug 22, 2026 · AMD EPYC 7713 64-Core Processor

smollm2-1.7b-instruct

LM-STUDIO MLX

llama · 1.7B · bf16

Good

Mar 4, 2026 · Apple M4

Global Score
85 vs 65
Hardware Fit
77 vs 99
Quality Score
88 vs 51

Hardware

qwen3.8:27b-bf16 smollm2-1.7b-instr…
MachineDell Inc. PowerEdge XE8545MacBook Air
CPUAMD EPYC 7713 64-Core ProcessorApple M4
Cores12810
RAM1007 GB32 GB
GPUGA100 [A100 SXM4 80GB], GA100 [A100 SXM4 80GB], Integrated Matrox G200eW3 Graphics Controller, GA100 [A100 SXM4 80GB], GA100 [A100 SXM4 80GB]Apple M4
OSRocky Linux 8.10macOS 26.3
Archx64arm64
Power Modeunknownbalanced

Performance

qwen3.8:27b-bf16 smollm2-1.7b-instr…
Tokens/sec27.228.5
First chunk237 ms393 ms
TTFT237 ms393 ms
Load time43.8 sN/A
Memory usage68.8 GB3.2 GB
Memory %7%10%

HW Fit Score Breakdown

qwen3.8:27b-bf16

Speed
27/50
TTFT
20/20
Memory
30/30

smollm2-1.7b-instruct

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

Quality

qwen3.8:27b-bf16

Reasoning
18/20
Coding
18/20
Instruction
16/20
Structured
15/15
Math
11/15
Multilingual
10/10
Reasoning: Strong Coding: Strong Instruction Following: Strong Structured Output: Strong Math: Adequate Multilingual: Strong

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
View qwen3.8:27b-bf16 details | View smollm2-1.7b-instr… details

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