yi-coder-1.5b-chat
LM-STUDIO GGUFllama · 1.5B · Q4_K_M
Mar 7, 2026 · Intel Core™ i5-5300U
qwen/qwen3.8-27b
LM-STUDIO MLXqwen3_5 · 27B · 4bit
Aug 19, 2026 · Apple M4 Max
Global Score
45 vs 84
Hardware Fit
67 vs 69
Quality Score
35 vs 90
Hardware
yi-coder-1.5b-chat qwen/qwen3.8-27b
MachineLENOVO 20BUS00700MacBook Pro
CPUIntel Core™ i5-5300UApple M4 Max
Cores416
RAM16 GB128 GB
GPUIntel(R) HD Graphics 5500Apple M4 Max
OSMicrosoft Windows 10 Professionnel 10.0.19045macOS 26.5.2
Archx64arm64
Power Modebalancedbalanced
Performance
yi-coder-1.5b-chat qwen/qwen3.8-27b
Tokens/sec7.728.9
First chunk2668 ms33 ms
TTFT2.7 s4.4 s
Load timeN/A7.9 s
Memory usage0.9 GB0.0 GB
Memory %6%0%
HW Fit Score Breakdown
yi-coder-1.5b-chat
Speed
26/50
TTFT
17/20
Memory
24/30
qwen/qwen3.8-27b
Speed
33/50
TTFT
6/20
Memory
30/30
Quality
yi-coder-1.5b-chat
Reasoning
4/20
Coding
12/20
Instruction
6/20
Structured
6/15
Math
1/15
Multilingual
6/10
Reasoning: Poor Coding: Adequate Instruction Following: Weak Structured Output: Weak Math: Poor Multilingual: Adequate
qwen/qwen3.8-27b
Reasoning
19/20
Coding
15/20
Instruction
16/20
Structured
15/15
Math
15/15
Multilingual
10/10
Reasoning: Strong Coding: Adequate Instruction Following: Strong Structured Output: Strong Math: Strong 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