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yi-coder-1.5b-chat

LM-STUDIO GGUF

llama · 1.5B · Q4_K_M

Marginal

Mar 7, 2026 · Intel Core™ i5-5300U

qwen2.5-7b-instruct

LM-STUDIO MLX

qwen2 · 7B · 4bit

Excellent

Mar 3, 2026 · Apple M4

Global Score
45 vs 82
Hardware Fit
67 vs 92
Quality Score
35 vs 78

Hardware

yi-coder-1.5b-chat qwen2.5-7b-instruct
MachineLENOVO 20BUS00700MacBook Air
CPUIntel Core™ i5-5300UApple M4
Cores410
RAM16 GB32 GB
GPUIntel(R) HD Graphics 5500Apple M4
OSMicrosoft Windows 10 Professionnel 10.0.19045macOS 26.3
Archx64arm64
Power Modebalancedbalanced

Performance

yi-coder-1.5b-chat qwen2.5-7b-instruct
Tokens/sec7.722.0
First chunk2668 ms477 ms
TTFT2.7 s477 ms
Load timeN/AN/A
Memory usage0.9 GB4.0 GB
Memory %6%13%

HW Fit Score Breakdown

yi-coder-1.5b-chat

Speed
26/50
TTFT
17/20
Memory
24/30

qwen2.5-7b-instruct

Speed
43/50
TTFT
20/20
Memory
29/30

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

qwen2.5-7b-instruct

Reasoning
14/20
Coding
17/20
Instruction
15/20
Structured
15/15
Math
8/15
Multilingual
9/10
Reasoning: Adequate Coding: Strong Instruction Following: Strong Structured Output: Strong Math: Adequate Multilingual: Strong
View yi-coder-1.5b-chat details | View qwen2.5-7b-instruct 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