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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

qwen/qwen3-8b

LM-STUDIO MLX

qwen3 · 8B · 4bit

Excellent

Mar 5, 2026 · Apple M4 Pro

Global Score
45 vs 89
Hardware Fit
67 vs 95
Quality Score
35 vs 87

Hardware

yi-coder-1.5b-chat qwen/qwen3-8b
MachineLENOVO 20BUS00700Mac mini
CPUIntel Core™ i5-5300UApple M4 Pro
Cores414
RAM16 GB64 GB
GPUIntel(R) HD Graphics 5500Apple M4 Pro
OSMicrosoft Windows 10 Professionnel 10.0.19045macOS 15.7.4
Archx64arm64
Power Modebalancedbalanced

Performance

yi-coder-1.5b-chat qwen/qwen3-8b
Tokens/sec7.733.4
First chunk2668 ms257 ms
TTFT2.7 s257 ms
Load timeN/AN/A
Memory usage0.9 GB4.3 GB
Memory %6%7%

HW Fit Score Breakdown

yi-coder-1.5b-chat

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

qwen/qwen3-8b

Speed
45/50
TTFT
20/20
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/qwen3-8b

Reasoning
19/20
Coding
14/20
Instruction
16/20
Structured
15/15
Math
13/15
Multilingual
10/10
Reasoning: Strong Coding: Adequate Instruction Following: Strong Structured Output: Strong Math: Strong Multilingual: Strong
View yi-coder-1.5b-chat details | View qwen/qwen3-8b 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