liquid/lfm2-1.2b

lfm2 · 1.2B · Q8_0

ASUSTeK COMPUTER INC. ROG Strix G513IM_G513IM (AMD Ryzen 7 4800H)

15 GB · Microsoft Windows 11 Pro 10.0.26200

Tested on October 1, 2026

Top 66% Compare

Global Score

69 /100

Good

Hardware Fit

100/100

Quality

56/100

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Hardware

Machine: ASUSTeK COMPUTER INC. ROG Strix G513IM_G513IM
CPU: AMD Ryzen 7 4800H
Cores: 16 total (16 perf)
Frequency: 2.9 GHz
RAM: 15 GB DDR4
GPU: AMD Radeon(TM) Graphics, NVIDIA GeForce RTX 3060 Laptop GPU
OS: Microsoft Windows 11 Pro 10.0.26200
Arch: x64
Power Mode: balanced

Performance

Tokens/sec Tokens generated per second — higher is better: 169.5
Standard deviation Variation of speed across benchmark runs — lower means more consistent: ±2.9
First chunk latency Delay before the first streamed chunk arrives from runtime: 27 ms
Time to first token How fast the model starts responding — lower is better: 77 ms
Load time Time to load the model into memory before inference: N/A
Memory usage RAM consumed during inference — percentage of total system memory: 3.4 GB (22%)
Total tokens Total number of tokens generated across all benchmark prompts: 1102

Score breakdown

Speed

50/50

Time to first token

20/20

Memory

30/30

Quality

Reasoning

9/20

Coding

7/20

Instruction following

14/20

Structured output

12/15

Math

5/15

Multilingual

9/10

Category levels

Reasoning: Weak Coding: Weak Instruction Following: Adequate Structured Output: Strong Math: Weak Multilingual: Strong

Metadata

Spec version: 0.2.1
Runtime: LM Studio
Model format: GGUF
Hardware profile: BALANCED
Result hash: a2e91e8825ca4394b98e7630c75fefde0b2d207fc10eb6f62d549d30f98a89b6

Interpretation

Hardware fit: 100/100. Overall suitability: GOOD (Global 69/100). Category profile: Reasoning: Weak, Coding: Weak, Instruction Following: Adequate, Structured Output: Strong, Math: Weak, Multilingual: Strong.

Warnings

Model memory footprint is estimated via LM Studio CLI rather than measured from a fresh load.

Bench Environment

Power: AC CPU load: avg 41% (peak 56%)

Run yours now

$ npm install -g metrillm@latest

$ metrillm

Requires Node 20+ and Ollama or LM Studio running

Or run without installing: npx metrillm@latest