qwen/qwen3.6-35b-a3b

qwen35moe · 35B · Q4_K_M

ECO MODE

ASUS (AMD Ryzen 7 7800X3D 8-Core Processor)

31 GB · cachyos rolling

Tested on July 4, 2026

Top 16% Compare

Global Score

84 /100

Excellent

Hardware Fit

79/100

Quality

86/100

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Hardware

Machine: ASUS
CPU: AMD Ryzen 7 7800X3D 8-Core Processor
Cores: 16 threads (8 cores)
Frequency: 2.74 GHz
RAM: 31 GB
GPU: NVIDIA GeForce RTX 4090, Raphael
OS: cachyos rolling
Arch: x64
Power Mode: low-power

Performance

Tokens/sec Tokens generated per second — higher is better: 115.8
Standard deviation Variation of speed across benchmark runs — lower means more consistent: ±1.1
First chunk latency Delay before the first streamed chunk arrives from runtime: 9 ms
Time to first token How fast the model starts responding — lower is better: 310 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: 25.3 GB (83%)
Total tokens Total number of tokens generated across all benchmark prompts: 1229

Score breakdown

Speed

50/50

Time to first token

20/20

Memory

9/30

Quality

Reasoning

16/20

Coding

18/20

Instruction following

15/20

Structured output

15/15

Math

12/15

Multilingual

10/10

Category levels

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

Metadata

Spec version: 0.2.1
Runtime: LM Studio
Model format: GGUF
Hardware profile: BALANCED
Result hash: 91f8c2fa168ca24dc9a1343411d9d49140a0aba376e94fc6a6624b197ebc1993

Interpretation

Hardware fit: 79/100. Overall suitability: EXCELLENT (Global 84/100). Category profile: Reasoning: Strong, Coding: Strong, Instruction Following: Strong, Structured Output: Strong, Math: Strong, Multilingual: Strong.

Warnings

Model memory footprint is estimated via LM Studio CLI rather than measured from a fresh load.
System was in low-power mode during this benchmark.

Bench Environment

Thermal: nominal Swap delta: +0.1 GB CPU load: avg 30% (peak 39%)

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$ npm install -g metrillm@latest

$ metrillm

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Or run without installing: npx metrillm@latest