qwen3-coder-next:latest

qwen3next · 79.7B · Q4_K_M

AZW GTR Pro (AMD RYZEN AI MAX+ 395)

125 GB · Ubuntu 24.04.4 LTS

Tested on March 5, 2026

Top 13% Compare

Global Score

82 /100

Excellent

Hardware Fit

71/100

Quality

87/100

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Ollama

ollama pull qwen3-coder-next:latest

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ollama.com/library/qwen3-coder-next

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GGUF versions & quantizations

Hardware

Machine: AZW GTR Pro
CPU: AMD RYZEN AI MAX+ 395
Cores: 32 threads (16 cores)
Frequency: 3 GHz
RAM: 125 GB
GPU: AMD Radeon 8060S
OS: Ubuntu 24.04.4 LTS
Arch: x64
Power Mode: performance

Performance

Tokens/sec Tokens generated per second — higher is better: 34.5
Standard deviation Variation of speed across benchmark runs — lower means more consistent: ±0.1
First chunk latency Delay before the first streamed chunk arrives from runtime: 262 ms
Time to first token How fast the model starts responding — lower is better: 262 ms
Load time Time to load the model into memory before inference: 16.4 s
Memory usage RAM consumed during inference — percentage of total system memory: 56.8 GB (46%)
Total tokens Total number of tokens generated across all benchmark prompts: 1046

Score breakdown

Speed

34/50

Time to first token

20/20

Memory

17/30

Quality

Reasoning

18/20

Coding

18/20

Instruction following

13/20

Structured output

15/15

Math

13/15

Multilingual

10/10

Category levels

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

Metadata

Spec version: 0.2.1
Runtime: Ollama 0.17.4
Model format: GGUF
Hardware profile: HIGH-END
Result hash: dddf6fb0246f981829b596f3382b3e47a7add9e1554d68e7fa04211de1894748

Interpretation

Hardware fit: 71/100. Overall suitability: EXCELLENT (Global 82/100). Category profile: Reasoning: Strong, Coding: Strong, Instruction Following: Adequate, Structured Output: Strong, Math: Strong, Multilingual: Strong.

Bench Environment

Thermal: nominal CPU load: avg 2% (peak 3%)

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