AMD-Pro-BenchCommunity

13,812 benchmarks in 32 GPU combinations documented

Qwen2.5-1.5B-Instruct on AMD GPUs

12 results · 2 sources · 18 measurements

Grouped by reported model identity. Exact weights, quantizations and software can differ. How results are reviewed

Documented results

12 selected tests
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Generic LLM
Qwen2.5-1.5B-InstructQ4_K_MWeights ↗Token speed——
201.56 tok/sGeneration · per request
1 × W7900Single GPU · 48 GB VRAM/GPU
Configuration
Memory
48 GB VRAM/GPU
OS
Ubuntu 24.04.4 LTS
Engine
llama.cpp / llama-cpp-python
Backend
HIP / ROCm 7.2.1
Harness
VTE Python CLI benchmark
Prompt / output
? / 151 tokens
Context
4096
Concurrency
1
Date
2026-07-19
Full record →
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llama-bench
Qwen2.5-1.5B-InstructQ4_K_MWeights ↗Token speed—
4,531.77 tok/sPrefill · mean · per request
—1 × RX 9060 XTSingle GPU · 16 GB VRAM/GPU
Configuration
Memory
16 GB VRAM/GPU
OS
Ubuntu 26.04
Engine
llama.cpp
Backend
ROCm / HIP
Harness
llama-bench
Prompt / output
512 / 0 tokens
Context
Not reported
Concurrency
Not reported
Date
2026-05-20
Full record →
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Generic LLM
Qwen2.5-1.5B-InstructQ4_K_MWeights ↗Token speed——
200.76 tok/sGeneration · per request
1 × W7900Single GPU · 48 GB VRAM/GPU
Configuration
Memory
48 GB VRAM/GPU
OS
Ubuntu 24.04.4 LTS
Engine
llama.cpp / llama-cpp-python
Backend
HIP / ROCm 7.2.1
Harness
VTE Python CLI benchmark
Prompt / output
? / 151 tokens
Context
4096
Concurrency
1
Date
2026-07-19
Full record →
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llama-bench
Qwen2.5-1.5B-InstructQ4_K_MWeights ↗Token speed——
107.85 tok/sGeneration · mean · per request
1 × RX 9060 XTSingle GPU · 16 GB VRAM/GPU
Configuration
Memory
16 GB VRAM/GPU
OS
Ubuntu 26.04
Engine
llama.cpp
Backend
ROCm / HIP
Harness
llama-bench
Prompt / output
0 / 128 tokens
Context
Not reported
Concurrency
Not reported
Date
2026-05-20
Full record →
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Generic LLM
Qwen2.5-1.5B-InstructQ4_K_MWeights ↗Token speed——
202.04 tok/sGeneration · per request
1 × W7900Single GPU · 48 GB VRAM/GPU
Configuration
Memory
48 GB VRAM/GPU
OS
Ubuntu 24.04.4 LTS
Engine
llama.cpp / llama-cpp-python
Backend
HIP / ROCm 7.2.1
Harness
VTE Python CLI benchmark
Prompt / output
? / 151 tokens
Context
4096
Concurrency
1
Date
2026-07-19
Full record →
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llama-bench
Qwen2.5-1.5B-InstructQ4_K_MWeights ↗Token speed—
4,790.91 tok/sPrefill · mean · per request
—1 × RX 9060 XTSingle GPU · 16 GB VRAM/GPU
Configuration
Memory
16 GB VRAM/GPU
OS
Ubuntu 26.04
Engine
llama.cpp
Backend
ROCm / HIP
Harness
llama-bench
Prompt / output
512 / 0 tokens
Context
Not reported
Concurrency
Not reported
Date
2026-05-20
Full record →
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Generic LLM
Qwen2.5-1.5B-InstructQ4_K_MWeights ↗Token speed——
138.81 tok/sGeneration · per request
1 × W7900Single GPU · 48 GB VRAM/GPU
Configuration
Memory
48 GB VRAM/GPU
OS
Ubuntu 24.04.4 LTS
Engine
VTE
Backend
HIP / ROCm 7.2.1
Harness
VTE Python CLI benchmark
Prompt / output
? / 60 tokens
Context
4096
Concurrency
1
Date
2026-07-19
Full record →
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llama-bench
Qwen2.5-1.5B-InstructQ4_K_MWeights ↗Token speed——
111.24 tok/sGeneration · mean · per request
1 × RX 9060 XTSingle GPU · 16 GB VRAM/GPU
Configuration
Memory
16 GB VRAM/GPU
OS
Ubuntu 26.04
Engine
llama.cpp
Backend
ROCm / HIP
Harness
llama-bench
Prompt / output
0 / 128 tokens
Context
Not reported
Concurrency
Not reported
Date
2026-05-20
Full record →
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Generic LLM
Qwen2.5-1.5B-InstructQ4_K_MWeights ↗Token speed——
140.77 tok/sGeneration · per request
1 × W7900Single GPU · 48 GB VRAM/GPU
Configuration
Memory
48 GB VRAM/GPU
OS
Ubuntu 24.04.4 LTS
Engine
VTE
Backend
HIP / ROCm 7.2.1
Harness
VTE Python CLI benchmark
Prompt / output
? / 150 tokens
Context
4096
Concurrency
1
Date
2026-07-19
Full record →
View
Report
Generic LLM
Qwen2.5-1.5B-InstructQ4_K_MWeights ↗Token speed——
140.91 tok/sGeneration · per request
1 × W7900Single GPU · 48 GB VRAM/GPU
Configuration
Memory
48 GB VRAM/GPU
OS
Ubuntu 24.04.4 LTS
Engine
VTE
Backend
HIP / ROCm 7.2.1
Harness
VTE Python CLI benchmark
Prompt / output
? / 150 tokens
Context
4096
Concurrency
1
Date
2026-07-19
Full record →
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Generic LLM
Qwen2.5-1.5B-InstructQ4_K_MWeights ↗Latency1 concurrent request
531.32 msModel load time · Whole system
——1 × W7900Single GPU · 48 GB VRAM/GPU
Configuration
Memory
48 GB VRAM/GPU
OS
Ubuntu 24.04.4 LTS
Engine
llama.cpp / llama-cpp-python
Backend
HIP / ROCm 7.2.1
Harness
VTE Python CLI benchmark
Prompt / output
? / ? tokens
Context
4096
Concurrency
1
Date
2026-07-19
Full record →
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Report
Generic LLM
Qwen2.5-1.5B-InstructQ4_K_MWeights ↗Latency1 concurrent request
2,748.82 msModel load time · Whole system
——1 × W7900Single GPU · 48 GB VRAM/GPU
Configuration
Memory
48 GB VRAM/GPU
OS
Ubuntu 24.04.4 LTS
Engine
VTE
Backend
HIP / ROCm 7.2.1
Harness
VTE Python CLI benchmark
Prompt / output
? / ? tokens
Context
4096
Concurrency
1
Date
2026-07-19
Full record →
Quantizations and software

Quantizations: Q4_K_M
Engines: llama.cpp, llama.cpp / llama-cpp-python, VTE

Explore all 12 results →

This is a selection across sources, not a ranking or a matched experiment. Reading benchmark reports

GPU benchmark pages: W7900 · RX 9060 XT