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AMD Radeon 780M Graphics (AMD Ryzen 7 8700G w/ Radeon 780M Graphics)

AMD · GPU · LynxBenchAI 26Q3 Index, recorded 2026-11-02

On the LynxBenchAI 26Q3 Index, the AMD Radeon 780M Graphics (AMD Ryzen 7 8700G w/ Radeon 780M Graphics) ranks 49 of 49 devices overall with a GT of 0.00 (Training 0.00, rank 49; Inference 0.00, rank 49; Compute 0.00, rank 49); overall it scores n/a the NVIDIA H100 80GB HBM3 and n/a the NVIDIA GeForce RTX 4090.

0.00
GT · rank #49 of 49

Where It Sits on the LynxBenchAI 26Q3 Index

Rank among all 49 devices; further right is higher.

  • Overall (GT)rank 49 of 49
  • Trainingrank 49 of 49
  • Inferencerank 49 of 49
  • Computerank 49 of 49
The AMD Radeon 780M Graphics (AMD Ryzen 7 8700G w/ Radeon 780M Graphics)'s score divided by the reference device's score
Compared withOverallTrainingInferenceCompute
NVIDIA H100 80GB HBM30.00xn/an/an/a
NVIDIA GeForce RTX 40900.00xn/an/an/a
Nearest devices on each score, with this device's score divided by theirs
ScoreNext aboveRatioNext belowRatio
Training Samsung UNIVERSAL8890 board based on EXYNOS8890 (Cortex-A53) last
Inference Samsung UNIVERSAL8890 board based on EXYNOS8890 (Cortex-A53) last
Compute Samsung UNIVERSAL8890 board based on EXYNOS8890 (Cortex-A53) last
  • Did not execute: BF16 compute, BF16 training, FP16 compute, FP16 inference, FP32 compute, FP32 training, FP64 compute, FP8 inference, INT8 inference (scored zero).

training

0.00 category score
Model Precision Sustained
MobileNetV3 FP32 0.00
MobileNetV3 BF16 0.00
Flan-T5 Small FP32 0.00
Flan-T5 Small BF16 0.00
DistilGPT2 FP32 0.00
DistilGPT2 BF16 0.00
DistilBERT FP32 0.00
DistilBERT BF16 0.00
GraphGPS (Peptides) FP32 0.00
GraphGPS (Peptides) BF16 0.00

inference

0.00 category score
Model Precision Sustained
MobileNetV3 FP16 0.00
MobileNetV3 INT8 0.00
Flan-T5 Small FP16 0.00
Flan-T5 Small INT8 0.00
Flan-T5 Small FP8 0.00
DistilGPT2 FP16 0.00
DistilGPT2 INT8 0.00
DistilGPT2 FP8 0.00
DistilBERT FP16 0.00
DistilBERT INT8 0.00
DistilBERT FP8 0.00
GraphGPS (Peptides) FP16 0.00
GraphGPS (Peptides) INT8 0.00
GraphGPS (Peptides) FP8 0.00

compute

0.00 category score
Model Precision Sustained
Dense MatMul FP32 0.00
Dense MatMul FP16 0.00
Dense MatMul BF16 0.00
Dense MatMul FP64 0.00
Sparse MatMul FP32 0.00
Sparse MatMul FP64 0.00

LynxBenchAI 26Q3 Index · GT = LynxBenchAI Global Score. Every precision result is sustained throughput under a declared, bounded optimisation budget — no collapsed single number below the category level.

Compare With

Each figure is the first device's overall score divided by the second's.

All comparisons →

How to Read These Results

A LynxBenchAI score is sustained throughput on a fixed catalogue of PyTorch models, measured after a warm-up at a batch size raised until throughput stops improving, so it is what the machine holds under load, not its best instant. Training, Inference and Compute are three separate scores; GT combines them (Training and Inference weigh 0.4 each, Compute 0.2).

Every run uses the stock, publicly released PyTorch stack, so a result is broadly indicative of the out-of-the-box PyTorch experience on that hardware, and so of custom PyTorch models too. It does not run your own model, and it is not a vendor-tuned peak like an MLPerf submission.

Scores compare only within one Index: the 26Q3 Index fixes the models, precisions, correctness thresholds and scoring, and a later Index may change them. Each test is one timed window, the scores have no 0-100 scale, and a precision a device cannot run scores zero rather than being skipped.

LynxBenchAI is built by TechnoLynx, which the European Commission engaged as an independent expert advisor on AI performance and benchmarking for AI Gigafactories under the EuroHPC Joint Undertaking (case study).

Questions

How fast is the AMD Radeon 780M Graphics (AMD Ryzen 7 8700G w/ Radeon 780M Graphics) for AI workloads?
On the LynxBenchAI 26Q3 Index, the AMD Radeon 780M Graphics (AMD Ryzen 7 8700G w/ Radeon 780M Graphics) ranks 49 of 49 devices overall with a GT of 0.00 (Training 0.00, rank 49; Inference 0.00, rank 49; Compute 0.00, rank 49); overall it scores n/a the NVIDIA H100 80GB HBM3 and n/a the NVIDIA GeForce RTX 4090.
How does the AMD Radeon 780M Graphics (AMD Ryzen 7 8700G w/ Radeon 780M Graphics) compare with the NVIDIA H100 80GB HBM3?
On the LynxBenchAI 26Q3 Index, the AMD Radeon 780M Graphics (AMD Ryzen 7 8700G w/ Radeon 780M Graphics) scores n/a the NVIDIA H100 80GB HBM3 overall: Training n/a, Inference n/a, Compute n/a.
How does the AMD Radeon 780M Graphics (AMD Ryzen 7 8700G w/ Radeon 780M Graphics) compare with the NVIDIA GeForce RTX 4090?
On the LynxBenchAI 26Q3 Index, the AMD Radeon 780M Graphics (AMD Ryzen 7 8700G w/ Radeon 780M Graphics) scores n/a the NVIDIA GeForce RTX 4090 overall: Training n/a, Inference n/a, Compute n/a.
Which precisions did the AMD Radeon 780M Graphics (AMD Ryzen 7 8700G w/ Radeon 780M Graphics) not run?
On the LynxBenchAI 26Q3 Index, the AMD Radeon 780M Graphics (AMD Ryzen 7 8700G w/ Radeon 780M Graphics) did not execute BF16 compute, BF16 training, FP16 compute, FP16 inference, FP32 compute, FP32 training, FP64 compute, FP8 inference and INT8 inference; those results score zero rather than being left out.
What does this result tell me about my own PyTorch model?
Every run uses the stock, publicly released PyTorch stack, so a result is broadly indicative of the out-of-the-box PyTorch experience on that hardware, and so of custom PyTorch models too. It does not run your own model, and it is not a vendor-tuned peak like an MLPerf submission.

Measure your own AMD Radeon 780M Graphics (AMD Ryzen 7 8700G w/ Radeon 780M Graphics): pip install lynxbench-ai · Install guide →

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