GPU comparison · 1080p benchmark
RX 9070 XT 16GB recorded 469 FPS against 184 FPS for Arc A770 16GB. These are continuous 1080p benchmark averages, not predicted FPS in any particular game.
Arc A770 16GB
184Benchmark FPS at 1080p- Our rating
- 60.2 / 100
- Graphics memory
- 16GB
- Released
- October 2022
- GPUsed cards tested
- 6
RX 9070 XT 16GB
469Benchmark FPS at 1080p- Our rating
- 83.5 / 100
- Graphics memory
- 16GB
- Released
- March 2025
- GPUsed cards tested
- 15
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What does this comparison mean?
Both GPUs have 16GB, yet the RX 9070 XT produces a much higher result than the Arc A770 in this benchmark. The shared memory figure says little about the difference in GPU performance.
Both variants have 16GB of graphics memory. Memory capacity, board dimensions, power connectors and the price of a particular used card are separate from this benchmark. Compare the exact item before deciding whether to upgrade.
The two GPUs in context
Arc A770 16GB
This Arc A770 uses the 16GB configuration. Intel documented October 2022 availability for the 16GB Limited Edition, separately from partner 8GB cards.
RX 9070 XT 16GB
The RX 9070 XT combines RDNA 4 and 16GB of GDDR6. AMD documented partner availability from March 2025.
Release and feature sources: Arc A770 16GB source · RX 9070 XT 16GB source.
How the figures are compared
Both FPS figures come from the owner-supplied GPUsed benchmark dataset. GPUsed reports a continuous FurMark run at 1080p for its physical-card checks. The percentage compares the higher model average with the lower one using the original FPS values. Our rating uses a compressed scale, with the fastest GPU at 100; it is separate from the percentage difference. A benchmark result does not predict gaming FPS.
GPUsed reports its physical-card checks typically last 30 to 60 minutes while temperature and stability are checked. The owner supplied the model-level FPS workbook on 2 October 2026; this benchmark dataset was last reconciled 3 October 2026. Historical cards tested are separate from the number of FPS runs behind a model average. Full benchmark method.