System identityMemory architecture Accepted benchmark runs
Environment
Telemetry availability Provenance & limitations
AMD Radeon RX 7800 XT (16 GB dedicated VRAM)
AMD Radeon RX 7800 XT — unknown
Dedicated VRAM: 16 GB, dedicated. llama.cpp's own Vulkan device query reported 15405 MiB free on this device at model-load time, on an adapter whose Vulkan properties report `uma: 0` -- a dedicated pool, not memory shared with system RAM.
Source: llama.cpp's own device-selection line in both accepted runs' raw stderr (`llama_prepare_model_devices: using device Vulkan0 (AMD Radeon RX 7800 XT) ... - 15405 MiB free`), published verbatim at /data. NOT from Windows WMI's Win32_VideoController.AdapterRAM, a 32-bit field that truncates for cards >=4GB -- which is why the structured result.json's hardware.accelerators[0].dedicatedVramBytes is honestly "UNKNOWN". Note this is free memory measured with a desktop session already resident, so it is a lower bound on the pool, not the pool's total; the accepted RX 9070 reported 15416 MiB free by the identical mechanism and the same llama.cpp build.
Reported device name: This card reports its real model name ("AMD Radeon RX 7800 XT") over Vulkan, unlike the accepted RX 9070, whose driver reports the generic "AMD Radeon(TM) Graphics".
Source: `ggml_vulkan: 0 = AMD Radeon RX 7800 XT (AMD proprietary driver)` in both accepted runs' raw stderr. Recorded because it shows the generic-string problem is a property of particular vendor drivers, not of a vendor or a generation -- which is why Labs' public identity comes from this registry rather than from rewriting driver strings.
| Model | Context | Prompt processing | Generation | Acceleration evidence | Status |
|---|---|---|---|---|---|
| llama 8B Q4_0 | 8192 | 763.53 tok/s | 74.81 tok/s | 33/33 layers offloaded to GPU | PASS |
| qwen3 14B Q4_K - Medium | 8192 | 417.30 tok/s | 43.51 tok/s | 41/41 layers offloaded to GPU | PASS |
Backend
Vulkan — target device: Vulkan
Methodology version
standard-ai-v0.1
| Host OS | Microsoft Windows 11 Pro 10.0.26200 |
| CPU | AMD Ryzen 7 3700X 8-Core Processor |
| Installed memory | 32 GB |
| llama.cpp / llama-bench | 0.5.0-dev (build 11146, commit 7fe450e19) |
| Backends compiled | CPU,RPC,Vulkan |
PowerUNAVAILABLE
TemperatureUNAVAILABLE
Accelerator memoryUNAVAILABLE
Missing telemetry is shown as UNAVAILABLE, never estimated or substituted. Throughput measurements are unaffected by missing telemetry.
- Model identity (SHA-256, declared type/parameter count) comes from the model file's own bytes and llama-bench's own GGUF parsing — see /data for the exact hashes.
- Acceleration evidence above is parsed directly from llama.cpp's own log output for each run, not assumed from the hardware being present.
- These measurements describe throughput on the specific standard-ai-v0.1 workload only — see Methodology for what this does and does not establish.