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The RTX 2070 has 8 GB; its working baseline depends on display use and other applications rather than nominal capacity alone.
The original 8 GB RTX 2070
The RTX 2070 is a Turing model with 8 GB GDDR6. NVIDIA lists 185 W for its comparison design; an actual AIB board needs its own limits verified. This is not the RTX 2070 SUPER. Capacity is per GPU without automatically adding several cards. For an existing workstation, preserve model name, board identity and pre-task process list. The system may detect the card while a display or applications already occupy memory. Nominal capacity and the available remainder are separate worker profile fields. Keep both rather than treating device availability as an empty resource.
| Official variant | Memory per GPU | Memory type | Board power | Evidence |
|---|---|---|---|---|
| NVIDIA GeForce RTX 2070 — 8 GB NVIDIA comparison reference/FE design | 8 GB | GDDR6 | 185 W | Specification |
Test inference against a known baseline
Match vLLM requirements to engine release, model revision, dtype and selected kernels. Turing meets the minimum hardware floor rather than certifying every modern backend. Preserve a bounded RTX 2070 request with fixed context and output. Measure baseline, post-loading memory and generation memory separately. If a configuration fails only with an active graphics application, inspect the changed remainder before automatically choosing another model. With llama.cpp CUDA, record offload and CPU involvement independently. A hybrid success does not establish full residency within 8 GB. The observed path belongs in the acceptance result.
Separate interactive and server scenes
Check Cycles CUDA or OptiX against Blender documentation, driver and the actual selected GPU. Run a packaged project with saved assets and quality settings. A background viewport and batch rendering can create different device conditions, so do not combine them in an unexplained measurement. Supporting backends use RTX hardware tracing without certifying every renderer. Record host RAM involvement separately. Image and logs confirm the result together. A small passing project does not establish that another scene’s materials, textures and geometry fit or execute in the same mode. Preserve the exact project package.
Make worker conditions reproducible
The manifest records driver, software image, display state and permitted background processes. Its policy should define whether new jobs can coexist with interactive applications. Otherwise the queue waits for confirmed handover. An HTTP client closing does not guarantee release of engine memory. Moving the card into a server also requires AIB dimensions, supply and airflow checks. The 185 W specification does not measure complete job energy; account for RAM and CPU separately. Avoid forced clocks or disabled protections to conceal instability. Preserve the initial state and a minimal reproducible case instead of tuning several factors simultaneously.
Compare environments through an artifact
The package contains matching LLM and scene manifests, two documented background states and results with status, VRAM/RAM and processes. If only available memory changes, adjust admission policy. If failure remains on a clean worker, inspect backend and footprint. If the image changes, inspect renderer and assets. The decision describes the original RTX 2070 under particular workstation or server conditions. It promises neither a fixed client count nor TPS or gains over SUPER. The observed baseline remains evidence rather than being replaced by an assumption that all nominal 8 GB are free.
Coding LLMs on 8GB VRAM: Start with a Bounded Task · Display-attached GPUs: the VRAM baseline before model loading · GPU catalog