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The RTX 3070 Ti has 8 GB like the ordinary 3070; GDDR6X and Ti do not add space for weights, KV cache or scenes.
GDDR6X without extra capacity
The RTX 3070 Ti uses 8 GB GDDR6X and has reference board power of 290 W. The ordinary RTX 3070 also has 8 GB, but uses GDDR6 and another power specification. A memory type change is not added capacity. The table concerns one GPU. Record the actual AIB board, baseline VRAM and resident applications before deployment. Check supply and cooling separately. The 290 W figure is neither measured constant draw nor inference duration, even when the compared cards belong to one Ampere generation. Treat those as separate observations rather than implications of the suffix.
| Official variant | Memory per GPU | Memory type | Board power | Evidence |
|---|---|---|---|---|
| NVIDIA GeForce RTX 3070 Ti — 8 GB NVIDIA comparison design | 8 GB | GDDR6X | 290 W | Specification |
Establish an admissible LLM envelope
The vLLM requirements define hardware and software conditions, not every quantization kernel’s support. Select a checkpoint, context and output limit on the Ti. Bound attempts and stopping conditions before testing so memory investigation does not become endless load. If startup fails, distinguish unsupported operations from insufficient VRAM. llama.cpp CUDA is another path requiring explicit offload accounting. Successful generation involving host RAM does not establish full GPU residency or transfer automatically to another engine. Evaluate quantization quality with an application corpus rather than treating load success as the entire acceptance result.
Accept a scene with known assets
Check Cycles CUDA or OptiX using an appropriate Blender release and driver. Preserve geometry, textures and quality settings in the RTX 3070 Ti scene manifest. Verify detection, complete image and system memory involvement. Assets exceeding local capacity create another execution mode rather than expanding VRAM. RTX hardware tracing depends on backend support and certifies no arbitrary renderer. Change one asset group at a time when investigating a limit. Reducing every setting simultaneously cannot explain which resource actually determined the original failure. Keep the project and its failure condition available for reproduction.
Bound accumulated work
Decide beforehand what resource exhaustion means: reject a job or defer it within a defined queue limit. A 3070 Ti does not justify admitting unlimited requests while its engine is occupied. Rejection records should retain cause and configuration instead of presenting out-of-memory as a generic network failure. Confirm inference ownership is released before switching to rendering. Observe RAM, storage and other processes as well. Calculate supply requirements for the actual installation rather than only reference 290 W, and do not disable normal protections to work around experiment instability. Admission is part of operational suitability, not an afterthought.
Verify controlled rejection
The artifact contains an admissible workload and a deliberately more demanding variant, with bounded attempts and recorded settings. The goal is explainable failure classification and worker recovery, rather than overloading the GPU. If a subsequent admissible job fails, inspect remaining processes and the queue. If failure depends on the backend, change the hypothesis from capacity to compatibility. The result describes an actual RTX 3070 Ti 8 GB envelope for LLMs and Cycles. It promises neither every compact model fits nor automatic fallback or universal gains over the 3070 without another matched measurement.
Coding LLMs on 8GB VRAM: Start with a Bounded Task · LLM memory bandwidth: why gigabytes are not enough · GPU catalog