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The ordinary GTX 1660 has 6 GB GDDR5; a verified model file and supported build matter more than assuming every Turing feature.
The ordinary GDDR5 model
The GTX 1660 uses Turing, 6 GB GDDR5 and reference board power of 120 W. GTX 1660 SUPER and Ti are other models despite also having 6 GB. NVIDIA’s GTX 16 table lists no Tensor or RT cores, an important distinction from RTX hardware. Capacity is per GPU rather than a sum across cards. Preserve AIB identity, driver and available baseline. Nominal 6 GB does not mean every smaller file leaves enough room for runtime, context and other device processes. Establish the whole working configuration before judging task suitability.
| Official variant | Memory per GPU | Memory type | Board power | Evidence |
|---|---|---|---|---|
| NVIDIA GeForce GTX 1660 — 6 GB NVIDIA comparison design | 6 GB | GDDR5 | 120 W | Specification |
Verify file and software path
CC 7.5 matches the vLLM hardware floor rather than certifying kernels or useful GTX serving without Tensor hardware. In a bounded llama.cpp CUDA experiment, preserve GGUF source, revision, hash and quantization format with build commit. Set context, output and offload afterward. A different model file turns the comparison into another configuration. Observe actual GPU layers and CPU/RAM, then validate answer and termination. Do not replace result quality with successful loading or treat CUDA involvement as proof of full residency within local 6 GB. Provenance and execution evidence answer different questions.
Accept a saved Cycles scene
Blender 5.2 CUDA and OptiX have independent requirements: CUDA CC 5.0, with OptiX also requiring driver 575 or newer. A suitable build and detection are necessary. GTX 1660 has no RTX RT cores, but no hardware acceleration does not prohibit every OptiX scenario. Preserve project, assets and settings, then check backend, image and VRAM/RAM. Record host memory separately. Another renderer needs its own device and feature requirements. Keep scenes comparable across repetitions: changed textures must not silently enter the second run from an external directory. The packed project defines the accepted input.
Associate files with the worker environment
The manifest retains model and scene package hashes, binary version, driver and device identity. A cache file on disk differs from GPU-resident weights. Confirm the previous process state before handing resources to another job. CPU and RAM participate in admission when offloading. Reference 120 W establishes neither complete node supply nor job energy. Verify AIB connectors and cooling. Normal validation requires neither forced clocks nor disabled protections; establish reproducible inputs and a supported path first. Otherwise a passing result cannot be repeated meaningfully. Keep cache and residency observations separate in the record.
Preserve provenance and execution evidence
The package contains GGUF provenance, hashes, manifests, settings, actual placement and LLM and scene outcomes. If a hash differs, investigate input before hardware speed. Unsupported operations point to build, while memory pressure points to budget and offload. CPU-only work receives another status. The conclusion concerns a verified ordinary GTX 1660 role rather than the whole Turing lineup. It promises neither known TPS nor every small model fits or superiority over another 6 GB card. Preserved provenance separates data changes from actual worker behavior changes. Retain these limits beside the accepted workload.
Choosing a GGUF file for llama.cpp · VRAM for LLMs: why model size is only part of the calculation · GPU catalog