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NVIDIA
Operating mode
Use this to bias workload recommendations toward responsiveness, background autonomy, lighter serving, or multi-GPU scale-out.
Current mode
Balanced
Balanced for general local use. Keeps the ranking neutral across personal and serving workflows.
The GTX 1650 4GB is the weakest GPU in this batch for local AI and should only be considered a last resort. With just 4 GB of VRAM, only the smallest models (1B–3B parameter range) can run without CPU offloading. It uses the Turing architecture (compute capability 7.5) and has basic Tensor Core support, but the 128 GB/s bandwidth and 4 GB limit make inference painfully slow. Only practical use case is as a test environment for model compatibility, not production inference.
Beyond LLMs
What AI tasks this GPU can handle — from text generation to image and video creation.
| Capability | Status | Representative Model | Detail |
|---|---|---|---|
| LLM Chat (7B) | Won’t fit | Llama 3.1 8B Q4 | — |
| LLM Coding (30B) | Won’t fit | Qwen 3 30B Q4 | — |
| LLM Large (70B) |
Architecture
Turing is NVIDIA's first-generation RTX architecture, introducing dedicated RT and Tensor Cores to consumer GPUs for the first time. Built on TSMC's 12nm FinFET process.
AI Relevance
The first consumer architecture with Tensor Cores, enabling meaningful acceleration for INT8 and FP16 inference. However, limited VRAM (typically 6-11 GB) restricts modern LLM model sizes.
Chat
AQwen 3 1.7B matches Chat and keeps a practical fit profile. It is a recent-generation family, which helps on current local SOTA workloads. It fits natively with comfortable headroom. Context coverage stays within the requested workload envelope. Known distribution channels: huggingface, ollama, lm-studio.
Coding
CStarCoder2 3B is a specialized fit for Coding. It sits in the middle of the current generation mix. It fits natively with comfortable headroom. Context coverage stays within the requested workload envelope.
Agentic Coding
CJust out of reach
High-quality models that need a bit more memory
Image & Video Generation
1 of 52 models can generate images or video on your GTX 1650 4GB
| Model | Max Resolution | Gen Time | Grade |
|---|---|---|---|
| SD TurboImage | 512×512 | ~10.4s | D |
| Stable Diffusion 1.5Image | 512×768 | ~20.8s | F |
| Realistic Vision v5.1Image | 512×768 | ~20.8s | F |
| DreamShaper 8Image | 512×768 | ~20.8s | F |
| LCM DreamShaper v7 |
Upgrade paths
See what you unlock with more powerful hardware
Upgrade options
Unlocks 93 additional models that do not fit on the current setup.
Lifts average decode speed across fitting models by about 39%.
~$349 MSRP
Unlocks 93 additional models that do not fit on the current setup.
~$249 MSRP
Unlocks 164 additional models that do not fit on the current setup.
Lifts average decode speed across fitting models by about 74%.
~$219 MSRP
Unlocks 286 additional models that do not fit on the current setup.
Lifts average decode speed across fitting models by about 630%.
~$8,000 MSRP
Compare with similar
| Won’t fit |
| Llama 3.1 70B Q4 |
| — |
| Image Gen (SDXL) | Won't fit | SDXL 1.0 FP16 | ~~1m 23s per image |
| Image Gen (Flux) | Won't fit | Flux.1 Dev FP16 | ~~6m 14s per image |
| Image Gen (SD 3.5) | Won't fit | SD 3.5 Large FP16 | ~~7m 37s per image |
| Video Short (25f) | Won't fit | LTX Video 2B | ~~1m 12s/frame |
| Video Long (100f) | Won't fit | Wan Video 14B | ~~3m 32s/frame |
StarCoder2 3B is a specialized fit for Agentic Coding. It sits in the middle of the current generation mix. It fits natively with comfortable headroom. Context coverage stays within the requested workload envelope.
Reasoning
Cai21labs AI21 Jamba Reasoning 3B matches Reasoning and keeps a practical fit profile. It sits in the middle of the current generation mix. It fits natively with comfortable headroom. Context coverage stays within the requested workload envelope.
RAG
CQwen2.5 3B Instruct is viable for RAG, but is not the most specialized choice. It sits in the middle of the current generation mix. It fits natively with comfortable headroom. Context coverage stays within the requested workload envelope.
| 512×768 |
| ~6.2s |
| F |
| PixArt-SigmaImage | 256×256 | ~1m 23s | F |
| FramePack I2VVideo | 256×256 | ~2m 33s/frame | F |
| SDXL TurboImage | 256×256 | ~10.4s | F |
| SDXL LightningImage | 256×256 | ~31.2s | F |
| Stable Diffusion XL 1.0Image | 256×256 | ~1m 23s | F |
| Playground v2.5Image | 256×256 | ~2m 5s | F |
| RealVisXL v5.0Image | 256×256 | ~1m 34s | F |
| DreamShaper XLImage | 256×256 | ~1m 34s | F |
| Juggernaut XL v9Image | 256×256 | ~1m 34s | F |
| Animagine XL 3.1Image | 256×256 | ~1m 34s | F |
| Pony Diffusion V6 XLImage | 256×256 | ~1m 34s | F |
| Animagine XL 4.0Image | 256×256 | ~1m 34s | F |
| Illustrious XLImage | 256×256 | ~1m 34s | F |
| Wan Video 2.1 1.3BVideo | 256×256 | ~1m 1s/frame | F |
| Stable Diffusion 3.5 MediumImage | 256×256 | ~2m 25s | F |
| Flux.2 Klein 4BImage | 256×256 | ~24.9s | F |
| LTX Video 2BVideo | 256×256 | ~1m 12s/frame | F |
| KolorsImage | 256×256 | ~2m 46s | F |
| Stable CascadeImage | 256×256 | ~3m 28s | F |
| AuraFlow v0.3Image | 256×256 | ~6m 14s | F |
| Stable Diffusion 3.5 LargeImage | 256×256 | ~7m 37s | F |
| Stable Diffusion 3.5 Large TurboImage | 256×256 | ~1m 23s | F |
| CogVideoX 2BVideo | 256×256 | ~1m 12s/frame | F |
| HunyuanVideoVideo | 256×256 | ~2m 33s/frame | F |
| ChromaImage | 256×256 | ~1m 23s | F |
| Z-Image TurboImage | 256×256 | ~1m 26s | F |
| Flux.1 DevImage | 256×256 | ~6m 14s | F |
| Flux.1 SchnellImage | 256×256 | ~1m 13s | F |
| LTX Video 13BVideo | 256×256 | ~2m 33s/frame | F |
| Flux.1 Kontext DevImage | 256×256 | ~6m 56s | F |
| AnimateDiff v1.5.3Video | 512×512 | ~37.9s/frame | F |
| Cosmos Diffusion 7BVideo | 256×256 | ~1m 59s/frame | F |
| CogVideoX 5BVideo | 256×256 | ~1m 44s/frame | F |
| Wan2.2 TI2V 5BVideo | 256×256 | ~1m 44s/frame | F |
| Flux.2 Klein 9BImage | 256×256 | ~41.5s | F |
| Flux.1 Fill DevImage | 256×256 | ~5m 53s | F |
| Mochi 1 PreviewVideo | 256×256 | ~2m 17s/frame | F |
| HunyuanVideo 1.5Video | 256×256 | ~2m 8s/frame | F |
| Helios 14BVideo | 256×256 | ~2m 37s/frame | F |
| SkyReels V2 14BVideo | 256×256 | ~2m 37s/frame | F |
| Wan Video 2.1 14BVideo | 256×256 | ~2m 37s/frame | F |
| Wan Video 2.2 14BVideo | 256×256 | ~2m 37s/frame | F |
| Qwen ImageImage | 256×256 | ~2m 20s | F |
| Qwen Image EditImage | 256×256 | ~2m 20s | F |
| Flux.2 DevImage | 256×256 | ~65m 31s | F |
| MAGI-1Video | 256×256 | ~3m 15s/frame | F |
| HunyuanImage 3.0Image | 256×256 | ~4m 6s | F |
Image models estimated at 1024×1024 (28 steps, FP16). Video models estimated at 768×512 (25 frames, 30 steps, FP16). Actual performance varies with runtime and system load.
There are 4 upgrade path(s) from GTX 1650 4GB: RTX 2060 6GB, GTX 1060 6GB. Upgrading would unlock larger models and faster inference speeds.
Buying advice
Usable for local AI with limits
Can run 2 of 50 top models, mostly smaller ones. Larger models need heavy quantization or won't fit.
4.0 GB
VRAM
$149
MSRP
$37/GB
Cost per GB VRAM
Best models for this GPU
What will limit you first
This setup is broadly balanced for this model.
Older PCIe generation
PCIe 3.0 is workable, but it compounds the penalty when you offload heavily or try to scale across multiple cards.
Best upgrade itinerary
Unlocks 93 additional models that do not fit on the current setup.
Want more headroom? RTX 2060 6GB (6.0 GB VRAM) is the next step up.
