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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 RTX 4060 8GB is NVIDIA's most power-efficient Ada Lovelace consumer GPU, drawing just 115W while still delivering Ada's 4th-gen Tensor Cores with FP8 support. The 8 GB VRAM limits you to 7B models at Q4 (Q8 is tight), but the very low TDP makes it ideal for small form factor builds or always-on AI setups. Its 272 GB/s bandwidth is modest and will bottleneck decode speed on any model that fills VRAM. For AI use, the RTX 4060 Ti 8GB or 16GB are considerably better picks at a small price premium.
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) | Runs natively | Llama 3.1 8B Q4 | — |
| LLM Coding (30B) | Won’t fit | Qwen 3 30B Q4 | — |
| LLM Large (70B) |
Architecture
Ada Lovelace is NVIDIA's fourth-generation RTX architecture, manufactured on TSMC's custom 4N process. It introduces 4th-generation Tensor Cores with FP8 support, 3rd-generation ray tracing cores, and the Shader Execution Reordering (SER) engine for improved workload scheduling.
AI Relevance
FP8 Tensor Core operations provide a significant uplift for quantized LLM inference compared to Ampere's FP16-only Tensor Cores. DLSS 3 Frame Generation demonstrates the architecture's AI processing capabilities.
Cost vs cloud API
Assumes 4 hours/day of active inference at 64 tok/s, RTX 4060 8GB amortized over 36 months, US residential electricity ($0.15/kWh), blended cloud pricing at $10 per 1M tokens (GPT-4o / Claude Sonnet tier).
27.6M
Tokens/month at this pace
$10.4
Monthly local cost
$276
Same tokens on cloud API
$0.375
Local $/1M tokens
Break-even: pays for itself in 1.1 months vs cloud API at this workload. Price reference: $299 MSRP.
Chat
SQwen 3.5 4B 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
ACodestral Mamba 7B 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. Known distribution channels: huggingface, ollama.
Agentic Coding
AJust out of reach
High-quality models that need a bit more memory
Image & Video Generation
21 of 52 models can generate images or video on your RTX 4060 8GB
| Model | Max Resolution | Gen Time | Grade |
|---|---|---|---|
| SD TurboImage | 512×512 | ~2.8s | S |
| Stable Diffusion 1.5Image | 512×768 | ~5.7s | S |
| Realistic Vision v5.1Image | 512×768 | ~5.7s | S |
| DreamShaper 8Image | 512×768 | ~5.7s | S |
| LCM DreamShaper v7 |
Upgrade paths
See what you unlock with more powerful hardware
Upgrade options
Unlocks 33 additional models that do not fit on the current setup.
Lifts average decode speed across fitting models by about 66%.
~$699 MSRP
Unlocks 34 additional models that do not fit on the current setup.
Lifts average decode speed across fitting models by about 67%.
~$999 MSRP
Unlocks 74 additional models that do not fit on the current setup.
~$329 MSRP
Unlocks 155 additional models that do not fit on the current setup.
Lifts average decode speed across fitting models by about 314%.
~$8,000 MSRP
Compare with similar
Related guides
| Won’t fit |
| Llama 3.1 70B Q4 |
| — |
| Image Gen (SDXL) | Runs with sequential offload | SDXL 1.0 FP16 | ~~1m 0s per image |
| Image Gen (Flux) | Won't fit | Flux.1 Dev FP16 | ~~1m 42s per image |
| Image Gen (SD 3.5) | Won't fit | SD 3.5 Large FP16 | ~~2m 5s per image |
| Video Short (25f) | Won't fit | LTX Video 2B | ~~19.8s/frame |
| Video Long (100f) | Won't fit | Wan Video 14B | ~~58.2s/frame |
Gemma 4 E2B is a specialized fit for Agentic Coding. 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.
Reasoning
ACodestral Mamba 7B is viable for Reasoning, 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. Known distribution channels: huggingface, ollama.
RAG
AGranite 4.1 3B matches RAG 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. Known distribution channels: huggingface, ollama.
| 512×768 |
| ~1.7s |
| S |
| PixArt-SigmaImage | 256×256 | ~22.8s | S |
| FramePack I2VVideo | 256×256 | ~41.8s/frame | A |
| SDXL TurboImage | 256×256 | ~7.6s | A |
| SDXL LightningImage | 256×256 | ~22.7s | B |
| Stable Diffusion XL 1.0Image | 256×256 | ~1m 0s | B |
| Playground v2.5Image | 256×256 | ~34.1s | B |
| RealVisXL v5.0Image | 256×256 | ~1m 8s | B |
| DreamShaper XLImage | 256×256 | ~1m 8s | B |
| Juggernaut XL v9Image | 256×256 | ~1m 8s | B |
| Animagine XL 3.1Image | 256×256 | ~1m 8s | B |
| Pony Diffusion V6 XLImage | 256×256 | ~1m 8s | B |
| Animagine XL 4.0Image | 256×256 | ~1m 8s | B |
| Illustrious XLImage | 256×256 | ~1m 8s | B |
| Wan Video 2.1 1.3BVideo | 256×256 | ~16.6s/frame | D |
| Stable Diffusion 3.5 MediumImage | 256×256 | ~39.8s | D |
| Flux.2 Klein 4BImage | 256×256 | ~6.8s | D |
| LTX Video 2BVideo | 256×256 | ~19.8s/frame | F |
| KolorsImage | 256×256 | ~45.5s | F |
| Stable CascadeImage | 256×256 | ~56.9s | F |
| AuraFlow v0.3Image | 256×256 | ~1m 42s | F |
| Stable Diffusion 3.5 LargeImage | 256×256 | ~2m 5s | F |
| Stable Diffusion 3.5 Large TurboImage | 256×256 | ~22.8s | F |
| CogVideoX 2BVideo | 256×256 | ~19.8s/frame | F |
| HunyuanVideoVideo | 256×256 | ~41.8s/frame | F |
| ChromaImage | 256×256 | ~22.8s | F |
| Z-Image TurboImage | 256×256 | ~23.5s | F |
| Flux.1 DevImage | 256×256 | ~1m 42s | F |
| Flux.1 SchnellImage | 256×256 | ~19.9s | F |
| LTX Video 13BVideo | 256×256 | ~41.8s/frame | F |
| Flux.1 Kontext DevImage | 256×256 | ~1m 54s | F |
| AnimateDiff v1.5.3Video | 512×768 | ~10.4s/frame | F |
| Cosmos Diffusion 7BVideo | 256×256 | ~32.6s/frame | F |
| CogVideoX 5BVideo | 256×256 | ~28.5s/frame | F |
| Wan2.2 TI2V 5BVideo | 256×256 | ~28.5s/frame | F |
| Flux.2 Klein 9BImage | 256×256 | ~11.4s | F |
| Flux.1 Fill DevImage | 256×256 | ~1m 37s | F |
| Mochi 1 PreviewVideo | 256×256 | ~37.6s/frame | F |
| HunyuanVideo 1.5Video | 256×256 | ~34.9s/frame | F |
| Helios 14BVideo | 256×256 | ~43s/frame | F |
| SkyReels V2 14BVideo | 256×256 | ~43s/frame | F |
| Wan Video 2.1 14BVideo | 256×256 | ~43s/frame | F |
| Wan Video 2.2 14BVideo | 256×256 | ~43s/frame | F |
| Qwen ImageImage | 256×256 | ~38.3s | F |
| Qwen Image EditImage | 256×256 | ~38.3s | F |
| Flux.2 DevImage | 256×256 | ~17m 57s | F |
| MAGI-1Video | 256×256 | ~53.4s/frame | F |
| HunyuanImage 3.0Image | 256×256 | ~1m 8s | 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 RTX 4060 8GB: RTX 3080 10GB, RTX 2080 Ti 11GB. Upgrading would unlock larger models and faster inference speeds.
Buying advice
Usable for local AI with limits
Can run 7 of 50 top models, mostly smaller ones. Larger models need heavy quantization or won't fit.
8.0 GB
VRAM
$299
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.
No major red flags
This recommendation has enough memory headroom and acceptable estimated speed for the selected workload.
Best upgrade itinerary
Unlocks 33 additional models that do not fit on the current setup.
Want more headroom? RTX 3080 10GB (10.0 GB VRAM) is the next step up.
