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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 4070 Ti Super 16GB combines 16 GB of GDDR6X VRAM with 672 GB/s bandwidth and strong compute, making it one of the best Ada Lovelace cards for local AI inference. The 16 GB VRAM fits 13B models at FP16 and 30B models at Q4 with fast decode speeds, unlike the bandwidth-constrained RTX 4060 Ti 16GB. This is the highest-VRAM Ada card that doesn't require spending $999+ on the RTX 4080 Super, and the bandwidth makes the extra VRAM genuinely usable.
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 102 tok/s, RTX 4070 Ti Super 16GB amortized over 36 months, US residential electricity ($0.15/kWh), blended cloud pricing at $10 per 1M tokens (GPT-4o / Claude Sonnet tier).
43.9M
Tokens/month at this pace
$26.7
Monthly local cost
$439
Same tokens on cloud API
$0.608
Local $/1M tokens
Break-even: pays for itself in 1.8 months vs cloud API at this workload. Price reference: $799 MSRP.
Chat
SQwen 3.5 9B 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
SQwen 3.5 9B is a specialized fit for 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.
Agentic Coding
SJust out of reach
High-quality models that need a bit more memory
Image & Video Generation
31 of 52 models can generate images or video on your RTX 4070 Ti Super 16GB
| Model | Max Resolution | Gen Time | Grade |
|---|---|---|---|
| SD TurboImage | 512×512 | 900ms | S |
| Stable Diffusion 1.5Image | 512×768 | ~1.8s | S |
| Realistic Vision v5.1Image | 512×768 | ~1.8s | S |
| DreamShaper 8Image | 512×768 | ~1.8s | S |
| LCM DreamShaper v7 |
Upgrade paths
See what you unlock with more powerful hardware
Upgrade options
Unlocks 2 additional models that do not fit on the current setup.
~$1,099 MSRP
Unlocks 14 additional models that do not fit on the current setup.
~$2,000 MSRP
Unlocks 36 additional models that do not fit on the current setup.
~$599 MSRP
Unlocks 81 additional models that do not fit on the current setup.
Lifts average decode speed across fitting models by about 118%.
~$8,000 MSRP
Compare with similar
Related guides
| Won’t fit |
| Llama 3.1 70B Q4 |
| — |
| Image Gen (SDXL) | Runs natively | SDXL 1.0 FP16 | ~~7.1s per image |
| Image Gen (Flux) | Won't fit | Flux.1 Dev FP16 | ~~31.9s per image |
| Image Gen (SD 3.5) | Runs with sequential offload | SD 3.5 Large FP16 | ~~1m 45s per image |
| Video Short (25f) | Runs natively | LTX Video 2B | ~~6.1s/frame |
| Video Long (100f) | Won't fit | Wan Video 14B | ~~18.1s/frame |
Qwen 3.5 9B 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
SQwen 3.5 9B matches Reasoning 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.
RAG
AGranite 4.1 8B 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 |
| 500ms |
| S |
| PixArt-SigmaImage | 1024×1024 | ~7.1s | S |
| FramePack I2VVideo | 256×256 | ~13s/frame | S |
| SDXL TurboImage | 512×512 | 900ms | S |
| SDXL LightningImage | 1024×1024 | ~2.7s | S |
| Stable Diffusion XL 1.0Image | 1024×1024 | ~7.1s | S |
| Playground v2.5Image | 1024×1024 | ~10.6s | S |
| RealVisXL v5.0Image | 1024×1024 | ~8s | S |
| DreamShaper XLImage | 1024×1024 | ~8s | S |
| Juggernaut XL v9Image | 1024×1024 | ~8s | S |
| Animagine XL 3.1Image | 1024×1024 | ~8s | S |
| Pony Diffusion V6 XLImage | 1024×1024 | ~8s | S |
| Animagine XL 4.0Image | 1024×1024 | ~8s | S |
| Illustrious XLImage | 1024×1024 | ~8s | S |
| Wan Video 2.1 1.3BVideo | 256×256 | ~5.2s/frame | S |
| Stable Diffusion 3.5 MediumImage | 256×256 | ~37.2s | S |
| Flux.2 Klein 4BImage | 256×256 | ~4.8s | S |
| LTX Video 2BVideo | 256×256 | ~6.1s/frame | S |
| KolorsImage | 256×256 | ~37.6s | A |
| Stable CascadeImage | 1024×1024 | ~17.7s | B |
| AuraFlow v0.3Image | 256×256 | ~1m 3s | B |
| Stable Diffusion 3.5 LargeImage | 256×256 | ~1m 45s | B |
| Stable Diffusion 3.5 Large TurboImage | 256×256 | ~19.1s | B |
| CogVideoX 2BVideo | 256×256 | ~6.1s/frame | D |
| HunyuanVideoVideo | 256×256 | ~13s/frame | D |
| ChromaImage | 256×256 | ~7.1s | D |
| Z-Image TurboImage | 256×256 | ~14.6s | D |
| Flux.1 DevImage | 256×256 | ~31.9s | F |
| Flux.1 SchnellImage | 256×256 | ~6.2s | F |
| LTX Video 13BVideo | 256×256 | ~13s/frame | F |
| Flux.1 Kontext DevImage | 256×256 | ~35.4s | F |
| AnimateDiff v1.5.3Video | 512×768 | ~3.2s/frame | F |
| Cosmos Diffusion 7BVideo | 256×256 | ~10.1s/frame | F |
| CogVideoX 5BVideo | 256×256 | ~8.9s/frame | F |
| Wan2.2 TI2V 5BVideo | 256×256 | ~8.9s/frame | F |
| Flux.2 Klein 9BImage | 256×256 | ~3.5s | F |
| Flux.1 Fill DevImage | 256×256 | ~30.1s | F |
| Mochi 1 PreviewVideo | 256×256 | ~11.7s/frame | F |
| HunyuanVideo 1.5Video | 256×256 | ~10.9s/frame | F |
| Helios 14BVideo | 256×256 | ~13.4s/frame | F |
| SkyReels V2 14BVideo | 256×256 | ~13.4s/frame | F |
| Wan Video 2.1 14BVideo | 256×256 | ~13.4s/frame | F |
| Wan Video 2.2 14BVideo | 256×256 | ~13.4s/frame | F |
| Qwen ImageImage | 256×256 | ~11.9s | F |
| Qwen Image EditImage | 256×256 | ~11.9s | F |
| Flux.2 DevImage | 256×256 | ~5m 35s | F |
| MAGI-1Video | 256×256 | ~16.6s/frame | F |
| HunyuanImage 3.0Image | 256×256 | ~21s | 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.
Buying advice
Usable for local AI with limits
Can run 11 of 50 top models, mostly smaller ones. Larger models need heavy quantization or won't fit.
16.0 GB
VRAM
$799
MSRP
$50/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 2 additional models that do not fit on the current setup.
Want more headroom? MacBook Pro M3 24GB (24.0 GB unified memory) is the next step up.
