GPU comparison
RTX 4070 Super vs RTX 4070 Ti Super for AI
Draft record to structure a future verified AI workflow comparison.
Planning summary only. Verify exact GPU variants, runtime support, and workload behavior before making purchase decisions.
RTX 4070 Super
- VRAM
- Needs verification
- Memory type
- Needs verification
- Bandwidth
- Needs verification
- Board power / TGP
- Needs verification
RTX 4070 Ti Super
- VRAM
- 16 GB
- Memory type
- GDDR6X
- Bandwidth
- 672 GB/s
- Board power / TGP
- 285 W
Quick planning summary
RTX 4070 Super: Needs verification | RTX 4070 Ti Super: 16 GB
RTX 4070 Super: Needs verification | RTX 4070 Ti Super: 672 GB/s
RTX 4070 Super: Needs verification | RTX 4070 Ti Super: 285 W
Image workflow planning
RTX 4070 Super: low | RTX 4070 Ti Super: medium
Benchmark evidence, exact board-partner variant, runtime compatibility, and workload fit.
Comparison table
| Field | RTX 4070 Super | RTX 4070 Ti Super |
|---|---|---|
| Memory planning | ||
| VRAM | Needs verification | 16 GB |
| Memory type | Needs verification | GDDR6X |
| Memory bus | Needs verification | 256-bit |
| Memory bandwidth | Needs verification | 672 GB/s |
| Compute / architecture | ||
| Vendor | NVIDIA | NVIDIA |
| Architecture | Needs verification | Ada Lovelace |
| Core / execution units | Needs verification | 8448 CUDA cores |
| Power planning | ||
| Board power / TGP | Needs verification | 285 W |
| Power connector | Needs verification | 1 x 16-pin |
| Verification | ||
| Status | Needs verification | Source-backed GPU specs available |
| Data confidence | low | medium |
| Last verified | Needs verification | 2026-05-29 |
Cautious verdict
Available source-backed planning fields do not create a clear split between these GPUs yet.
This is not a benchmark verdict, and it should not be treated as purchase guidance.
Final fit still depends on model size, quantization, runtime support, drivers, and tested workload behavior.
How to interpret this comparison
VRAM is capacity headroom, not guaranteed speed. Memory bandwidth can matter, but benchmark evidence is still needed before drawing performance conclusions.
Runtime support, drivers, and exact board-partner variants can change practical results. Use the VRAM Calculator before treating this comparison as purchase guidance.
RECOMMENDED NEXT STEP
Check model memory before choosing between these GPUs
Run your model assumptions through the VRAM Calculator, then return to GPU profiles for source notes and board-partner verification.
Use case notes
For local LLM planning, prioritize VRAM headroom and runtime compatibility. For image workflows, avoid assuming performance until benchmark evidence is attached.
When to choose cloud GPU instead
Consider cloud testing when memory estimates exceed local cards, when workloads are infrequent, or when validating before hardware purchase.
FAQ
Why compare two close Ada-generation GPUs for AI planning?
Close-generation comparisons help identify whether extra VRAM or memory subsystem differences matter for the target workload. Draft or unsourced fields should be verified before treating the comparison as guidance.
When should I use the VRAM Calculator first?
Use it before comparing cards so your shortlist matches estimated memory requirements.
When should I choose cloud GPU instead?
When local VRAM is below estimate, testing is occasional, or you need validation before buying.
Should I rely on this comparison as purchase guidance?
No. This page is planning guidance and intentionally avoids unsupported benchmark, price, availability, and buying claims.
Related GPU profiles
Sources and data confidence
RTX 4070 Super
Confidence: low
Source types: none attached
RTX 4070 Ti Super
Confidence: medium
Source types: official, manufacturer
Includes manufacturer / variant-specific fields.
No benchmark source is attached to this comparison, so benchmark claims are not included.