The RTX 4070 Ti SUPER packs 16GB GDDR6X and delivers 72 tokens per second for 8B models. A strong performer from the previous generation, offering enough VRAM for 14B models with solid throughput.
16GB GDDR6X at 672 GB/s positions this card between the 5060 Ti and 5070 Ti in bandwidth. It loads 14B Q4 models with room to spare and handles 7B models at 72 tok/s. The main drawback is pricing: at $1,148 MSRP, it costs more than the newer RTX 5070 Ti ($749) which is actually faster. Best bought on the used market where prices have dropped since the RTX 50-series launch.
| GPU | VRAM | Speed | Bandwidth | Price |
|---|---|---|---|---|
| RTX 5070 Ti | 16 GB | 87 tok/s | 896 GB/s | $749 |
| RTX 4070 SUPER | 12 GB | 56 tok/s | 504 GB/s | $759 |
| RTX 4070 Ti SUPER | 16 GB | 72 tok/s | 672 GB/s | $1,148 |
| RTX 4080 SUPER | 16 GB | 79 tok/s | 736 GB/s | $1,597 |
Llama / 8B / Q4_K_M / ~6.5 GB
Best for: Chat, Coding·Pop: 94/100
Perf: ~72.0 tok/s · first token ~0.4s
Fits in 16 GB VRAM with room to spare. Best for chat, coding on RTX 4070 Ti SUPER.
ollama run llama3.1:8b-instruct-q4_K_M
Qwen / 9B / Q4_K_M / ~7 GB
Best for: Quality, Coding, Reasoning·Pop: 86/100
Perf: ~65.1 tok/s · first token ~0.4s
Fits in 16 GB VRAM with room to spare. Best for quality, coding, reasoning on RTX 4070 Ti SUPER.
ollama run qwen3.5:9b-instruct-q4_K_M
Qwen / 8B / Q4_K_M / ~6.5 GB
Best for: Chat, Coding·Pop: 88/100
Perf: ~72.0 tok/s · first token ~0.4s
Fits in 16 GB VRAM with room to spare. Best for chat, coding on RTX 4070 Ti SUPER.
ollama run qwen3:8b-q4_K_M
Mistral / 7B / Q4_K_M / ~5.5 GB
Best for: Chat, Coding·Pop: 90/100
Perf: ~80.7 tok/s · first token ~0.4s
Fits in 16 GB VRAM with room to spare. Best for chat, coding on RTX 4070 Ti SUPER.
ollama run mistral:7b-instruct-q4_K_M
Qwen / 7B / Q4_K_M / ~5.5 GB
Best for: Coding·Pop: 85/100
Perf: ~80.7 tok/s · first token ~0.4s
Fits in 16 GB VRAM with room to spare. Best for coding on RTX 4070 Ti SUPER.
ollama run qwen2.5-coder:7b-q4_K_M
Qwen / 7B / Q4_K_M / ~5.5 GB
Best for: Chat, Coding·Pop: 86/100
Perf: ~80.7 tok/s · first token ~0.4s
Fits in 16 GB VRAM with room to spare. Best for chat, coding on RTX 4070 Ti SUPER.
ollama run qwen2.5:7b-instruct-q4_K_M
LFM2 / 8B / Q4_K_M / ~6 GB
Best for: Local agents, tool calling, fast chat·Pop: 75/100
Perf: ~72.0 tok/s · first token ~0.4s
Fits in 16 GB VRAM with room to spare. Best for local agents, tool calling, fast chat on RTX 4070 Ti SUPER.
ollama run liquidai/lfm2:8b-a1b-instruct-q4_K_M
DeepSeek / 7B / Q4_K_M / ~5.5 GB
Best for: Reasoning, Coding·Pop: 77/100
Perf: ~80.7 tok/s · first token ~0.4s
Fits in 16 GB VRAM with room to spare. Best for reasoning, coding on RTX 4070 Ti SUPER.
ollama run deepseek-r1-distill:qwen-7b-q4_K_M
Llama / 8B / Q5_K_M / ~8 GB
Best for: Chat, Coding·Pop: 82/100
Perf: ~61.9 tok/s · first token ~0.4s
Fits in 16 GB VRAM with room to spare. Best for chat, coding on RTX 4070 Ti SUPER.
ollama run llama3.1:8b-instruct-q5_K_M
Gemma / 9B / Q4_K_M / ~7 GB
Best for: Chat, Coding·Pop: 81/100
Perf: ~65.1 tok/s · first token ~0.4s
Fits in 16 GB VRAM with room to spare. Best for chat, coding on RTX 4070 Ti SUPER.
ollama run gemma2:9b-instruct-q4_K_M
Alibaba Cloud — Widest size range (0.5B to 235B)
LlamaMeta — Most popular open-weight model family
DeepSeekDeepSeek AI — Best-in-class reasoning with R1 models
MistralMistral AI — Excellent performance-per-parameter ratio
GemmaGoogle DeepMind — Excellent quality at small sizes (1B-9B)
PhiMicrosoft — Best quality-per-parameter in small sizes
The RTX 4070 Ti SUPER has 16GB GDDR6X VRAM with 672 GB/s bandwidth. About 15.5GB usable for model loading. Fits 14B models at Q4 and all 7B-9B models comfortably.
Up to 14B parameter models at Q4 quantization. Same model capacity as other 16GB cards. Speed is 72 tok/s — faster than the 4060 Ti but slower than the newer 5070 Ti.
At MSRP ($1,148), no. The RTX 5070 Ti costs $749 and is 21% faster. However, used 4070 Ti SUPERs at $600-700 offer good value — you get 16GB VRAM and 72 tok/s at a reasonable price.
The RTX 5070 Ti is faster (87 vs 72 tok/s), cheaper ($749 vs $1,148), and uses GDDR7. The 5070 Ti wins on every metric for AI workloads. The only reason to buy the 4070 Ti SUPER is availability or used pricing.
Use our interactive wizard to compare models across Apple Silicon and NVIDIA GPUs.