NVIDIA · 12 GB GDDR · 504 GB/s
Yes. GeForce RTX 4070 Ti fits Mistral Nemo 12B Instruct at Q4_K_M, the largest catalog model that clears the fit line at 8K context.
192-bit GDDR6X at 1313 MHz. 1313×16×192/8 = 504 GB/s. Source.
| Model | Quant | Weights | Total | Verdict | Speed | Ollama |
|---|---|---|---|---|---|---|
| Mistral Nemo 12B Instruct | Q4_K_M | 6.96 GiB | 9.15 GiB | Fits | 31–54 tok/s | ollama run mistral-nemo:12b |
| Gemma 4 12B | Q4_K_M | 6.63 GiB | 7.95 GiB | Fits | 37–57 tok/s | ollama run gemma4:12b |
| Gemma 3 12B Instruct | Q4_K_M | 6.80 GiB | 8.52 GiB | Fits | 34–55 tok/s | ollama run gemma3:12b |
| Qwen3.5 9B | Q4_K_M | 5.29 GiB | 6.39 GiB | Fits | 46–71 tok/s | ollama run qwen3.5:9b |
| Qwen3 8B | Q4_K_M | 4.68 GiB | 6.62 GiB | Fits | 44–80 tok/s | ollama run qwen3:8b |
| Llama 3.1 8B Instruct | Q4_K_M | 4.58 GiB | 6.39 GiB | Fits | 46–82 tok/s | ollama run llama3.1:8b |
| Qwen2.5 7B Instruct | Q4_K_M | 4.36 GiB | 5.56 GiB | Fits | 54–86 tok/s | ollama run qwen2.5:7b |
| Gemma 4 E4B | Q4_K_M | 4.64 GiB | 5.66 GiB | Fits | 53–81 tok/s | ollama run gemma4:e4b |
| Gemma 4 E2B | Q4_K_M | 2.89 GiB | 3.69 GiB | Fits | 86–130 tok/s | ollama run gemma4:e2b |
| Gemma 3 4B Instruct | Q4_K_M | 2.32 GiB | 3.24 GiB | Fits | 100–162 tok/s | ollama run gemma3:4b |
| Phi-4-mini Instruct | Q4_K_M | 2.32 GiB | 4.01 GiB | Fits | 78–162 tok/s | ollama run phi4-mini |
| Llama 3.2 3B Instruct | Q4_K_M | 1.88 GiB | 3.42 GiB | Fits | 94–200 tok/s | ollama run llama3.2:3b |
| SmolLM3 3B | Q4_K_M | 1.78 GiB | 2.99 GiB | Fits | 110–211 tok/s | — |
| Llama 3.2 1B Instruct | Q4_K_M | 0.75 GiB | 1.58 GiB | Fits | 258–499 tok/s | ollama run llama3.2:1b |
| Qwen2.5 14B Instruct | Q4_K_M | 8.37 GiB | 10.9 GiB | Tight | 26–45 tok/s | ollama run qwen2.5:14b |
| DeepSeek-R1 Distill Qwen 14B | Q4_K_M | 8.37 GiB | 10.9 GiB | Tight | 26–45 tok/s | ollama run deepseek-r1:14b |
| Qwen3 14B | Q4_K_M | 8.38 GiB | 10.6 GiB | Tight | 27–45 tok/s | ollama run qwen3:14b |
| Phi-4 | Q4_K_M | 8.43 GiB | 11.0 GiB | Tight | 26–45 tok/s | ollama run phi4:14b |
| Qwen3.6 35B-A3B | UD-Q4_K_M | 20.6 GiB | 22.4 GiB | Offload | 13–18 tok/s | — |
| Qwen2.5 32B Instruct | Q4_K_M | 18.5 GiB | 22.0 GiB | Offload | 1–2 tok/s | ollama run qwen2.5:32b |
| DeepSeek-R1 Distill Qwen 32B | Q4_K_M | 18.5 GiB | 22.0 GiB | Offload | 1–2 tok/s | ollama run deepseek-r1:32b |
| Qwen3 32B | Q4_K_M | 18.4 GiB | 22.0 GiB | Offload | 1–2 tok/s | ollama run qwen3:32b |
| Gemma 4 31B | Q4_K_M | 17.1 GiB | 19.9 GiB | Offload | 2 tok/s | ollama run gemma4:31b |
| Qwen3 30B-A3B | Q4_K_M | 17.3 GiB | 19.5 GiB | Offload | 15–22 tok/s | ollama run qwen3:30b-a3b |
| Qwen3.8 27B | UD-Q4_K_M | 15.3 GiB | 17.3 GiB | Offload | 2–4 tok/s | — |
| Gemma 3 27B Instruct | Q4_K_M | 15.4 GiB | 17.8 GiB | Offload | 2–3 tok/s | ollama run gemma3:27b |
| Gemma 4 26B-A4B | UD-Q4_K_M | 15.8 GiB | 17.5 GiB | Offload | 17–25 tok/s | ollama run gemma4:26b-a4b |
| Mistral Small 3.2 24B Instruct | Q4_K_M | 13.3 GiB | 15.9 GiB | Offload | 3–5 tok/s | — |
| Devstral Small 2 24B Instruct | Q4_K_M | 13.3 GiB | 15.9 GiB | Offload | 3–5 tok/s | — |
| gpt-oss-20b | MXFP4 | 11.3 GiB | 12.6 GiB | Offload | 105–153 tok/s | ollama run gpt-oss:20b |
| gpt-oss-120b | MXFP4 | 59.0 GiB | 62.8 GiB | No | — | ollama run gpt-oss:120b |
| Qwen2.5 72B Instruct | Q4_K_M | 44.2 GiB | 49.5 GiB | No | — | ollama run qwen2.5:72b |
| Llama 3.3 70B Instruct | Q4_K_M | 39.6 GiB | 44.7 GiB | No | — | ollama run llama3.3:70b |
FAQ
What does the verdict for GeForce RTX 4070 Ti mean?
Memory is the GGUF file, plus KV cache at 8,192 tokens, plus a 0.5 GiB engine allowance, then 5% headroom. Fits means that total is at most 85% of fast memory. Tight means it still fits. Offload means it needs system RAM. No means it does not fit in VRAM plus system RAM after an 8 GB Windows reserve. The formula is on the methodology page.
What memory did you count as usable?
Fast memory is the full 12 GB. System RAM is assumed to be 32 GB DDR5-5600, with 8 GB kept for Windows, and you can change that on the homepage calculator.
Why is speed a range?
Decode speed is memory bandwidth divided by the bytes read per token. The high end is 80% of that roofline on the weights alone. The low end is 55% once the KV cache at the working context is included. It is not a benchmark.
How should I run Qwen2.5 14B Instruct?
The table uses Q4_K_M. Ollama's matching command is `ollama run qwen2.5:14b`. That blob is the library default and can differ from the cited GGUF by a few hundred MB.