Alquilar Nvidia Nvidia Titan V.

Name: Nvidia Nvidia Titan V
Brand: Nvidia
SKU: nvidia-titan-v

3GB VRAM 250W

AI models

Models that run on this GPU.

GPU-count + quantization recommendations covering fine-tuning, inference, and run-it-yourself scenarios on the Nvidia Nvidia Titan V.

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FAQ

AI models on this GPU.

What AI models can I run on a Nvidia Titan V?

The grid above lists every open-weights model with a recommended GPU configuration for this card. Each row tells you the minimum GPU count and the quantization level (FP16, FP8, INT8, INT4) needed to load the model in 3GB of VRAM.

What's the VRAM minimum to run a model on the Nvidia Titan V?

Rule of thumb: a model needs roughly (parameters × bytes-per-weight × 1.2) of VRAM to load, plus headroom for the KV cache during inference. FP16 = 2 bytes/weight, FP8/INT8 = 1 byte, INT4 = 0.5 bytes. A 70B model at FP16 needs ~168GB; at INT4 it drops to ~42GB and fits a single high-VRAM card.

How does quantization (FP16 vs FP8 vs INT4) affect what fits?

Lower-precision quantization shrinks the memory footprint nearly linearly with the bit count. The trade-off is output quality: FP16 is the reference, FP8 is usually indistinguishable for most prompts, INT8 introduces small quality losses, INT4 is noticeably degraded on reasoning-heavy tasks but fine for chat. The badge on each row tells you which level the recommendation assumes.

Can I fine-tune on the Nvidia Titan V or only do inference?

Fine-tuning needs 4–8× more VRAM than inference at the same model size — gradients, optimizer state, and activations all live in memory. LoRA / QLoRA cut that overhead dramatically (often 4–10×). The notes column flags whether a row is an inference-only recommendation or includes a fine-tuning path.

Where do these GPU-count recommendations come from?

We curate them from official model cards, community benchmark threads (r/LocalLLaMA, HuggingFace forum), and known-good configurations published by the model makers. Each recommendation has been verified to load at the stated quantization on the listed GPU count — though throughput and context-length still vary by workload.

Alquilar Nvidia Nvidia Titan V.

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Run these on this GPU.

Frequently asked.

Models that run on this GPU.

Whisper Medium

Whisper Small

Whisper Base

Whisper Tiny

Stable Diffusion 1.5

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BGE-M3

Gemma 3 1B

TinyLlama 1.1B

Gemma 3 270M It Lora

Meta Llama 3.2 1B Instruct

Gemma 3 1b it

Gemma 3 270M It

Gemma 3 1B Pt

DeepSeek R1 Distill Qwen 1.5B

Whisper Large v3

Whisper Medium

Whisper Small

Whisper Base

Whisper Tiny

Stable Diffusion 1.5

Llama 3.2 1B

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BGE-M3

Gemma 3 1B

TinyLlama 1.1B

Moondream 1.8B

Gemma 3 270M It Lora

Gemma 2B It

Meta Llama 3.2 1B Instruct

Gemma 3 1b it

Gemma 3 270M It

Gemma 3 1B Pt

Qwen3.5-2B

Arcee AI: Spotlight

DeepSeek R1 Distill Qwen 1.5B

Whisper Large v3

Whisper Medium

Whisper Small

Whisper Base

Whisper Tiny

Stable Diffusion 3.5 Medium

Stable Diffusion XL

Stable Diffusion 1.5

Llama 3.2 1B

Llama 3.2 3B

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BGE-M3

Qwen 2.5 3B

Qwen 3 4B

Gemma 2 2B

Gemma 3 4B

Gemma 3 1B

Phi-3.5 Mini

Phi-3 Mini

TinyLlama 1.1B

Moondream 1.8B

Mistral: Ministral 3 3B 2512

Qwen3 4B Base

Gemma 3 4b it

Gemma 3 270M It Lora

Qwen2.5 3B Instruct

Gemma 2B It

Qwen3 4B Instruct 2507

Meta Llama 3.2 1B Instruct

Gemma 3 1b it

Gemma 3 270M It

Meta Llama 3.2 3B Instruct

Gemma 3 1B Pt

Qwen3.5-2B

Qwen3.5-4B

Microsoft: Phi 4 Mini Instruct