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NVIDIA RTX 4080 (16GB)

The NVIDIA RTX 4080 (16GB) is equipped with 16 GB of dedicated VRAM and 717 GB/s memory bandwidth. It provides 100% addressable VRAM for CUDA and TensorRT-LLM runtimes, supporting full precision and quantized inference.

Memory

16 GB

Usable Memory Ceiling

16 GB

Bandwidth

716.8 GB/s

Max Inference Class

14B Models (Q4)

TDP

320W

VRAM Usage vs Context Length

Simulated memory requirements as context increases. Curves crossing above the reference line will cause Out Of Memory (OOM) errors.

Precision:

Model Compatibility & Speed Matrix

Simulated inference throughput and memory feasibility across popular open-weights models.

Context:

KV Cache:

GPUs:

ModelParametersPrecisionTPS (Approx.)TTFTCan Run
Llama 3.2 1B

1.2B

INT4

191 tok/s

~297 ms

Llama 3.2 1B

1.2B

Q8

143 tok/s

~298 ms

Llama 3.2 1B

1.2B

FP16

92 tok/s

~302 ms

Llama 3.2 3B

3.2B

INT4

110 tok/s

~731 ms

Llama 3.2 3B

3.2B

Q8

73 tok/s

~736 ms

Llama 3.2 3B

3.2B

FP16

41 tok/s

~746 ms

Mistral 7B

7.2B

INT4

61 tok/s

~1573 ms

Mistral 7B

7.2B

Q8

37 tok/s

~1584 ms

Mistral 7B

7.2B

FP16

-

-

Llama 3.1 8B

8.0B

INT4

56 tok/s

~1742 ms

Llama 3.1 8B

8.0B

Q8

32 tok/s

~1905 ms

Llama 3.1 8B

8.0B

FP16

-

-

Mistral Nemo 12B

12.2B

INT4

39 tok/s

~2636 ms

Mistral Nemo 12B

12.2B

Q8

-

-

Mistral Nemo 12B

12.2B

FP16

-

-

Qwen 2.5 14B

14.7B

INT4

31 tok/s

~3436 ms

Qwen 2.5 14B

14.7B

Q8

-

-

Qwen 2.5 14B

14.7B

FP16

-

-

DeepSeek R1 32B

32.5B

INT4

-

-

Llama 3.3 70B

70.6B

INT4

-

-

Qwen 2.5 72B

72.7B

INT4

-

-

DeepSeek V3 671B

671B (37B active)

INT4

-

-

Need custom layer dimensions, offloading configurations, or distributed multi-node topology?

Open in Advanced VRAM Calculator

Inference Feasibility

Maximum model parameter class runnable by weight precision.

Context:

4-bit

Q4

14B Models

8-bit

Q8

8B Models

16-bit

FP16

3B Models

Fine-Tuning Feasibility

Hardware capacity for local training and adapter fine-tuning.

Context Length:

QLoRA

4-bit

14B Models

LoRA

16-bit

8B Models

Full Parameter Training

1B Models

Workload Recommendations

Guidance for optimal precision and operational ceilings on NVIDIA RTX 4080 (16GB).

Inference Sweet Spot

Optimal for 8B models across extended context (32k+). 14B models fit comfortably at Q4 precision with standard context.

Bandwidth & Speed Profile

With 716.8 GB/s aggregate bandwidth, batch size 1 inference operates in a memory-bandwidth bound regime. Generates approximately 159 tok/s on an 8B Q4 model and 19 tok/s on a 70B Q4 model.