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NVIDIA A800 (80GB)

The NVIDIA A800 (80GB) features 80 GB of dedicated VRAM and 1935 GB/s memory bandwidth, supporting CUDA and TensorRT-LLM runtimes for full-precision and quantized inference.

Memory

80 GB

Usable Memory Ceiling

80 GB

Bandwidth

1935 GB/s

Max Inference Class

70B+ Models (Q4)

TDP

400W

VRAM Scaling by Context Length

Estimated memory requirements as context length increases. Curves crossing above the reference line indicate Out of Memory (OOM).

DeepSeek-R1 14B (14B)Nemotron 3.5 Lightning 30B A3B (30B (3B active))Llama 3.3 70B (70B)Qwen3-235B-A22B (235B (22B active))

Precision:

Best Models to Run on NVIDIA A800 (80GB)

Inference throughput, memory compatibility, and generation speeds for open-weights LLMs on NVIDIA A800 (80GB).

Sort by:

Context:

KV Cache:

GPUs:

RankModelParametersPrecisionTPS (Approx.)TTFTCan Run

#33

Qwen 3.8 27B

27B

INT4
Q8
FP16

87 tok/s

52 tok/s

27 tok/s

~1.1s

~1.1s

~1.1s

#48

Agnes 3.0 Flash

33B

INT4
Q8
FP16

74 tok/s

43 tok/s

21 tok/s

~1.3s

~1.3s

~1.5s

#61

Sarvam-105B

106B (10.3B active)

INT4

184 tok/s

~552 ms

#72

K2 Horizon MoVA 36B A4B

36B (4B active)

INT4
Q8
FP16

290 tok/s

218 tok/s

133 tok/s

~213 ms

~215 ms

~236 ms

#75

Ling 3.0 Flash VL

124B (5.5B active)

INT4

253 tok/s

~428 ms

#83

Qwen3.5-27B

27B

INT4
Q8
FP16

87 tok/s

52 tok/s

27 tok/s

~1.1s

~1.1s

~1.1s

#84

Qwen3.5-122B-A10B

122B (10B active)

INT4

142 tok/s

~615 ms

#92

Sarvam-30B

32B (2.4B active)

INT4
Q8
FP16

351 tok/s

284 tok/s

187 tok/s

~150 ms

~150 ms

~165 ms

#94

Qwen3.6 35B A3B

35B (3B active)

INT4
Q8
FP16

325 tok/s

255 tok/s

162 tok/s

~174 ms

~175 ms

~192 ms

#96

Muse Glimmer 30B

30B

INT4
Q8
FP16

80 tok/s

47 tok/s

25 tok/s

~1.2s

~1.2s

~1.2s

#100

Phi-4 Reasoning Plus

14B

INT4
Q8
FP16

112 tok/s

78 tok/s

46 tok/s

~571 ms

~574 ms

~584 ms

#101

MiMo V2 Flash

15B (309B active)

INT4
Q8
FP16

9 tok/s

5 tok/s

2 tok/s

~11.8s

~11.9s

~12.1s

#106

GLM-4.5-Air

106B (12B active)

INT4

54 tok/s

~682 ms

#108

Gemma 4 26B A4B

25.2B (3.8B active)

INT4
Q8
FP16

305 tok/s

229 tok/s

147 tok/s

~195 ms

~196 ms

~199 ms

#109

Gemma 4 12B

11.95B

INT4
Q8
FP16

126 tok/s

89 tok/s

53 tok/s

~489 ms

~492 ms

~500 ms

#113

Qwen3.5-9B

9B

INT4
Q8
FP16

205 tok/s

133 tok/s

75 tok/s

~369 ms

~372 ms

~378 ms

#114

Qwen3.5-35B-A3B

35B (3B active)

INT4
Q8
FP16

325 tok/s

255 tok/s

162 tok/s

~174 ms

~175 ms

~192 ms

#114

Ling 3.0 Flash

124B (5.1B active)

INT4

263 tok/s

~411 ms

#118

K2 Horizon 7B

7B

INT4
Q8
FP16

241 tok/s

161 tok/s

93 tok/s

~290 ms

~292 ms

~296 ms

#126

Qwen3 Next 80B A3B

80B (79B active)

INT4

26 tok/s

~3.1s

Inference Capacity

Maximum model parameter class runnable by weight precision.

Context:

4-bit

Q4

70B+ Models

8-bit

Q8

70B Models

16-bit

FP16

32B Models

Fine-Tuning Capacity

Hardware capacity for local training and adapter fine-tuning.

Context Length:

QLoRA

4-bit

70B+ Models

LoRA

16-bit

70B Models

Full Parameter Training

7B-8B Models

Workload Recommendations

Guidance for optimal precision and operational ceilings on NVIDIA A800 (80GB).

Inference Sweet Spot

Suitable for 70B parameter models at Q4/Q8 with extended 32k context windows, or high-throughput batching of smaller dense architectures.

Bandwidth & Speed Profile

With 1935 GB/s aggregate bandwidth, batch size 1 inference operates in a memory-bandwidth bound regime. Generates approximately 430 tok/s on an 8B Q4 model and 51 tok/s on a 70B Q4 model.

Frequently Asked Questions