ApX logoApX logo

NVIDIA H200 (141GB)

The NVIDIA H200 (141GB) features 141 GB of dedicated VRAM and 4800 GB/s memory bandwidth, supporting CUDA and TensorRT-LLM runtimes for full-precision and quantized inference.

Memory

141 GB

Usable Memory Ceiling

141 GB

Bandwidth

4800 GB/s

Max Inference Class

70B+ Models (Q4)

TDP

700W

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)OLMo 3 32B Base (32B)GPT-OSS 120B (117B (5.1B active))ERNIE-4.5-VL-424B-A47B-Base (424B (47B active))

Precision:

Best Models to Run on NVIDIA H200 (141GB)

Inference throughput, memory compatibility, and generation speeds for open-weights LLMs on NVIDIA H200 (141GB).

Sort by:

Context:

KV Cache:

GPUs:

RankModelParametersPrecisionTPS (Approx.)TTFTCan Run

#30

DeepSeek-V4-Flash-Vision-Exp

290.9B (20.4B active)

INT4

204 tok/s

~295 ms

#33

Qwen 3.8 27B

27B

INT4
Q8
FP16

182 tok/s

115 tok/s

64 tok/s

~345 ms

~348 ms

~355 ms

#41

Qwen 3.8 Flash

176B (6B active)

INT4

422 tok/s

~77 ms

#42

DeepSeek-V4-Flash

284B (13B active)

INT4

267 tok/s

~190 ms

#48

Agnes 3.0 Flash

33B

INT4
Q8
FP16

157 tok/s

97 tok/s

53 tok/s

~419 ms

~423 ms

~432 ms

#61

Sarvam-105B

106B (10.3B active)

INT4
Q8

325 tok/s

233 tok/s

~178 ms

~179 ms

#72

K2 Horizon MoVA 36B A4B

36B (4B active)

INT4
Q8
FP16

438 tok/s

365 tok/s

264 tok/s

~70 ms

~71 ms

~72 ms

#75

Ling 3.0 Flash VL

124B (5.5B active)

INT4
Q8

416 tok/s

311 tok/s

~127 ms

~139 ms

#82

Qwen3 235B A22B Thinking

235B (22B active)

INT4

75 tok/s

~414 ms

#83

Qwen3.5-27B

27B

INT4
Q8
FP16

182 tok/s

115 tok/s

64 tok/s

~345 ms

~348 ms

~355 ms

#84

Qwen3.5-122B-A10B

122B (10B active)

INT4
Q8

278 tok/s

201 tok/s

~182 ms

~199 ms

#92

Sarvam-30B

32B (2.4B active)

INT4
Q8
FP16

489 tok/s

432 tok/s

340 tok/s

~50 ms

~50 ms

~51 ms

#94

Qwen3.6 35B A3B

35B (3B active)

INT4
Q8
FP16

468 tok/s

404 tok/s

307 tok/s

~58 ms

~58 ms

~59 ms

#96

Muse Glimmer 30B

30B

INT4
Q8
FP16

168 tok/s

105 tok/s

58 tok/s

~382 ms

~386 ms

~394 ms

#100

Phi-4 Reasoning Plus

14B

INT4
Q8
FP16

223 tok/s

165 tok/s

103 tok/s

~184 ms

~186 ms

~189 ms

#101

MiMo V2 Flash

15B (309B active)

INT4
Q8
FP16

22 tok/s

12 tok/s

6 tok/s

~3.7s

~3.8s

~3.9s

#106

GLM-4.5-Air

106B (12B active)

INT4
Q8

126 tok/s

106 tok/s

~203 ms

~221 ms

#108

Gemma 4 26B A4B

25.2B (3.8B active)

INT4
Q8
FP16

451 tok/s

377 tok/s

275 tok/s

~64 ms

~65 ms

~66 ms

#109

Gemma 4 12B

11.95B

INT4
Q8
FP16

245 tok/s

184 tok/s

117 tok/s

~158 ms

~159 ms

~162 ms

#111

MiniMax M2

229B (10B active)

INT4

89 tok/s

~241 ms

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 H200 (141GB).

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 4800 GB/s aggregate bandwidth, batch size 1 inference operates in a memory-bandwidth bound regime. Generates approximately 1067 tok/s on an 8B Q4 model and 126 tok/s on a 70B Q4 model.

Frequently Asked Questions