ApX logoApX logo

NVIDIA RTX 6000 Blackwell (96GB)

The NVIDIA RTX 6000 Blackwell (96GB) features 96 GB of dedicated VRAM and 1792 GB/s memory bandwidth, supporting CUDA and TensorRT-LLM runtimes for full-precision and quantized inference.

Memory

96 GB

Usable Memory Ceiling

96 GB

Bandwidth

1792 GB/s

Max Inference Class

70B+ Models (Q4)

TDP

500W

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)DeepSeek-R1 32B (32B)AliceAI Foundation 80B A3B Base (80B (3B active))GLM-5.3 Flash (313.3B (17.3B active))

Precision:

Best Models to Run on NVIDIA RTX 6000 Blackwell (96GB)

Inference throughput, memory compatibility, and generation speeds for open-weights LLMs on NVIDIA RTX 6000 Blackwell (96GB).

Sort by:

Context:

KV Cache:

GPUs:

RankModelParametersPrecisionTPS (Approx.)TTFTCan Run

#33

Qwen 3.8 27B

27B

INT4
Q8
FP16

78 tok/s

48 tok/s

26 tok/s

~607 ms

~615 ms

~633 ms

#41

Qwen 3.8 Flash

176B (6B active)

INT4

194 tok/s

~147 ms

#48

Agnes 3.0 Flash

33B

INT4
Q8
FP16

67 tok/s

40 tok/s

22 tok/s

~737 ms

~746 ms

~768 ms

#61

Sarvam-105B

106B (10.3B active)

INT4

150 tok/s

~311 ms

#72

K2 Horizon MoVA 36B A4B

36B (4B active)

INT4
Q8
FP16

214 tok/s

172 tok/s

118 tok/s

~124 ms

~125 ms

~128 ms

#75

Ling 3.0 Flash VL

124B (5.5B active)

INT4

201 tok/s

~223 ms

#83

Qwen3.5-27B

27B

INT4
Q8
FP16

78 tok/s

48 tok/s

26 tok/s

~607 ms

~615 ms

~633 ms

#84

Qwen3.5-122B-A10B

122B (10B active)

INT4

125 tok/s

~319 ms

#92

Sarvam-30B

32B (2.4B active)

INT4
Q8
FP16

245 tok/s

210 tok/s

158 tok/s

~89 ms

~89 ms

~91 ms

#94

Qwen3.6 35B A3B

35B (3B active)

INT4
Q8
FP16

232 tok/s

194 tok/s

140 tok/s

~102 ms

~103 ms

~105 ms

#96

Muse Glimmer 30B

30B

INT4
Q8
FP16

72 tok/s

44 tok/s

23 tok/s

~672 ms

~681 ms

~701 ms

#100

Phi-4 Reasoning Plus

14B

INT4
Q8
FP16

98 tok/s

70 tok/s

43 tok/s

~325 ms

~329 ms

~338 ms

#101

MiMo V2 Flash

15B (309B active)

INT4
Q8
FP16

9 tok/s

5 tok/s

2 tok/s

~6.6s

~6.7s

~6.9s

#106

GLM-4.5-Air

106B (12B active)

INT4

53 tok/s

~359 ms

#108

Gemma 4 26B A4B

25.2B (3.8B active)

INT4
Q8
FP16

222 tok/s

178 tok/s

123 tok/s

~114 ms

~115 ms

~118 ms

#109

Gemma 4 12B

11.95B

INT4
Q8
FP16

108 tok/s

79 tok/s

49 tok/s

~279 ms

~282 ms

~290 ms

#113

Qwen3.5-9B

9B

INT4
Q8
FP16

163 tok/s

113 tok/s

68 tok/s

~211 ms

~214 ms

~220 ms

#114

Qwen3.5-35B-A3B

35B (3B active)

INT4
Q8
FP16

232 tok/s

194 tok/s

140 tok/s

~102 ms

~103 ms

~105 ms

#114

Ling 3.0 Flash

124B (5.1B active)

INT4

206 tok/s

~214 ms

#118

K2 Horizon 7B

7B

INT4
Q8
FP16

186 tok/s

134 tok/s

83 tok/s

~167 ms

~169 ms

~174 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 RTX 6000 Blackwell (96GB).

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 1792 GB/s aggregate bandwidth, batch size 1 inference operates in a memory-bandwidth bound regime. Generates approximately 398 tok/s on an 8B Q4 model and 47 tok/s on a 70B Q4 model.

Frequently Asked Questions