LLMLlama

dphn/dolphin-2.9.1-yi-1.5-34b

dphn/dolphin-2.9.1-yi-1.5-34b

Parameters

37.5B

Context

8K

Downloads

4.5M

Likes

65

Architecture

llama

60 layers · 8 KV heads · head 128 · hidden 7168

View on HuggingFace

GPU Requirements

VRAM / RAM / disk estimates by quantization and usage scenario

QuantizationMinimumRecommendedProduction
FP1616bit
98.7 GB
RAM 148.1 · Disk 147.8
142.0 GB
RAM 213.0 · Disk 173.8
368.7 GB
RAM 553.0 · Disk 212.8
FP88bit
54.6 GB
RAM 81.9 · Disk 93.4
95.9 GB
RAM 143.8 · Disk 119.4
320.5 GB
RAM 480.8 · Disk 158.4
INT88bit
54.6 GB
RAM 81.9 · Disk 93.4
95.9 GB
RAM 143.8 · Disk 119.4
320.5 GB
RAM 480.8 · Disk 158.4
AWQ4bit
33.3 GB
RAM 50.0 · Disk 67.2
73.7 GB
RAM 110.5 · Disk 93.2
297.4 GB
RAM 446.1 · Disk 132.2
GPTQ4bit
33.6 GB
RAM 50.4 · Disk 67.6
74.0 GB
RAM 110.9 · Disk 93.6
297.7 GB
RAM 446.5 · Disk 132.6
GGUF4bit
34.2 GB
RAM 51.3 · Disk 68.3
74.5 GB
RAM 111.8 · Disk 94.3
298.3 GB
RAM 447.4 · Disk 133.3

GPU Recommendations

Best ValueBEST

1× H200 SXM

141 GB VRAM

$2,555/mo

≈ 265.3 tok/s

Effective production throughput ≈ 185.7 tok/s

score 0.6104

Cheapest

4× RTX 3090

96 GB VRAM

$306/mo

≈ 124.2 tok/s

Effective production throughput ≈ 86.9 tok/s

score 0.605

Deploy on vast ↗
Performance

8× H200 SXM

1128 GB VRAM

$20,440/mo

≈ 849.1 tok/s

Effective production throughput ≈ 594.4 tok/s

score 0.2197

Min Complexity

1× A100 80GB

80 GB VRAM

$876/mo

≈ 112.7 tok/s

Effective production throughput ≈ 78.9 tok/s

score 0.6407

Deploy on vast ↗

💬 Community — real deployment experience

0 Articles · 0 Benchmarks

View Community →

GPUs that fit (single card)

A100 80GB

80 GB VRAM

$876

/mo · vast

H100 SXM

80 GB VRAM

$1,170

/mo · vast

H200 SXM

141 GB VRAM

$2,555

/mo · lambda

B200

180 GB VRAM

$3,013

/mo · vast

B200 SXM

180 GB VRAM

AmciHub

AI Model Deployment & Compute Intelligence — analyze AI model requirements, GPU performance, cloud pricing and deployment costs to find the right deployment solution.

© 2026 AmciHub. All rights reserved. Model → Requirement → GPU → Benchmark → Cloud → Cost → Recommendation