AudioQwenMIT

Qwen2-Audio 7B

Qwen/Qwen2-Audio-7B-Instruct

Parameters

7.6B

Context

8K

Downloads

607.9K

Likes

551

Architecture

transformer

View on HuggingFace

GPU Requirements

VRAM / RAM / disk estimates by quantization and usage scenario

QuantizationMinimumRecommendedProduction
FP1616bit
37.3 GB
RAM 56.0 · Disk 61.1
40.0 GB
RAM 59.9 · Disk 87.1
43.6 GB
RAM 65.4 · Disk 126.1
FP88bit
20.2 GB
RAM 32.0 · Disk 50.0
22.1 GB
RAM 33.1 · Disk 76.0
24.9 GB
RAM 37.4 · Disk 115.0
INT88bit
20.2 GB
RAM 32.0 · Disk 50.0
22.1 GB
RAM 33.1 · Disk 76.0
24.9 GB
RAM 37.4 · Disk 115.0
AWQ4bit
12.0 GB
RAM 32.0 · Disk 44.7
13.4 GB
RAM 32.0 · Disk 70.7
15.9 GB
RAM 32.0 · Disk 109.7
GPTQ4bit
12.1 GB
RAM 32.0 · Disk 44.8
13.5 GB
RAM 32.0 · Disk 70.8
16.1 GB
RAM 32.0 · Disk 109.8
GGUF4bit
12.3 GB
RAM 32.0 · Disk 44.9
13.8 GB
RAM 32.0 · Disk 70.9
16.3 GB
RAM 32.0 · Disk 109.9

GPU Recommendations

Best ValueBEST

1× RTX 5090

32 GB VRAM

$257/mo

≈ 41800 chars/s

Effective production throughput ≈ 29260 chars/s

score 0.6094

Deploy on vast ↗
Cheapest

1× RTX 4070S Ti

16 GB VRAM

$49.5/mo

≈ 0 chars/s (N/A — benchmark unavailable)

Effective production throughput ≈ 0 chars/s

score 0.6651

Deploy on vast ↗
Performance

8× H100 SXM

640 GB VRAM

$9,362/mo

≈ 107040 chars/s

Effective production throughput ≈ 74928 chars/s

score 0.2415

Deploy on vast ↗
Min Complexity

1× RTX 3090

24 GB VRAM

$76.5/mo

≈ 14200 chars/s

Effective production throughput ≈ 9940 chars/s

score 0.6443

Deploy on vast ↗

💬 Community — real deployment experience

0 Articles · 0 Benchmarks

View Community →

GPUs that fit (single card)

RTX 4070S Ti

16 GB VRAM

$49.5

/mo · vast

RTX 4080S

16 GB VRAM

$50.0

/mo · vast

RTX 3090

24 GB VRAM

$76.5

/mo · vast

RTX 5070 Ti

16 GB VRAM

$86.3

/mo · vast

Tesla V100

16 GB VRAM

$88.4

/mo · vast

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