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Alibaba

Qwen 3 1.7B

Alibaba · dense · 1.7B parameters · 131,072 context

Quality
50.0

Architecture Details

TypeDENSE
Total Parameters1.7B
Active Parameters1.7B
Layers28
Hidden Dimension1,536
Attention Heads16
KV Heads8
Head Dimension128
Vocab Size151,936

Memory Requirements

BF16 Weights

3.4 GB

FP8 Weights

1.7 GB

INT4 Weights

0.8 GB

KV-Cache per Token57344 bytes
Activation Estimate0.30 GB

Fits on (single-node)

B200 SXM BF16B100 SXM BF16GB200 NVL72 (per GPU) BF16GB300 NVL72 (per GPU) BF16H200 SXM BF16H100 SXM BF16H100 PCIe BF16H100 NVL BF16

GPU Recommendations

A4000optimal

BF16 · 1 GPU · vllm

90/100

score

Throughput

711.5 tok/s

Cost/Month

$161

Cost/M Tokens

$0.09

Use this config →
RTX 4080optimal

BF16 · 1 GPU · vllm

90/100

score

Throughput

1.1K tok/s

Cost/Month

$304

Cost/M Tokens

$0.10

Use this config →
RTX 4070 Tioptimal

BF16 · 1 GPU · vllm

90/100

score

Throughput

800.4 tok/s

Cost/Month

$237

Cost/M Tokens

$0.11

Use this config →

API Pricing Comparison

No API pricing data available for this model.

Capabilities

Features

Tool Use Vision Code Math Reasoning Multilingual Structured Output

Supported Frameworks

vllmsglangtgitensorrt-llmollama

Supported Precisions

BF16 (default)FP8INT4

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