Updated minutes ago
Qwen 3 8B
Alibaba · dense · 8.2B parameters · 131,072 context
Quality67.0
Architecture Details
TypeDENSE
Total Parameters8.2B
Active Parameters8.2B
Layers36
Hidden Dimension4,096
Attention Heads32
KV Heads8
Head Dimension128
Vocab Size151,936
Memory Requirements
BF16 Weights
16.4 GB
FP8 Weights
8.2 GB
INT4 Weights
4.1 GB
KV-Cache per Token147456 bytes
Activation Estimate1.00 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
A30optimal
BF16 · 1 GPU · vllm
100/100
score
Throughput
307.2 tok/s
Cost/Month
$332
Cost/M Tokens
$0.41
RTX 4090optimal
BF16 · 1 GPU · vllm
100/100
score
Throughput
331.9 tok/s
Cost/Month
$370
Cost/M Tokens
$0.42
RTX 3090optimal
BF16 · 1 GPU · vllm
100/100
score
Throughput
308.2 tok/s
Cost/Month
$180
Cost/M Tokens
$0.22
API Pricing Comparison
| Provider | Input $/M | Output $/M | Badges |
|---|---|---|---|
| together | $0.20 | $0.20 | Cheapest |
| fireworks | $0.20 | $0.20 |
Quality Benchmarks
MMLU72.0
HumanEval42.0
GSM8K78.0
MT-Bench77.0
Capabilities
Features
✓ Tool Use✗ Vision✓ Code✓ Math✓ Reasoning✓ Multilingual✓ Structured Output
Supported Frameworks
vllmsglangtgitensorrt-llmollama
Supported Precisions
BF16 (default)FP8INT4