Updated minutes ago
Llama 3.2 90B Vision
Meta · dense · 90B parameters · 131,072 context
Quality50.0
Architecture Details
TypeDENSE
Total Parameters90B
Active Parameters90B
Layers80
Hidden Dimension8,192
Attention Heads64
KV Heads8
Head Dimension128
Vocab Size128,256
Memory Requirements
BF16 Weights
180.0 GB
FP8 Weights
90.0 GB
INT4 Weights
45.0 GB
KV-Cache per Token327680 bytes
Activation Estimate3.00 GB
Fits on (single-node)
B200 SXM FP8B100 SXM FP8GB200 NVL72 (per GPU) FP8GB300 NVL72 (per GPU) FP8H200 SXM FP8H100 SXM INT4H100 PCIe INT4H100 NVL INT4
GPU Recommendations
B200 SXMoptimal
FP8 · 1 GPU · tensorrt-llm
100/100
score
Throughput
560.0 tok/s
Cost/Month
$4261
Cost/M Tokens
$2.90
B100 SXMoptimal
FP8 · 1 GPU · tensorrt-llm
100/100
score
Throughput
560.0 tok/s
Cost/Month
$4271
Cost/M Tokens
$2.90
GB200 NVL72 (per GPU)optimal
FP8 · 1 GPU · tensorrt-llm
100/100
score
Throughput
560.0 tok/s
Cost/Month
$6169
Cost/M Tokens
$4.19
API Pricing Comparison
| Provider | Input $/M | Output $/M | Badges |
|---|---|---|---|
| fireworks | $0.90 | $0.90 | Cheapest |
| together | $1.20 | $1.20 |
Capabilities
Features
✓ Tool Use✓ Vision✓ Code✓ Math✗ Reasoning✓ Multilingual✓ Structured Output
Supported Frameworks
vllmsglangtgitensorrt-llm
Supported Precisions
BF16 (default)FP8INT4