Updated minutes ago
Mistral Small 3.1 24B
Mistral AI · dense · 24B parameters · 131,072 context
Quality50.0
Architecture Details
TypeDENSE
Total Parameters24B
Active Parameters24B
Layers40
Hidden Dimension5,120
Attention Heads32
KV Heads8
Head Dimension128
Vocab Size32,768
Memory Requirements
BF16 Weights
48.0 GB
FP8 Weights
24.0 GB
INT4 Weights
12.0 GB
KV-Cache per Token163840 bytes
Activation Estimate1.50 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
H20optimal
FP8 · 1 GPU · tensorrt-llm
100/100
score
Throughput
1.1K tok/s
Cost/Month
$940
Cost/M Tokens
$0.34
H100 SXMoptimal
FP8 · 1 GPU · tensorrt-llm
95/100
score
Throughput
1.1K tok/s
Cost/Month
$1794
Cost/M Tokens
$0.65
H100 PCIeoptimal
FP8 · 1 GPU · tensorrt-llm
95/100
score
Throughput
697.1 tok/s
Cost/Month
$1794
Cost/M Tokens
$0.98
API Pricing Comparison
| Provider | Input $/M | Output $/M | Badges |
|---|---|---|---|
| mistral | $0.10 | $0.30 | Cheapest |
Capabilities
Features
✓ Tool Use✓ Vision✓ Code✓ Math✗ Reasoning✓ Multilingual✓ Structured Output
Supported Frameworks
vllmsglangtgitensorrt-llmollama
Supported Precisions
BF16 (default)FP8INT4