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Mistral - French AI startup known for efficient open models (founded 2023):
Mistral-7B-v0.1
Mistral-Nemo-Base-2407
Codestral-22B-v0.1
Mistral-Small-24B-Base-2501
Ministral-8B-Instruct-2410
Mistral-Large-Instruct-2411
Mixtral-8x7B-v0.1
Mixtral-8x22B-v0.1
Mamba-Codestral-7B-v0.1
Pixtral-12B-Base-2409
Voxtral-Mini-3B-2507
Voxtral-Small-24B-2507
Mistral-Small-3.2-24B-Instruct-2506
Ministral-3-3B-Base-2512
Ministral-3-8B-Base-2512
Ministral-3-14B-Base-2512
Mistral-Large-3-675B-Base-2512
Devstral-Small-2-24B-Instruct-2512
Devstral-2-123B-Instruct-2512
mistralai/Ministral-3-3B-Base-2512
📊 Model Parameters
Total Parameters
3,849,090,048
Context Length
2,048
Hidden Size
0
Layers
0
Attention Heads
0
KV Heads
0
💾 Memory Requirements
FP32 (Full)
14.34 GB
FP16 (Half)
7.17 GB
INT8 (Quantized)
3.58 GB
INT4 (Quantized)
1.79 GB
🔑 KV Cache (Inference)
Per Token (FP16)
0 B
Max Context FP32
0.0 MB
Max Context FP16
0.0 MB
Max Context INT8
0.0 MB
⚙️ Model Configuration
Attention Configuration
Tied Embeddings
Yes
Special Tokens
BOS Token ID
Not set
Pad Token ID
Not set
EOS Token ID
Not set
Data Type
Model Dtype
bfloat16
Layer Types:
Attention
MLP/FFN
Normalization
Embedding
Attention
MLP
Norm
Embedding
Clear
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