---
license: apache-2.0
language:
- en
pipeline_tag: text-generation
tags:
- mistral
- long-context
library_name: transformers
---

# Charlie 1.5

Charlie 1.5 is a high-performance, 12B-parameter large language model (LLM) built on the Mistral architecture. It is designed for **long-context reasoning, complex enterprise workflows, and structured decision-making**.

With a **131,072-token (128k+) context window**, Charlie 1.5 enables native processing of large inputs, such as financial filings, legal contracts, technical reports without requiring retrieval-augmented generation (RAG) pipelines or external chunking systems.

---

## Model Summary

| Attribute | Description |
|---------|-------------|
| **Architecture** | Mistral-based decoder-only transformer |
| **Parameters** | ~12B |
| **Layers** | 40 |
| **Hidden Size** | 5,120 |
| **Context Window** | 131,072 tokens |
| **Vocabulary Size** | 131,072 |
| **Precision** | bfloat16 (BF16) |
| **License** | Apache License 2.0 |

---

## Model Highlights

- **Extended Context:** Native support for 131k-token sequences using RoPE (theta: 1,000,000)
- **Efficient Attention:** Grouped Query Attention (32 attention heads, 8 KV heads)
- **Broad Coverage:** Large vocabulary supporting multilingual, technical, and domain-specific text
- **Deployment-Friendly:** Optimized for mid-range GPUs such as NVIDIA A10G
- **Long-Form Reasoning:** Particularly effective on large-document and multi-step reasoning tasks

---

## Performance & Benchmarks

| Benchmark | Score |
|---------|-------|
| **MMLU** | 68 |
| **MMLU-Pro** | 39 |
| **ARC-Challenge** | 60 |

### Inference Performance (NVIDIA A10G)

- **Time to First Token (TTFT):** ~80 ms  
- **Throughput:** ~146 tokens/sec  
- **Precision:** bfloat16 (BF16)

Benchmark results are indicative and may vary depending on hardware, prompt length, and configuration.

---

## Intended Use & Scope

Charlie 1.5 is intended for:
- Long-context document analysis
- Enterprise decision-support systems
- Research and experimentation
- Commercial and non-commercial applications
- Fine-tuning and derivative model development

The model is provided as-is and should be independently evaluated before use in high-risk or safety-critical applications.

---

## Usage

Charlie 1.5 can be used with the Hugging Face `transformers` library:

```python
import torch
from transformers import pipeline

pipe = pipeline(
    "text-generation",
    model="your-username/charlie-1.5",
    torch_dtype=torch.bfloat16,
    device_map="auto"
)

prompt = """
Analyze the impact of a 15% tariff increase on lithium-ion components from the Asia-Pacific region. 

1. Identify the top 3 Tier 2 suppliers most at risk based on current lead times.
2. Propose a diversification strategy for our European assembly plant.
3. Calculate the projected shift in COGS if we pivot 40% of sourcing to Mexico.
"""
messages = [
     {"role": "system", "content": ""},
     {"role": "user", "content": prompt},
]

outputs = pipe(messages,
              max_new_tokens=512,
              do_sample=True,
              temperature=0.1,
              use_cache=True,
              return_full_text=False,
              num_return_sequences=1
              )
for output in outputs:
    print(output['generated_text'])
```

## Technical Specifications

- Hidden Size: 5,120
- Intermediate Size: 14,336
- Attention Heads: 32 (8 KV heads using Grouped Query Attention)
- Activation Function: SiLU
- Normalization: RMSNorm (epsilon: 1e-05)
- Max Position Embeddings: 131,072

## License

The model is released freely and without restriction under the Apache License 2.0. There are no restrictions on downstream usage beyond those stated in the license.

## Citation & Attribution

If you use Charlie 1.5 in research or commercial applications, please attribute it to the original Gaudium AI development team.