**SPEED-1** is a Mixture-of-Experts (MoE) language model with ~19B parameters, built by SKT AI LABS Private Limited, an Indian AI company based in Sidhi, Madhya Pradesh. It is designed for complex tasks across a wide range, trained for complex reasoning, with chain-of-thought data spanning agentic tasks, mathematics, and coding.
---
## Evaluation Results
Early results from ongoing development (October 2026, evaluated on AMD MI300X). Detailed eval configuration will be published with the full release.
Benchmark
SPEED-1
Reasoning & Knowledge
HMMT (Feb 26)
49.0
HMMT (Nov 25)
45.0
MMMLU
56.0
MMLU-Pro
67.0
GPQA Diamond
56.0
Instruction Following & Agents
IFEval
64.8
IFBench
24.0
---
## Reasoning
Reasoning (thinking traces) is supported via the chat template. Extended reasoning evaluations are pending the full release.
---
## Usage
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
# Load model and tokenizer (trust_remote_code needed for the custom class)
tokenizer = AutoTokenizer.from_pretrained("sKT-Ai-Labs/SPEED-1", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(
"sKT-Ai-Labs/SPEED-1",
torch_dtype=torch.bfloat16,
device_map="auto",
trust_remote_code=True,
)
# Apply the model's chat template (SPEED uses ### User: / ### Assistant:)
messages = [{"role": "user", "content": "Create a Python CLI tool using docker-py that manages Docker containers. I need a watch command that listens to the Docker events stream and triggers a callback whenever a container dies with a non-zero exit code."}]
inputs = tokenizer.apply_chat_template(messages, add_generation_prompt=True,
return_tensors="pt").to("cuda") if torch.cuda.is_available() else \
tokenizer.apply_chat_template(messages, add_generation_prompt=True, return_tensors="pt")
# Generate (give it room to reason before it answers)
outputs = model.generate(**inputs, max_new_tokens=2048, temperature=0.6, top_p=0.9)
result = tokenizer.decode(outputs[0][inputs["input_ids"].shape[1]:], skip_special_tokens=True)
print(result)
```
> **Note:** SPEED reasons inside tags before answering — keep
> `max_new_tokens` high (≥1024) or the reply is cut off mid-thought.
---
## Citation
```bibtex
@misc{SPEED-1,
author = {SKT AI LABS, India},
title = {SPEED-1: Indic-first multilingual Mixture-of-Experts model},
year = {2026},
publisher = {SKT AI LABS},
url = {https://huggingface.co/sKT-Ai-Labs/SPEED-1}
}
```
