Next generation AI compute optimization
Next generation AI compute optimization
Next generation
AI compute optimization
Inceptron accelerates LLM, CV, and NLP models and brings operational simplicity to your AI deployments. Unlocking top performance for AI with powerful model compression, acceleration, and a scalable, production-ready runtime.
Upload
your model
Upload your custom
or open source model
Optimize
Optimize based on your
verification benchmarks
Optimize based
on your verification benchmarks
Download
and Deploy
Download your optimized
model and runtime
Download
your optimized
model and runtime
A leading
contributor
to TVM
A leading contributor to TVM
Inceptron is a unique company consisting of machine learning, compiler, and high performance computing experts. We live in the details, with our inference optimizations taking us deep into the instruction-level details across a wide range of compute architectures. As machine learning model optimization experts, we can further increase inference performance through our cutting edge model optimization techniques.
20 User TPS
Input tokens: 7000Output tokens: 600
VLLM, Llama 3.1 70b, HW: 2xH100
40 User TPS
Input tokens: 7000
Output tokens: 600
INCEPTRON, Llama 3.1 70b, HW: 2xH100
20 User TPS
Input tokens: 7000Output tokens: 600
VLLM, Llama 3.1 70b, HW: 2xH100
80 User TPS
Input tokens: 7000
Output tokens: 600
Accuracy is kept within 2% of original model at the selected benchmarks:
1. ARC-C, zero shot;
2. GSM8K, 8 shots;
3. MMLU CoT (Chain of Thought), zero shot;
4. SQUAD, zero shot;
INCEPTRON 2%, Llama 3.1 70b, HW: 2xH100
20 User TPS
Input tokens: 7000Output tokens: 600
VLLM, Llama 3.1 70b, HW: 2xH100
40 User TPS
Input tokens: 7000
Output tokens: 600
INCEPTRON, Llama 3.1 70b, HW: 2xH100
20 User TPS
Input tokens: 7000Output tokens: 600
VLLM, Llama 3.1 70b, HW: 2xH100
80 User TPS
Input tokens: 7000
Output tokens: 600
Accuracy is kept within 2% of original model at the selected benchmarks:
1. ARC-C, zero shot;
2. GSM8K, 8 shots;
3. MMLU CoT (Chain of Thought), zero shot;
4. SQUAD, zero shot;
INCEPTRON 2%, Llama 3.1 70b, HW: 2xH100
20 User TPS
Input tokens: 7000Output tokens: 600
VLLM, Llama 3.1 70b, HW: 2xH100
40 User TPS
Input tokens: 7000
Output tokens: 600
INCEPTRON, Llama 3.1 70b, HW: 2xH100
20 User TPS
Input tokens: 7000Output tokens: 600
VLLM, Llama 3.1 70b, HW: 2xH100
80 User TPS
Input tokens: 7000
Output tokens: 600
Accuracy is kept within 2% of original model at the selected benchmarks:
1. ARC-C, zero shot;
2. GSM8K, 8 shots;
3. MMLU CoT (Chain of Thought), zero shot;
4. SQUAD, zero shot;
INCEPTRON 2%, Llama 3.1 70b, HW: 2xH100
20 User TPS
Input tokens: 7000Output tokens: 600
VLLM, Llama 3.1 70b, HW: 2xH100
40 User TPS
Input tokens: 7000
Output tokens: 600
INCEPTRON, Llama 3.1 70b, HW: 2xH100
20 User TPS
Input tokens: 7000Output tokens: 600
VLLM, Llama 3.1 70b, HW: 2xH100
80 User TPS
Input tokens: 7000
Output tokens: 600
Accuracy is kept within 2% of original model at the selected benchmarks:
1. ARC-C, zero shot;
2. GSM8K, 8 shots;
3. MMLU CoT (Chain of Thought), zero shot;
4. SQUAD, zero shot;
INCEPTRON 2%, Llama 3.1 70b, HW: 2xH100
IT teams can now deploy custom or open source models in production without worrying about inference optimization, enabling cost-efficient and rapid AI deployment with confidence.
A leading contributor
to TVM
Inceptron is a unique company consisting of machine learning, compiler, and high performance computing experts. We live in the details, with our inference optimizations taking us deep into the instruction-level details across a wide range of compute architectures. As machine learning model optimization experts, we can further increase inference performance through our cutting edge model optimization techniques.
20 User TPS
Input tokens: 7000Output tokens: 600
VLLM, Llama 3.1 70b, HW: 2xH100
40 User TPS
Input tokens: 7000
Output tokens: 600
INCEPTRON, Llama 3.1 70b, HW: 2xH100
20 User TPS
Input tokens: 7000Output tokens: 600
VLLM, Llama 3.1 70b, HW: 2xH100
80 User TPS
Input tokens: 7000
Output tokens: 600
Accuracy is kept within 2% of original model at the selected benchmarks:
1. ARC-C, zero shot;
2. GSM8K, 8 shots;
3. MMLU CoT (Chain of Thought), zero shot;
4. SQUAD, zero shot;
INCEPTRON 2%, Llama 3.1 70b, HW: 2xH100
20 User TPS
Input tokens: 7000Output tokens: 600
VLLM, Llama 3.1 70b, HW: 2xH100
40 User TPS
Input tokens: 7000
Output tokens: 600
INCEPTRON, Llama 3.1 70b, HW: 2xH100
20 User TPS
Input tokens: 7000Output tokens: 600
VLLM, Llama 3.1 70b, HW: 2xH100
80 User TPS
Input tokens: 7000
Output tokens: 600
Accuracy is kept within 2% of original model at the selected benchmarks:
1. ARC-C, zero shot;
2. GSM8K, 8 shots;
3. MMLU CoT (Chain of Thought), zero shot;
4. SQUAD, zero shot;
INCEPTRON 2%, Llama 3.1 70b, HW: 2xH100
20 User TPS
Input tokens: 7000Output tokens: 600
VLLM, Llama 3.1 70b, HW: 2xH100
40 User TPS
Input tokens: 7000
Output tokens: 600
INCEPTRON, Llama 3.1 70b, HW: 2xH100
20 User TPS
Input tokens: 7000Output tokens: 600
VLLM, Llama 3.1 70b, HW: 2xH100
80 User TPS
Input tokens: 7000
Output tokens: 600
Accuracy is kept within 2% of original model at the selected benchmarks:
1. ARC-C, zero shot;
2. GSM8K, 8 shots;
3. MMLU CoT (Chain of Thought), zero shot;
4. SQUAD, zero shot;
INCEPTRON 2%, Llama 3.1 70b, HW: 2xH100
20 User TPS
Input tokens: 7000Output tokens: 600
VLLM, Llama 3.1 70b, HW: 2xH100
40 User TPS
Input tokens: 7000
Output tokens: 600
INCEPTRON, Llama 3.1 70b, HW: 2xH100
20 User TPS
Input tokens: 7000Output tokens: 600
VLLM, Llama 3.1 70b, HW: 2xH100
80 User TPS
Input tokens: 7000
Output tokens: 600
Accuracy is kept within 2% of original model at the selected benchmarks:
1. ARC-C, zero shot;
2. GSM8K, 8 shots;
3. MMLU CoT (Chain of Thought), zero shot;
4. SQUAD, zero shot;
INCEPTRON 2%, Llama 3.1 70b, HW: 2xH100
IT teams can now deploy custom or open source models in production without worrying about inference optimization, enabling cost-efficient and rapid AI deployment with confidence.
One stop for any optimization needs:
One stop for any optimization needs:
LLMs
LLM inference at scale is pricey and hard to tune-Inceptron makes it faster and cheaper.
See more
LLMs
LLM inference at scale is pricey and hard to tune-Inceptron makes it faster and cheaper.
See more
LLMs
LLM inference at scale is pricey and hard to tune-Inceptron makes it faster and cheaper.
See more
Computer vision
Computer-vision workloads run faster and cheaper with Inceptron.
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Computer vision
Computer-vision workloads run faster and cheaper with Inceptron.
See more
Computer vision
Computer-vision workloads run faster and cheaper with Inceptron.
See more
How it works
How it works
Bring your TensorFlow, PyTorch, or ONNX model and say whether you need bit-perfect accuracy or maximum speed. Our compiler then runs through 40-plus optimisation passes—trimming memory traffic, filling tensor cores, and more—to craft a build uniquely tuned to your use cases and available hardware. You get back a deployment-ready Docker image.
Let’s Talk
Drop us a message and we will get back
to you as soon as possible!
