APMIC CaiGunn Model

CaiGunn 34BCaiGunn 34Bx2 (Coming soon)
Training architectureAPMIC APMIC Brainformers + LlamaMamba + Transformer + MoDE
Computing architectureNeMo FrameworkANF
Hardware requirements
  • Recommended GPU VRAM needs to exceed 70G
  • Compatible with GPUs of A100, H100, H200, B100 and above
  • Recommended GPU VRAM needs to exceed 80G~140GB
  • Compatible with GPUs of A100, H100, H200, B100 and above
Features
  • checkSupport English and Chinese
  • checkCan run locally
  • check4K Context window
  • checkCan be fine-tuned with the CaiGunn platform
  • checkMMLU score higher than GPT 3.5
  • checkSupports English and Chinese
  • checkCan run locally
  • check8K Context window
  • checkCan be fine-tuned with the CaiGunn platform
Download ModelFree Trial

Cost halved, with no compromise on performance

  • checkAfter completing Imitation Learning for APMIC, the inference cost can be reduced by over 50%.
  • checkOutperforms well-known models in Chinese and English according to specific evaluation criteria.
  • checkSupports domain-specific fine-tuning via the CaiGunn platform.

MMLU Rankings (English)

Company NameModelScore
OpenAIGPT-4Not deployable86.5
APMICCaiGunn75.7
GoogleGemini ProNot deployable71.8
Mistral AIMixtral-8x7B71.4
OpenAIGPT-3.5Not deployable70.0
MetaLLaMA 65B68.9
GoogleGemma 7B64.6

TMMLU+ Rankings (Traditional Chinese)

Company NameModelScore
OpenAIGPT-4Not deployable60.40
APMICCaiGunn-zh55.20
Media TekBreeze-7B40.35
Mistral AIMixtral-8x7B36.93
NTUTaiwan-LLM-13B21.36
InnoluxBailong-instruct-7B6.80

Capable of Handling 21 Times the Data of OpenAI

Input Data Volume Capable of Processing at the Same Cost

Company NameModelTokens
APMICCaiGunn21.4x
GoogleGemini12.0x
OpenAIGPT3.5-Turbo1x

Output Data Volume Capable of Processing at the Same Cost

Company NameModelTokens
APMICCaiGunn8.7x
GoogleGemini5.3x
OpenAIGPT3.5-Turbo1x

Flexible Free Deployment

Instant Cloud Usage

Instantly use well-known large language models through CaiGunn. The platform includes built-in automatic text preprocessing, RAG, image-text output, version control, model testing, preview, deployment, and more. It also supports custom model training, fine-tuning, and inference in the cloud, allowing you to have your own models in the cloud.

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Enterprise On-Premises Usage

CaiGunn's enterprise version offers powerful features, supporting not only NVIDIA DGX and HGX hardware but also hybrid and private cloud architectures, including AWS, Azure, Google, Oracle Cloud, DGX Cloud, and other cloud providers, ensuring data privacy and protection.

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Developer Zone

CaiGunn's models are currently deployed in Taiwan. We provide users with model usage through the CaiGunn API, enabling not only No-Code usage but also secondary development.

Low Inference Cost

After fine-tuning, models trained in specific domains can provide lower inference costs.

Support for Application Scenarios

Language models are just the core. We can support more application systems launched by APMIC, such as customer service, knowledge management, contract recognition, etc.

Data Confidentiality

With NVIDIA H100 or higher-level Confidential Computing technology, data can be kept confidential from training to deployment.

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