ESMC-6B Zero Config

Docker offers the quickest path to setting up this model locally.

Please follow the instructions listed below to get started.

Then, execute the docker-compose up command to launch the model.

🛡️ Checksum: b7a836f45a3c8a21e7954f53971afaa0 — ⏰ Updated on: 2026-06-21



  • CPU: multi-threading optimized for fast prompt processing
  • RAM: at least 32 GB in dual-channel mode for bandwidth
  • Disk Space: free: 80 GB on system drive for scratch space
  • Graphics: 12 GB VRAM minimum required for basic quantization

ESMC-6B is a 6‑billion parameter language model designed for both conversational AI and code generation.

It leverages a hybrid transformer architecture that combines sparse attention with rotary positional embeddings to achieve faster inference.

The model was trained on a diverse corpus of 1.5 trillion tokens, covering web text, scholarly articles, and open‑source code.

Key specifications include the following details.

Parameters 6 B
Context length 8K tokens
Training data 1.5 T tokens
Inference speed 120 tokens/s on 8×A100

Compared to previous models, ESMC-6B delivers superior performance on benchmarks while maintaining a compact footprint, making it suitable for deployment in resource‑constrained environments.

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