Enterprise Local LLM: RTX 6000 Capabilities & Custom Training
Dual RTX Pro 6000 Specs
- VRAM: 96GB each (192GB total)
- Memory Bandwidth: 960 GB/s
- CUDA Cores: 18,176
- Target: Enterprise AI workloads
Model Capabilities with 192GB VRAM
| Model | VRAM | Fits? | Tokens/sec |
|---|---|---|---|
| Llama 70B Q4 | ~40GB | Single GPU | 30-50 |
| Llama 70B Q8 | ~75GB | Single GPU | 25-40 |
| Llama 70B FP16 | ~140GB | Dual GPU | 15-25 |
| Llama 405B Q4 | ~200GB | Tight fit | 5-10 |
| Multiple 70B simultaneously | - | Yes | - |
Training Capabilities
| Task | 96GB | 192GB |
|---|---|---|
| Fine-tune 7B full | Easy | Easy |
| Fine-tune 13B full | Yes | Easy |
| Fine-tune 70B LoRA | Yes | Easy |
| Fine-tune 70B full | Tight | Yes |
Custom Training: Making a Coder BETTER
What Training Adds (LoRA Adapter)
Base model stays unchanged. You add a small adapter (~100-500MB) that teaches:
- YOUR codebase patterns
- YOUR naming conventions
- YOUR preferred libraries
- YOUR error handling style
- Company coding standards
- Project-specific knowledge
Training Data for Corlera/Nexus
- All 18 MCP server source files
- Example tool implementations
- Redis patterns (Track Pattern, Quadfecta)
- Documentation and docstrings
- Bug fix examples (before/after)
- Good conversation examples
Result: Expert at YOUR Code
Before training: - Generic MCP structure - Guesses at patterns - May conflict with your style
After training: - Uses YOUR exact patterns - Knows Nexus architecture - Production-ready output - Matches your style perfectly
Is It BETTER Than Base Model?
For generic coding: Same For YOUR codebase: Significantly better
The trained model becomes an expert at Nexus-specific work.
KV Cache Clarification
What's Stored
- Input tokens (your question)
- Output tokens (model response)
- ALL conversation history
- Cumulative across turns
Multi-GPU KV Cache
- NOT "overflow when full"
- Layer-based split
- Each GPU handles its layers + their KV cache
- Plan model size accordingly
Production Setup Vision
Threadripper 64-core
128GB System RAM
Dual RTX Pro 6000 (192GB VRAM)
Qwen Coder 32B + Nexus LoRA
= Coding assistant that knows your entire
codebase and matches your style exactly
Last updated: 2025-12-08 Session: s_801t