Real workloads,real results.
Coding agents and document search are the two most popular AI workloads in the enterprise today. Score is not limited to them: any application or agent that speaks the OpenAI-compatible API runs the same way.
Coding agents that work across your whole codebase, for the whole team.
Handle more users on the same coding workload, across the whole team, without adding hardware.
- Cursor
- OpenCode
- Claude Code
- Pi
Coding agent: Gemma 4-31B on Gen6 Xeon vs OpenRouter
Multi-turn coding agent, self-hosted with Score-SDK, against the same model served by a hosted API.
- Model
- Gemma 4-31B
- Hardware
- Gen6 Xeon versus OpenRouter
- Workload
- Multi-turn coding agent, cost comparison
The same day's work, metered two ways
money saved, by 17:00
| Deployment | Cost per day | Cost per year (250 days) |
|---|---|---|
| Frontier-model API | $2,700 | $675,000 |
| Xeon + Score-SDK | $158 | $39,474 |
Search large, confidential documents without sending them anywhere.
Let employees search large, confidential document collections and datasets without sending the data to an external AI service. Score loads the documents once, serves many people at the same time, and runs inside your environment.
3× more concurrent knowledge-search sessions
Six concurrent RAG knowledge-search sessions on Score versus two on the GPU baseline.
- Hardware
- Score on Xeon versus a GPU baseline
- Workload
- Six concurrent knowledge-search sessions
RAG cost: self-hosted gpt-oss-120B on Gen4 Xeon vs Amazon Bedrock
Direct cost comparison for the same retrieval workload, self-hosted against a hosted API.
- Model
- gpt-oss-120B
- Hardware
- Gen4 Xeon versus Amazon Bedrock
- Workload
- Retrieval-augmented generation, cost comparison
Not limited to these.
The same software, the same endpoint, the same economics for other applications and agents.
Private and regulated AI
Run AI on sensitive data without sending prompts, records or documents outside your environment.
Data centers and AI infrastructure
More tokens per dollar and per watt from the CPU and GPU nodes you already rack.
Any OpenAI-compatible application or agent
Internal tools, batch jobs, support assistants, custom agent loops. If it speaks the OpenAI-compatible API, it runs on Score unchanged.
Benchmark your workload.
Send us a real workload. We run it on your models, your context lengths and your concurrency, and hand you the numbers either way.