# Dynavera Benchmark Results

**Date:** 2026-03-24 13:29:55  
**Inference endpoint:** `http://fyp-inference-dev:8001`  
**Repetitions per benchmark:** 10  

## 1. GPU Server Health

| Field | Value |
|---|---|
| Status | OK |
| LLM Ready | True |
| Embed Ready | True |
| Health check RTT | 44.5 ms |

## 2. Embedding Latency

| Query type | Chars | Mean (ms) | Median (ms) | P95 (ms) | Min (ms) | Max (ms) |
|---|---|---|---|---|---|---|
| short | 19 | 25.0 | 25.3 | 31.9 | 20.8 | 31.9 |
| medium | 172 | 24.0 | 22.8 | 31.8 | 21.0 | 31.8 |
| long | 428 | 29.8 | 27.5 | 37.7 | 25.0 | 37.7 |

## 3. Semantic Chunking Latency

| Input size | Chars | Chunks produced | Latency (ms) |
|---|---|---|---|
| small  (~200 c) | 200 | 1 | 26.7 |
| medium (~2k c) | 1810 | 1 | 62.7 |
| large  (~8k c) | 7740 | 1 | 204.0 |

## 4. LLM Inference Latency

| Prompt type | Elapsed (s) | Prompt tokens | Completion tokens | Tok/s |
|---|---|---|---|---|
| short_qa | 1.26 | 55 | 69 | 54.9 |
| progress_summary | 1.24 | 74 | 68 | 54.9 |
| curriculum_gen | 1.4 | 79 | 76 | 54.4 |
| assessment_gen | 4.75 | 83 | 249 | 52.4 |
| knowledge_explanation | 10.34 | 83 | 541 | 52.3 |

> **Note on end-to-end session time:** A full onboarding session invokes multiple sequential
> inference calls (curriculum generation → knowledge explanation × N modules → assessment generation → progress summary).
> Total wall-clock time accumulates across all turns plus retrieval and tool-call overhead.

## 5. Database Statistics

| Entity | Count |
|---|---|
| Organizations | 3 |
| Roles | 10 |
| Users | 12 |
| Training Files (total) | 1 |
| Training Files (embedded) | 0 |
| Knowledge Chunks (with embeddings) | 8 |
| Onboarding Sessions | 4 |

## 6. pgvector Retrieval Latency

**Role:** fNIRS Specialist  
**Organisation:** University of Birmingham  
**Query:** "What are the key responsibilities, tools, and procedures for this role?"  
**Total chunks in DB:** 8  

| Top-K | Results returned | Mean (ms) | Median (ms) | P95 (ms) | Min (ms) | Max (ms) |
|---|---|---|---|---|---|---|
| top_5 | 5 | 2.3 | 2.0 | 5.0 | 1.9 | 5.0 |
| top_10 | 8 | 2.4 | 2.4 | 3.1 | 2.3 | 3.1 |
| top_20 | 8 | 2.3 | 2.3 | 2.6 | 2.2 | 2.6 |

## Raw JSON

```json
{
  "health": {
    "status": "OK",
    "llm_ready": true,
    "embed_ready": true,
    "latency_ms": 44.5
  },
  "embeddings": {
    "short": {
      "query_chars": 19,
      "mean_ms": 25.0,
      "median_ms": 25.3,
      "p95_ms": 31.9,
      "min_ms": 20.8,
      "max_ms": 31.9
    },
    "medium": {
      "query_chars": 172,
      "mean_ms": 24.0,
      "median_ms": 22.8,
      "p95_ms": 31.8,
      "min_ms": 21.0,
      "max_ms": 31.8
    },
    "long": {
      "query_chars": 428,
      "mean_ms": 29.8,
      "median_ms": 27.5,
      "p95_ms": 37.7,
      "min_ms": 25.0,
      "max_ms": 37.7
    }
  },
  "chunking": {
    "small  (~200 c)": {
      "chars": 200,
      "chunks_produced": 1,
      "latency_ms": 26.7
    },
    "medium (~2k c)": {
      "chars": 1810,
      "chunks_produced": 1,
      "latency_ms": 62.7
    },
    "large  (~8k c)": {
      "chars": 7740,
      "chunks_produced": 1,
      "latency_ms": 204.0
    }
  },
  "llm": {
    "short_qa": {
      "elapsed_s": 1.26,
      "prompt_tokens": 55,
      "completion_tokens": 69,
      "tokens_per_sec": 54.9,
      "response_preview": "A Kubernetes pod is the basic execution unit of a containerized application, and it represents a log"
    },
    "progress_summary": {
      "elapsed_s": 1.24,
      "prompt_tokens": 74,
      "completion_tokens": 68,
      "tokens_per_sec": 54.9,
      "response_preview": "The trainee has demonstrated a strong foundation in the fundamentals of version control with Git, as"
    },
    "curriculum_gen": {
      "elapsed_s": 1.4,
      "prompt_tokens": 79,
      "completion_tokens": 76,
      "tokens_per_sec": 54.4,
      "response_preview": "[   \"Module 1: Introduction to Backend Services\",   \"Module 2: Fundamentals of API Design\",   \"Modul"
    },
    "assessment_gen": {
      "elapsed_s": 4.75,
      "prompt_tokens": 83,
      "completion_tokens": 249,
      "tokens_per_sec": 52.4,
      "response_preview": "[   {     \"question\": \"What is the primary purpose of a Continuous Integration (CI) pipeline?\",     "
    },
    "knowledge_explanation": {
      "elapsed_s": 10.34,
      "prompt_tokens": 83,
      "completion_tokens": 541,
      "tokens_per_sec": 52.3,
      "response_preview": "**Git Branching Strategy Best Practices**  As a new engineer, understanding Git branching strategies"
    }
  },
  "database": {
    "organizations": 3,
    "roles": 10,
    "users": 12,
    "training_files_total": 1,
    "training_files_embedded": 0,
    "knowledge_chunks_with_embeddings": 8,
    "onboarding_sessions": 4
  },
  "retrieval": {
    "role": "fNIRS Specialist",
    "organization": "University of Birmingham",
    "query": "What are the key responsibilities, tools, and procedures for this role?",
    "total_chunks_in_db": 8,
    "results": {
      "top_5": {
        "results_returned": 5,
        "mean_ms": 2.3,
        "median_ms": 2.0,
        "p95_ms": 5.0,
        "min_ms": 1.9,
        "max_ms": 5.0
      },
      "top_10": {
        "results_returned": 8,
        "mean_ms": 2.4,
        "median_ms": 2.4,
        "p95_ms": 3.1,
        "min_ms": 2.3,
        "max_ms": 3.1
      },
      "top_20": {
        "results_returned": 8,
        "mean_ms": 2.3,
        "median_ms": 2.3,
        "p95_ms": 2.6,
        "min_ms": 2.2,
        "max_ms": 2.6
      }
    }
  }
}
```