Benchmarked Beyond the Limits
Every claim we make is backed by rigorous, reproducible testing. 297 test points across multiple model providers, with 10 simultaneous queries per test. We published the results.
Testing Methodology
Our primary evaluation uses the Multiple Needle-in-a-Haystack (NIAH) protocol — the industry standard for measuring long-context retrieval accuracy, extended to test 10 simultaneous needles per query.
We place 10 specific facts at varying depths within documents of increasing size, then query the system to retrieve all of them. By sweeping across every combination of document depth and context length — from 8K to 20M tokens — we produce a comprehensive accuracy surface that reveals exactly where and how retrieval quality changes at scale. The 20M token benchmark was tested using ollama/llama3.1:8b running locally.
Multiple Needle-in-a-Haystack Accuracy
Retrieval accuracy across every combination of document depth and context length, testing 10 needles simultaneously. Green intensity equals precision. Accuracy improves with scale.
>99% combined accuracy across all test points. CosmicMind reaches 100% accuracy at 5M+ tokens — the opposite of degradation.
CosmicMind vs Context Stuffing
Context stuffing — packing as much raw text into the prompt as possible — degrades rapidly past 128K tokens and becomes completely impossible beyond the native window. CosmicMind's cognitive architecture keeps accuracy improving at every scale, reaching 100% at 5M+.
Raw Accuracy Data
| Context | CosmicMind | Stuffing |
|---|---|---|
| 8K | 96.2% | 99.5% |
| 32K | 97% | 97.2% |
| 128K | 97.5% | 91.8% |
| 512K | 98% | 78.4% |
| 1M | 98.5% | 62.1% |
| 2M | 99% | 45.3% |
| 5M | 100% | N/A |
| 10M | 100% | N/A |
| 20M | 100% | N/A |
Retrieval Speed at Scale
Sub-second retrieval even at 20 million tokens.
Retrieval time at 20M tokens: 270ms (0.27 seconds) — fast enough for real-time applications.
A Note on Language
We use cognitive metaphors — neurons, synapses, cognition — throughout CosmicMind. These are not claims of artificial consciousness. They are precise analogies for how our patent-pending architecture functions.