Same task.
10× faster. 7× richer.
We ran the same complex tasks on Army AI and ChatGPT Plus. Here are the real results — unedited, timed, side by side.
Inference speed — tokens/second
Army AI uses Groq LPU + Cerebras WSE-3 hardware — purpose-built for AI inference, not general GPU.
Sources: Groq published benchmarks · Cerebras published benchmarks · OpenAI / Anthropic / Google public API measurements · Speeds may vary by model and load.
Head-to-head: 4 real tasks
Task #1
“Write a go-to-market strategy for a B2B SaaS targeting HR managers”
- ✓Architect planned 5 subtasks
- ✓Researcher gathered 8 market data points
- ✓Implementator wrote full 1,200-word strategy
- ✓Verificator caught 3 inconsistencies
- ✓Optimizer tightened language by 18%
Single response, 600 words, no cross-verification
Task #2
“Analyze the competitive landscape for a fintech startup launching in Europe”
- ✓Architect structured: players / trends / gaps / threats / opportunities
- ✓Researcher identified 12 competitors
- ✓Implementator produced full 1,800-word analysis
- ✓Verificator corrected 2 outdated facts
- ✓Optimizer added executive summary
Single response, 750 words, one perspective
Task #3
“Review an NDA for unusual IP clauses and one-sided indemnification”
- ✓Architect split into: IP / liability / termination / governing law
- ✓Researcher surfaced standard NDA benchmarks
- ✓Implementator flagged 4 risk clauses
- ✓Verificator confirmed legal accuracy
- ✓Optimizer wrote client-ready summary
Single response, general NDA advice, no structured risk list
Task #4
“Create a 30-day LinkedIn content calendar for a cybersecurity startup”
- ✓Architect created weekly themes
- ✓Researcher found trending cybersecurity topics
- ✓Implementator wrote 30 post ideas with hooks
- ✓Verificator ensured variety and consistency
- ✓Optimizer added CTAs and engagement tactics
Single response, 15 generic post ideas
Why is Army AI faster?
1. Hardware purpose-built for AI
Groq LPU and Cerebras WSE-3 are not general-purpose GPUs. They process tokens 10-15× faster than the hardware running ChatGPT/Claude.
2. Parallelism — 7 agents at once
While ChatGPT generates one sequential response, Army dispatches 7 agents simultaneously. Total wall-clock time = time of the slowest agent, not sum of all.
3. No waiting for full response
SSE streaming shows results as they arrive. You see the Researcher's findings while the Optimizer is still running — not after everything completes.
4. Specialized agents = less hallucination
The Verificator explicitly checks the Implementator's output for errors. One model doing everything introduces more failure points than 7 specialized ones.
Try it yourself — free
50 tasks/month free. No credit card. Run the same task on Army AI and compare yourself.
Benchmark methodology: tasks were submitted to ChatGPT-4o (Plus plan) and Army AI within the same 24h window. Times measured from submission to full response. Results are representative; actual performance may vary. · ← Back to armyai.app