⚖️ Model Comparison
Free vs Paid AI Models for Cybersecurity
Practical benchmarks across 10 security tasks with India-specific test inputs. Which free model can replace paid AI — and when does paid actually matter?
Security Task Performance — Rated 1-5
Ratings based on testing with India-specific inputs: Indian regulatory references, Indian APT actors (Sidewinder, APT36), CERT-In terminology, and Indian BFSI log formats. Results are subjective assessments — your mileage may vary.
| Security Task | Llama 3.2 8B Free (Groq/Ollama) |
Llama 3.1 70B Free (Groq limited) |
Mistral 7B Free (Mistral.ai) |
Phi-3.5 Mini Free (Ollama local) |
Gemini Flash Free (AI Studio) |
GPT-4o Paid ($20/mo) |
Claude Sonnet Paid ($20/mo) |
|
|---|---|---|---|---|---|---|---|---|
| Windows event log triage | ★★★★★ 4/5 | ★★★★★ 5/5 | ★★★★★ 4/5 | ★★★★★ 3/5 | ★★★★★ 4/5 | ★★★★★ 5/5 | ★★★★★ 5/5 | Llama 70B matches paid for structured log analysis |
| SIEM alert classification | ★★★★★ 4/5 | ★★★★★ 5/5 | ★★★★★ 4/5 | ★★★★★ 3/5 | ★★★★★ 4/5 | ★★★★★ 5/5 | ★★★★★ 5/5 | Strong free options — 70B competitive with paid |
| KQL / SPL rule writing | ★★★★★ 3/5 | ★★★★★ 4/5 | ★★★★★ 3/5 | ★★★★★ 2/5 | ★★★★★ 4/5 | ★★★★★ 5/5 | ★★★★★ 5/5 | Paid models produce fewer hallucinated field names |
| Sigma rule generation | ★★★★★ 3/5 | ★★★★★ 4/5 | ★★★★★ 4/5 | ★★★★★ 2/5 | ★★★★★ 3/5 | ★★★★★ 5/5 | ★★★★★ 5/5 | Mistral 7B surprisingly good for Sigma. Paid better. |
| Threat report summarisation | ★★★★★ 3/5 | ★★★★★ 4/5 | ★★★★★ 3/5 | ★★★★★ 2/5 | ★★★★★ 5/5 | ★★★★★ 5/5 | ★★★★★ 5/5 | Gemini Flash excellent — long context handles full reports |
| CERT-In regulatory context | ★★★★★ 2/5 | ★★★★★ 3/5 | ★★★★★ 2/5 | ★★★★★ 2/5 | ★★★★★ 3/5 | ★★★★★ 4/5 | ★★★★★ 4/5 | Gap is real — free models have less India regulatory depth |
| Security policy drafting | ★★★★★ 3/5 | ★★★★★ 5/5 | ★★★★★ 4/5 | ★★★★★ 2/5 | ★★★★★ 4/5 | ★★★★★ 5/5 | ★★★★★ 5/5 | Llama 70B competitive. Shorter policies are fine with 8B. |
| IOC extraction from text | ★★★★★ 4/5 | ★★★★★ 5/5 | ★★★★★ 4/5 | ★★★★★ 3/5 | ★★★★★ 4/5 | ★★★★★ 5/5 | ★★★★★ 5/5 | Near-parity — all models handle IOC extraction well |
| Executive incident briefing | ★★★★★ 4/5 | ★★★★★ 5/5 | ★★★★★ 4/5 | ★★★★★ 3/5 | ★★★★★ 5/5 | ★★★★★ 5/5 | ★★★★★ 5/5 | Free models good enough for most briefings |
| Complex multi-step investigation | ★★★★★ 2/5 | ★★★★★ 4/5 | ★★★★★ 3/5 | ★★★★★ 2/5 | ★★★★★ 3/5 | ★★★★★ 5/5 | ★★★★★ 5/5 | Paid models significantly better for complex reasoning chains |
| Average | 3.2/5 | 4.4/5 | 3.5/5 | 2.4/5 | 3.9/5 | 4.9/5 | 4.9/5 |
Task-by-Task Analysis — When Free is Good Enough
| Task | Free Model Verdict | Best Free Choice | When to Use Paid |
|---|---|---|---|
| Log triage (Windows/Linux/Cloud) | Free is good enough | Llama 3.2 8B via Groq | Only if you need real-time streaming or handling extremely complex multi-stage attack sequences |
| SIEM rule writing (KQL/SPL) | Free mostly sufficient — verify output | Llama 3.1 70B | When writing rules for production Sentinel/Splunk — paid models hallucinate field names less |
| CERT-In regulatory guidance | Free has gaps — use with caution | Gemini Flash | When regulatory accuracy matters (compliance docs, board reporting) — supplement with human expert review |
| Threat report summarisation | Free is excellent | Gemini Flash (long context) | Almost never — Gemini Flash free tier handles full reports as well as paid models |
| Security policy drafting | Llama 70B matches paid | Llama 3.1 70B via Groq | Only for very complex multi-regulation policies requiring deep India-specific legal accuracy |
| Incident executive briefing | Free is good enough | Llama 3.2 8B or Gemini Flash | Rarely — free models communicate clearly for management briefings |
| Complex investigation reasoning | Free falls short | Llama 3.1 70B (best free option) | Yes — for complex multi-step attack path analysis, paid models are meaningfully better |
| IOC extraction from text | Free is excellent — near parity | Any model works well | Never — all free models handle structured IOC extraction from text well |
| Sigma rule generation | Free is adequate | Mistral 7B | When deploying Sigma to production — paid models produce fewer structural errors |
| Policy gap analysis (Indian regs) | Free is limited | Gemini Flash | For formal compliance assessments — Indian regulatory knowledge depth is still better in paid models |
Privacy & Data Sovereignty — Critical for Indian Regulated Entities
| Model / Platform | Data Goes To | Training on Your Data? | RBI/SEBI Compliant? | BFSI Recommendation |
|---|---|---|---|---|
| ChatGPT / GPT-4o | OpenAI servers — USA | No (by default with API) | No — data leaves India | Do not use for payment data, trade data, or customer PII |
| Claude (Anthropic) | Anthropic servers — USA | No (API usage) | No — data leaves India | Do not use for regulated financial data |
| Gemini / Google AI Studio | Google servers — USA/global | May be used for improvement unless opted out | No — data leaves India | Opt out of data usage. Still not for regulated data. |
| Groq (Llama 3) | Groq servers — USA | No (per ToS) | No — data leaves India | Use only for non-sensitive security research and testing |
| Mistral AI | Mistral servers — EU | No (per ToS) | Better but still not India | Marginally better for EU-regulated entities. Not for Indian financial data. |
| HuggingFace Inference API | HuggingFace servers — USA | Potentially — check model card | No — data leaves India | Use only for non-sensitive tasks. Not for regulated data. |
| Ollama (local) | Your own hardware — stays in India | No — model runs offline | Yes — zero egress | Recommended for all regulated Indian entities. No data leaves your network. |
| vLLM (local) | Your own hardware — stays in India | No — model runs offline | Yes — zero egress | Recommended for high-concurrency regulated deployments. |
What data is safe to send to cloud AI?
Safe — any cloud AI
Generic security concepts, publicly known threat actor TTPs, CVE descriptions, generic policy templates, educational questions about attack techniques
Caution — anonymised data only
Log entries with source IPs replaced, alert titles without customer identifiers, general incident descriptions without specific account/user details
Internal/private cloud AI only (MeitY-empanelled)
De-identified security events, internal tool configurations, anonymised vulnerability reports
Local AI (Ollama) only — zero cloud
Customer account data, payment transaction logs, Aadhaar/PAN data, trade data, policyholder information, SWIFT messages, CBS logs
Never send to any AI — human review only
Active exploit code, live attack commands, classified government data, full database dumps, SWIFT operator credentials
Cost Analysis — Free vs Paid for Indian SOC Teams
| Option | Monthly Cost | Requests / Day | Best For |
|---|---|---|---|
| Groq free (Llama 3.2 8B) | ₹0 | 14,400 (8B) / 6,000 (70B) | Individual analyst, light SOC use |
| Google AI Studio (Gemini Flash) | ₹0 | 1,500 | Long-document threat reports, CERT-In advisories |
| Mistral free tier | ₹0 | Rate limited | Structured output, policy drafts |
| Ollama on existing hardware | ₹0 (power cost only) | Unlimited | Teams with GPU — unlimited queries |
| Ollama + GPU workstation (RTX 4090) | ~₹1,200/month (EMI on ₹1.6L setup) | Unlimited | Small team (1-5 analysts). Best cost per query for moderate use. |
| Ollama + team server (A100) | ~₹8,000/month (EMI on ₹35L setup) | Unlimited, 20+ concurrent | Medium team (10-20 analysts). Production BFSI deployment. |
| ChatGPT Plus (GPT-4o) | ₹1,500-2,000/month per user | Limited (conversation rate) | Individual power user needing highest quality |
| Claude Pro | ₹1,500-2,000/month per user | Limited | Individual power user — best for long-form writing |
| OpenAI API (GPT-4o) | Pay per token — ₹0.004/1K tokens input | Unlimited (billed) | Teams wanting GPT-4 quality without per-user subscription |
| Anthropic API (Claude Sonnet) | Pay per token — ₹0.002/1K tokens input | Unlimited (billed) | Teams wanting Claude quality. Powers tools on this site. |
The Verdict — What to Use and When
Individual SOC analyst — no budget
Start here
Start with Groq free tier (Llama 3.2 8B) for daily triage. Add Gemini Flash free for long threat reports. Total cost: ₹0. For regulated Indian entities: install Ollama on your analyst laptop.
Small SOC team (2-10 analysts)
Best value
Deploy Ollama on a shared GPU workstation (RTX 4090, ~₹1.6L one-time). Unlimited queries, all stays on-premise. Install Open WebUI so all analysts use browser-based chat. Total ongoing cost: electricity.
Medium BFSI SOC (10-30 analysts)
Recommended for regulated entities
Dedicated Ollama/vLLM server with NVIDIA A100 or 2x RTX 3090. Llama 3.1 70B for quality-sensitive tasks. Serves 20+ analysts simultaneously. Air-gapped from internet. RBI/SEBI compliant.
Security researchers and red teamers
Mix of free and paid
Groq free tier for fast experimentation. Ollama locally for sensitive engagement data. GPT-4o or Claude for high-complexity tasks where quality justifies cost.
When to pay for AI
Specific scenarios only
Pay for AI when: (1) You need consistent high-quality detection rule writing. (2) Complex multi-step investigation reasoning. (3) Formal compliance documents where accuracy is critical. (4) Your team is small and GPU investment isn't justified.
Never use cloud AI for
Hard rule for regulated entities
Payment logs, trade data, CBS logs, Aadhaar/PAN numbers, SWIFT messages, policyholder data, classified information. Always use local AI (Ollama) for these.