AI security alert triage is cheap at the token layer. The expensive part is sending every noisy SIEM alert, EDR event, firewall hit, and cloud posture finding to a premium model as if it were a breach investigation.
For a standard security alert packet of 6,000 input tokens and 1,000 output tokens, model cost ranges from $0.70 per 1,000 alerts on GPT-5 nano to $360 per 1,000 alerts on GPT-5.5 Pro. That is a 514x spread for the same alert context. At SOC scale, routing matters more than brand preference.
This guide breaks down AI costs for alert triage, incident summaries, escalation notes, and human analyst handoffs. You will get concrete token assumptions, cost-per-alert tables, monthly SOC scenarios, and clear model recommendations for cheap triage, balanced investigation, and premium escalation.
⚠️ Warning: AI can summarize evidence, prioritize queues, draft notes, and prepare analyst handoffs. It should not silently close high-severity alerts, disable controls, or take containment action without your approved detection engineering, audit, and human escalation process.
What an AI SOC workflow actually does
Most SOC teams do not need AI to "be the analyst." They need AI to compress repetitive alert work into structured decisions a human can trust faster.
A practical AI SOC workflow has four model tasks:
| Workflow step | Typical input | Typical output | Main purpose |
|---|---|---|---|
| Alert triage | 3,000 tokens | 500 tokens | Classify severity, explain signal, extract entities, recommend queue |
| Enriched alert review | 8,000 tokens | 1,200 tokens | Add asset context, related events, threat intel, and confidence |
| Incident summary | 16,000 tokens | 2,500 tokens | Summarize timelines, evidence, affected systems, and current status |
| Analyst handoff | 24,000 tokens | 3,000 tokens | Prepare a reviewer-ready case packet with next actions |
The standard alert packet in this article uses 6,000 input tokens and 1,000 output tokens. That is enough for the alert payload, rule description, short asset record, recent log snippets, identity context, known false-positive notes, and a structured verdict.
Do not budget from chat-message intuition. Security workflows carry evidence. A single alert can include process trees, authentication logs, cloud audit events, IP enrichment, user history, vulnerability data, and detection-rule metadata.
💡 Key Takeaway: Budget SOC AI around alert packets and handoff packets, not prompts. The difference between 3,000 input tokens and 24,000 input tokens is the difference between cheap classification and investigation-grade summarization.
Cost per security alert by model
The formula is simple:
Cost per alert = input tokens × input price + output tokens × output price
For the standard alert packet, this guide uses:
- 6,000 input tokens
- 1,000 output tokens
- Prices from current AI Cost Check model data
- Cost shown per alert and per 1,000 alerts
| Model | Input / output price per 1M tokens | Standard alert cost | Cost per 1,000 alerts | Best role |
|---|---|---|---|---|
| GPT-5 nano | $0.05 / $0.40 | $0.00070 | $0.70 | Cheapest text triage |
| Gemini 2.0 Flash-Lite | $0.075 / $0.30 | $0.00075 | $0.75 | Cheap triage with large context |
| DeepSeek V4 Flash | $0.14 / $0.28 | $0.00112 | $1.12 | Low-cost structured investigation |
| Grok 4.1 Fast | $0.20 / $0.50 | $0.00170 | $1.70 | Cheap long-context review |
| DeepSeek V3.2 | $0.28 / $0.42 | $0.00210 | $2.10 | Budget reasoning and JSON outputs |
| GPT-5 mini | $0.25 / $2.00 | $0.00350 | $3.50 | Balanced investigation notes |
| Gemini 2.5 Flash | $0.30 / $2.50 | $0.00430 | $4.30 | Multimodal and broad security context |
| Claude Haiku 4.5 | $1.00 / $5.00 | $0.01100 | $11.00 | Conservative lightweight summaries |
| Claude Sonnet 4.6 | $3.00 / $15.00 | $0.03300 | $33.00 | Premium escalation and handoff quality |
| GPT-5.5 | $5.00 / $30.00 | $0.06000 | $60.00 | Complex IR reasoning |
| GPT-5.5 Pro | $30.00 / $180.00 | $0.36000 | $360.00 | Rare executive or legal-grade incident memo |
[stat] 514x The cost spread between GPT-5 nano and GPT-5.5 Pro for the same 6k-input, 1k-output security alert packet
The cheapest practical triage model is GPT-5 nano. It costs less than one tenth of a cent per standard alert and $0.35 per 1,000 lightweight triage alerts. Use it when the output is structured: severity, entities, reason codes, queue, confidence, and whether the case needs review.
Premium models are not wrong. They are wrong as the default. Claude Sonnet 4.6 is excellent for human-readable handoffs, but it costs 47x more than GPT-5 nano on the standard packet. GPT-5.5 Pro costs 514x more.
Cost by SOC task type
A good SOC stack does not use one prompt for everything. Split the workflow into small, measurable tasks and route by risk.
Lightweight alert triage
Lightweight triage receives the alert payload, rule description, asset label, user identity, and a few recent event snippets. Use 3,000 input tokens and 500 output tokens as the planning number.
| Model | Cost per triage alert | Cost per 1,000 triage alerts |
|---|---|---|
| GPT-5 nano | $0.00035 | $0.35 |
| Gemini 2.0 Flash-Lite | $0.00038 | $0.38 |
| DeepSeek V4 Flash | $0.00056 | $0.56 |
| Grok 4.1 Fast | $0.00085 | $0.85 |
| GPT-5 mini | $0.00175 | $1.75 |
| Claude Sonnet 4.6 | $0.01650 | $16.50 |
Use GPT-5 nano for cheap text triage. The output should be compact JSON, not a long paragraph. Require the model to return alert type, involved host, user, IPs, likely false-positive reason, confidence, recommended queue, and a one-sentence rationale.
Enriched alert review
Enriched review adds related events, endpoint process context, vulnerability or asset criticality, threat-intel notes, identity history, and previous alerts. Use 8,000 input tokens and 1,200 output tokens.
| Model | Cost per enriched review | Cost per 1,000 reviews |
|---|---|---|
| GPT-5 nano | $0.00088 | $0.88 |
| Gemini 2.0 Flash-Lite | $0.00096 | $0.96 |
| DeepSeek V4 Flash | $0.00146 | $1.46 |
| DeepSeek V3.2 | $0.00274 | $2.74 |
| GPT-5 mini | $0.00440 | $4.40 |
| Claude Sonnet 4.6 | $0.04200 | $42.00 |
Use DeepSeek V4 Flash for low-cost enriched review when the output feeds another system or a case-management tool. Use GPT-5 mini when the output is read directly by analysts and needs cleaner explanations.
Incident summaries
Incident summaries are longer because the model reads multiple alerts, analyst notes, timeline snippets, affected assets, containment status, and open questions. Use 16,000 input tokens and 2,500 output tokens.
| Model | Cost per incident summary | Cost per 1,000 summaries |
|---|---|---|
| DeepSeek V4 Flash | $0.00294 | $2.94 |
| Grok 4.1 Fast | $0.00445 | $4.45 |
| GPT-5 mini | $0.00900 | $9.00 |
| Gemini 2.5 Flash | $0.01105 | $11.05 |
| Claude Haiku 4.5 | $0.02850 | $28.50 |
| Claude Sonnet 4.6 | $0.08550 | $85.50 |
| GPT-5.5 | $0.15500 | $155.00 |
Use GPT-5 mini as the balanced incident-summary model. It costs $9 per 1,000 summaries, which is cheap enough for broad use and strong enough for readable timelines, scope statements, and next-step lists.
Escalation notes and analyst handoffs
Escalation notes are shorter than full handoffs. Use 10,000 input tokens and 1,500 output tokens for an escalation note. A full human analyst handoff uses 24,000 input tokens and 3,000 output tokens.
| Model | Escalation note | Analyst handoff | Handoff cost per 1,000 |
|---|---|---|---|
| DeepSeek V4 Flash | $0.00182 | $0.00420 | $4.20 |
| GPT-5 mini | $0.00550 | $0.01200 | $12.00 |
| Gemini 2.5 Flash | $0.00675 | $0.01470 | $14.70 |
| Claude Haiku 4.5 | $0.01750 | $0.03900 | $39.00 |
| Claude Sonnet 4.6 | $0.05250 | $0.11700 | $117.00 |
| GPT-5.5 | $0.09500 | $0.21000 | $210.00 |
| GPT-5.5 Pro | $0.57000 | $1.26000 | $1,260.00 |
Use Claude Sonnet 4.6 for premium human handoffs. The cost is $0.117 per handoff, or $117 per 1,000 handoffs. That is expensive compared with triage, but tiny compared with analyst time when the case is genuinely high risk.
📊 Quick Math: If only 1% of 100,000 monthly alerts need a Sonnet handoff, the premium layer costs $117/month. If every alert gets the same Sonnet handoff, it costs $11,700/month.
Recommended model routing for SOC teams
The best SOC architecture is a three-layer routing system.
Layer 1: Cheap triage for every alert
Run every alert through GPT-5 nano. Keep the prompt short and force structured output. The model should not write an essay. It should classify, extract, score, and route.
Use this layer for:
- severity normalization
- likely false-positive detection
- duplicate or related-alert grouping
- queue assignment
- entity extraction
- confidence scoring
- recommended next action
For a lightweight triage packet of 3,000 input tokens and 500 output tokens, GPT-5 nano costs $0.35 per 1,000 alerts. At 1 million alerts/month, the first-pass triage bill is about $350/month.
Layer 2: Balanced investigation for alerts that survive triage
Send medium-confidence and suspicious alerts to GPT-5 mini or DeepSeek V4 Flash. This layer reads more context and produces analyst-friendly notes.
Use DeepSeek V4 Flash when cost and structured output matter most. Use GPT-5 mini when the summary will go directly into Slack, Jira, ServiceNow, a SIEM case, or an analyst queue.
Layer 3: Premium escalation for serious cases
Send high-impact incidents to Claude Sonnet 4.6. This is the model for long handoffs, executive-ready summaries, careful containment notes, and ambiguous incident narratives.
Use GPT-5.5 Pro only for rare legal, regulator, board, or post-incident review memos. For a 30,000 input / 5,000 output IR memo, GPT-5.5 Pro costs $1.80 per memo. That is acceptable for rare cases and reckless for routine alerts.
✅ TL;DR: Use GPT-5 nano for cheap triage, GPT-5 mini for balanced incident summaries, and Claude Sonnet 4.6 for premium analyst handoffs. Reserve GPT-5.5 Pro for rare executive or legal-grade incident memos.
Monthly SOC cost scenarios
Per-alert pricing is useful. Monthly routing is what finance and security leadership actually need.
Scenario 1: Small SOC with 10,000 alerts per month
Assumptions:
- 10,000 alerts/month get GPT-5 nano lightweight triage
- 20% get GPT-5 mini escalation notes
- 3% get Claude Sonnet 4.6 analyst handoffs
| Component | Volume | Unit cost | Monthly cost |
|---|---|---|---|
| GPT-5 nano triage | 10,000 | $0.00035 | $3.50 |
| GPT-5 mini escalation notes | 2,000 | $0.00550 | $11.00 |
| Claude Sonnet 4.6 handoffs | 300 | $0.11700 | $35.10 |
| Total | 10,000 alerts | — | $49.60/month |
At this scale, the model bill is not the constraint. The important work is prompt design, analyst review, audit logging, and measuring whether AI reduces mean time to triage.
Scenario 2: Mid-market SOC with 100,000 alerts per month
Assumptions:
- 100,000 alerts/month get GPT-5 nano triage
- 15% get DeepSeek V4 Flash enriched review
- 5% get GPT-5 mini escalation notes
- 1% get Claude Sonnet 4.6 analyst handoffs
| Component | Volume | Unit cost | Monthly cost |
|---|---|---|---|
| GPT-5 nano triage | 100,000 | $0.00035 | $35.00 |
| DeepSeek V4 Flash enriched review | 15,000 | $0.00146 | $21.84 |
| GPT-5 mini escalation notes | 5,000 | $0.00550 | $27.50 |
| Claude Sonnet 4.6 handoffs | 1,000 | $0.11700 | $117.00 |
| Total | 100,000 alerts | — | $201.34/month |
The routed workflow keeps the bill near $200/month while still giving important cases a premium summary. If the same SOC sent every alert to Claude Sonnet 4.6 for full handoff generation, the bill would be $11,700/month.
Scenario 3: Enterprise SOC with 1 million alerts per month
Assumptions:
- 1,000,000 alerts/month get GPT-5 nano triage
- 10% get DeepSeek V4 Flash enriched review
- 3% get GPT-5 mini incident summaries
- 1% get Claude Sonnet 4.6 analyst handoffs
- 0.1% get GPT-5.5 Pro executive or legal-grade IR memos
| Component | Volume | Unit cost | Monthly cost |
|---|---|---|---|
| GPT-5 nano triage | 1,000,000 | $0.00035 | $350.00 |
| DeepSeek V4 Flash enriched review | 100,000 | $0.00146 | $145.60 |
| GPT-5 mini incident summaries | 30,000 | $0.00900 | $270.00 |
| Claude Sonnet 4.6 handoffs | 10,000 | $0.11700 | $1,170.00 |
| GPT-5.5 Pro IR memos | 1,000 | $1.80000 | $1,800.00 |
| Total | 1,000,000 alerts | — | $3,735.60/month |
The expensive line is not first-pass triage. It is the rare memo layer. That is the right shape. Your best model should be concentrated on incidents where precision, accountability, and readability matter.
How to keep AI alert triage costs low
First, shrink the packet before the model sees it. Do not send raw logs when extracted fields are enough. Build a compact alert object with rule metadata, key entities, asset criticality, recent related events, and the smallest evidence snippets needed for a decision.
Second, cap output length. A triage output should be structured and short:
- normalized severity
- category
- involved entities
- evidence references
- confidence score
- likely false-positive reason
- recommended queue
- next action
Third, route by confidence. Clean duplicates, known benign patterns, and low-confidence noise should stay on cheap models. High-impact assets, suspicious identity activity, endpoint process chains, and multi-stage detections deserve richer summaries.
Fourth, separate summarization from action. The model can draft "disable account" as a recommendation, but your workflow should require approved tools, human confirmation, or deterministic policy gates before action.
Fifth, measure cost per useful alert, not cost per API call. A cheap model that increases analyst rework is not cheap. Track alert reopen rate, analyst override rate, escalation precision, and time saved per queue.
For general pricing discipline, read 10 strategies to cut your AI API bill in half. The same principles apply to SOC workflows: shorter prompts, tighter outputs, caching, routing, and continuous measurement.
Cheapest models for each SOC job
Use these defaults:
| Job | Recommended model | Reason |
|---|---|---|
| First-pass alert triage | GPT-5 nano | Lowest cost for structured text classification |
| Triage with very large context | Gemini 2.0 Flash-Lite | Cheap and large-context friendly |
| Enriched structured review | DeepSeek V4 Flash | Strong budget choice for JSON-style investigation outputs |
| Balanced incident summary | GPT-5 mini | Best cost-quality default for readable SOC notes |
| Premium analyst handoff | Claude Sonnet 4.6 | Stronger long-form reasoning and reviewer-ready language |
| Legal, board, or regulator memo | GPT-5.5 Pro | Reserve for rare high-stakes incident narratives |
If your team is still estimating token counts, start with the AI Cost Check calculator and price each workflow separately. If tokens are new to your finance team, send them what AI tokens are before asking them to approve a monthly budget.
Frequently asked questions
How much does AI security alert triage cost per alert?
A lightweight alert triage job with 3,000 input tokens and 500 output tokens costs about $0.00035 per alert on GPT-5 nano, $0.00038 on Gemini 2.0 Flash-Lite, and $0.00175 on GPT-5 mini. A standard alert packet with 6,000 input tokens and 1,000 output tokens costs $0.00070 on GPT-5 nano and $0.033 on Claude Sonnet 4.6.
How much does AI alert triage cost per 1,000 alerts?
For 1,000 standard alert packets, expect $0.70 on GPT-5 nano, $0.75 on Gemini 2.0 Flash-Lite, $1.12 on DeepSeek V4 Flash, $3.50 on GPT-5 mini, and $33 on Claude Sonnet 4.6. Use the AI Cost Check calculator to adjust the token counts for your own SIEM and EDR data.
Which model is cheapest for SOC alert triage?
GPT-5 nano is the cheapest model in this comparison for text-only alert triage, at $0.35 per 1,000 lightweight triage alerts and $0.70 per 1,000 standard alert packets. Use Gemini 2.0 Flash-Lite when you want a similarly cheap option with a larger context window.
Which model should SOC teams use for analyst handoffs?
Use Claude Sonnet 4.6 for premium analyst handoffs. At 24,000 input tokens and 3,000 output tokens, it costs $0.117 per handoff or $117 per 1,000 handoffs. Use GPT-5 mini for routine summaries and reserve Sonnet for cases that human analysts will actually investigate.
Can AI replace a SOC analyst?
No. AI should reduce queue noise, compress evidence, draft notes, and help analysts move faster. It does not replace detection engineering, containment approvals, incident command, forensic judgment, or accountability for security decisions.
Calculate your own SOC AI cost
Price four packets before you build:
- Lightweight triage: 3,000 input + 500 output tokens
- Enriched alert review: 8,000 input + 1,200 output tokens
- Incident summary: 16,000 input + 2,500 output tokens
- Analyst handoff: 24,000 input + 3,000 output tokens
Then multiply each packet by your monthly alert volume and escalation rate. A strong default stack is GPT-5 nano for triage, GPT-5 mini for balanced incident summaries, and Claude Sonnet 4.6 for premium handoffs.
Run your exact token counts in AI Cost Check, then stress-test the operating plan with estimate AI API costs before building. The winning SOC design is not one model everywhere. It is cheap triage, selective investigation, and premium reasoning only where the incident justifies it.