OpenAI GPT-5.4 Pro API Pricing: Frontier Deep Reasoning Economics
Analyze OpenAI GPT-5.4 Pro API pricing ($30.00/M input, $180.00/M output), maximum-depth analytical reasoning, prompt caching, and enterprise ROI.
How much does GPT-5.4 Pro cost per million tokens?
OpenAI GPT-5.4 Pro costs $30.00 per million input tokens and $180.00 per million output tokens ($67.50/M blended at 3:1). Engineered for maximum reasoning depth, complex scientific synthesis, and zero-defect enterprise execution. Verified 2026-09-08.
How much does GPT-5.4 Pro cost per 1,000 requests?
Computed from generated token pricing. Each row assumes the listed input and output tokens per request; output is adjusted by this model's measured 1.04× verbosity factor.
| Request shape | Input tokens | Output tokens | Cost / 1,000 requests |
|---|---|---|---|
| Short | 100 | 50 | $12.3600 |
| Medium | 1,000 | 500 | $123.6000 |
| Long | 4,000 | 2,000 | $494.4000 |
Formula: ((input price × input tokens) + (output price × output tokens × verbosity factor)) ÷ 1,000,000 × 1,000. Assumptions: short 100/50, medium 1,000/500, long 4,000/2,000 input/output tokens per request. Verbosity run: 2026-06-21T00:00:00.000Z.
Three model-specific legacy pricing decisions
GPT-5.4 Pro owns the historical professional-analysis and coding-agent bill; GPT-5.6 Sol is a dated migration input only.
1. Fixed model-specific workload bills
| Workload | Input / output | 100K requests | Evidence boundary |
|---|---|---|---|
| Professional analysis | 12,000 / 3,000 | $90000.00 | Output-heavy; output share shown |
| Coding agent | 8,000 / 2,000 | $60000.00 | Text tokens |
| Long answer | 32,000 / 6,000 | $204000.00 | Fixed output shape |
Formula: requests × (input tokens × input $/M + output tokens × output $/M × output expansion) ÷ 1,000,000. Retry-adjusted cost = base ÷ (1 − retry rate); the base table does not hide a retry assumption.
2. Pro → Sol accepted-result crossover
| Fixed shape | GPT-5.4 Pro | GPT-5.6 Sol | Numeric decision boundary |
|---|---|---|---|
| Professional analysis · 12,000 / 3,000 | $100000.00 | $11489.36 | 18% accepted-result uplift required after fixed retry assumptions (10% → 6%) |
| Coding agent · 8,000 / 2,000 | $66666.67 | $7659.57 | 18% accepted-result uplift required after fixed retry assumptions (10% → 6%) |
This is a cost-per-accepted-result threshold, not a measured quality claim. It answers when the successor’s dated bill can absorb its required uplift; it does not decide the broad model comparison.
3. Legacy availability and delay-cost ledger
| Traffic / evidence | Result | Safe treatment |
|---|---|---|
| 100K requests | $100000.00 | Fixed first workload; text-token units |
| 1M requests | $900000.00 | Linear token spend only; no volume discount inferred |
| 10M requests | $9000000.00 | Budget exposure; quota and latency remain unavailable |
| Cache and batch rates: Unavailable | Unavailable | Do not infer, zero-price, or import a neighboring model’s mechanic |
| Context tier: Unavailable in the pricing record | Unavailable | Do not infer, zero-price, or import a neighboring model’s mechanic |
| Shutdown date: Unavailable; null is not indefinite availability | Unavailable | Do not infer, zero-price, or import a neighboring model’s mechanic |
| Lifecycle | legacy; no sourced announcement date | No sourced shutdown date; revalidate before current claims |
Output cost-share calculation
| Workload | Input cost | Output cost | Output share |
|---|---|---|---|
| Professional analysis | $36000.00 | $54000.00 | 60.0% |
| Coding agent | $24000.00 | $36000.00 | 60.0% |
| Long answer | $96000.00 | $108000.00 | 52.9% |
Output share = output-token spend ÷ (input-token spend + output-token spend), using 100K requests and the fixed output expansion shown above.
Delay-of-migration ledger
| Delay | Monthly requests | Legacy monthly cost | Cumulative delay cost | Retest input |
|---|---|---|---|---|
| 1 month | 1,000,000 | $900000.00 | $900000.00 | One fixed workload retest at each review point |
| 3 months | 1,000,000 | $900000.00 | $2700000.00 | One fixed workload retest at each review point |
| 6 months | 1,000,000 | $900000.00 | $5400000.00 | One fixed workload retest at each review point |
| 12 months | 1,000,000 | $900000.00 | $10800000.00 | One fixed workload retest at each review point |
Delay cost = 1,000,000-request legacy monthly bill × delay months. Quality, latency, and shutdown date remain unavailable; the retest input is an explicit operational assumption, not measured evidence.
Price verified 2026-04-06; lifecycle verified 2026-08-14. Luna is the data owner. This is historical evidence, not a current availability promise: revalidate before migrating. “Unavailable” means no compatible dated evidence was found; it is never treated as zero. First-party price source · lifecycle source · Test this model in All AI Ask.
Continue with the lifecycle tracker and all dated API pricing; these links keep lifecycle policy and cross-market pricing in their existing owners.
All three Batch 6 contributions are server-rendered for GPT-5.4 Pro; fixed inputs, formulas, dated provenance, successor boundary, lifecycle state, and missing-data treatment remain visible.
Batch 68 · exact model pricing decision contributions · verified 2026-09-08
Exact model boundary: OpenAI gpt-5.4-pro (slug gpt-5-4-pro). First-party provider pricing and API documentation remain fact owners.
Frontier deep reasoning token pricing and monthly spend matrix
Frozen Batch 68 scenario board. Formula / deterministic rule: monthly_spend = calls * ((in_tokens * 30.00 + out_tokens * 180.00) / 1M) Boundary: Owns GPT-5.4 Pro premium tier token expenditure calculations.
| Frozen scenario / field ID | Model, identity, provider, and evidence fields | Result | State |
|---|---|---|---|
batch68-gpt-5-4-pro-m1-r11K autonomous scientific discovery workflows | model=gpt-5.4-pro; slug=gpt-5-4-pro; provider=OpenAI; scenario=1K autonomous scientific discovery workflows; workload; prompt tokens; completion tokens; standard spend; cached spend; batch spend; ROI verdict; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-08; measurement versus assumption=explicit | Unavailable — 1K autonomous scientific discovery workflows is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch68-gpt-5-4-pro-m1-r25K multi-file software architecture reviews | model=gpt-5.4-pro; slug=gpt-5-4-pro; provider=OpenAI; scenario=5K multi-file software architecture reviews; workload; prompt tokens; completion tokens; standard spend; cached spend; batch spend; ROI verdict; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-08; measurement versus assumption=explicit | Unavailable — 5K multi-file software architecture reviews is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch68-gpt-5-4-pro-m1-r325K mission-critical compliance audits | model=gpt-5.4-pro; slug=gpt-5-4-pro; provider=OpenAI; scenario=25K mission-critical compliance audits; workload; prompt tokens; completion tokens; standard spend; cached spend; batch spend; ROI verdict; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-08; measurement versus assumption=explicit | Unavailable — 25K mission-critical compliance audits is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch68-gpt-5-4-pro-m1-r4prompt caching reuse (50% input discount) | model=gpt-5.4-pro; slug=gpt-5-4-pro; provider=OpenAI; scenario=prompt caching reuse (50% input discount); workload; prompt tokens; completion tokens; standard spend; cached spend; batch spend; ROI verdict; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-08; measurement versus assumption=explicit | Unavailable — prompt caching reuse (50% input discount) is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch68-gpt-5-4-pro-m1-r5batch processing API queue (50% discount) | model=gpt-5.4-pro; slug=gpt-5-4-pro; provider=OpenAI; scenario=batch processing API queue (50% discount); workload; prompt tokens; completion tokens; standard spend; cached spend; batch spend; ROI verdict; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-08; measurement versus assumption=explicit | Unavailable — batch processing API queue (50% discount) is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch68-gpt-5-4-pro-m1-r6unresolved billing currency | model=gpt-5.4-pro; slug=gpt-5-4-pro; provider=OpenAI; scenario=unresolved billing currency; workload; prompt tokens; completion tokens; standard spend; cached spend; batch spend; ROI verdict; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-08; measurement versus assumption=explicit | Unavailable — unresolved billing currency has no matched, dated bilateral observation. | FAIL CLOSED — manual, probe, or source evidence required |
First-party provenance: OpenAI API pricing; verification date 2026-09-08. Missing or conflicting joins fail closed.
Mission-critical zero-defect ROI and defect prevention gate
Frozen Batch 68 scenario board. Formula / deterministic rule: roi = prevented_production_outage_value - run_cost Boundary: Owns deep reasoning justification against catastrophic software or financial errors.
| Frozen scenario / field ID | Model, identity, provider, and evidence fields | Result | State |
|---|---|---|---|
batch68-gpt-5-4-pro-m2-r1financial transaction smart contract audit | model=gpt-5.4-pro; slug=gpt-5-4-pro; provider=OpenAI; scenario=financial transaction smart contract audit; domain; error risk value; reasoning token budget; inference cost; net prevented loss; deployment verdict; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-08; measurement versus assumption=explicit | Unavailable — financial transaction smart contract audit is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch68-gpt-5-4-pro-m2-r2aerospace regulatory compliance packet | model=gpt-5.4-pro; slug=gpt-5-4-pro; provider=OpenAI; scenario=aerospace regulatory compliance packet; domain; error risk value; reasoning token budget; inference cost; net prevented loss; deployment verdict; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-08; measurement versus assumption=explicit | Unavailable — aerospace regulatory compliance packet is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch68-gpt-5-4-pro-m2-r3medical diagnostic protocol synthesis | model=gpt-5.4-pro; slug=gpt-5-4-pro; provider=OpenAI; scenario=medical diagnostic protocol synthesis; domain; error risk value; reasoning token budget; inference cost; net prevented loss; deployment verdict; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-08; measurement versus assumption=explicit | Unavailable — medical diagnostic protocol synthesis is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch68-gpt-5-4-pro-m2-r4enterprise security architecture sign-off | model=gpt-5.4-pro; slug=gpt-5-4-pro; provider=OpenAI; scenario=enterprise security architecture sign-off; domain; error risk value; reasoning token budget; inference cost; net prevented loss; deployment verdict; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-08; measurement versus assumption=explicit | Unavailable — enterprise security architecture sign-off is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch68-gpt-5-4-pro-m2-r5unnecessary premium invocation penalty | model=gpt-5.4-pro; slug=gpt-5-4-pro; provider=OpenAI; scenario=unnecessary premium invocation penalty; domain; error risk value; reasoning token budget; inference cost; net prevented loss; deployment verdict; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-08; measurement versus assumption=explicit | Unavailable — unnecessary premium invocation penalty is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch68-gpt-5-4-pro-m2-r6unverified proof assertion | model=gpt-5.4-pro; slug=gpt-5-4-pro; provider=OpenAI; scenario=unverified proof assertion; domain; error risk value; reasoning token budget; inference cost; net prevented loss; deployment verdict; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-08; measurement versus assumption=explicit | Unavailable — unverified proof assertion is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
First-party provenance: OpenAI API documentation; verification date 2026-09-08. Missing or conflicting joins fail closed.
Three-tier escalation architecture: Nano vs Mini vs Pro
Frozen Batch 68 scenario board. Formula / deterministic rule: blended_cost = nano_cost + mini_cost + pro_cost; Pro reserved for critical failures Boundary: Owns multi-model architectural routing reserving GPT-5.4 Pro for difficult problems.
| Frozen scenario / field ID | Model, identity, provider, and evidence fields | Result | State |
|---|---|---|---|
batch68-gpt-5-4-pro-m3-r190% GPT-5.4 Nano triage / 9% Mini / 1% Pro | model=gpt-5.4-pro; slug=gpt-5-4-pro; provider=OpenAI; scenario=90% GPT-5.4 Nano triage / 9% Mini / 1% Pro; routing distribution; total monthly calls; blended spend; cost savings vs pure Pro; accuracy retention; routing verdict; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-08; measurement versus assumption=explicit | Unavailable — 90% GPT-5.4 Nano triage / 9% Mini / 1% Pro is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch68-gpt-5-4-pro-m3-r280% Nano / 15% Mini / 5% Pro escalation | model=gpt-5.4-pro; slug=gpt-5-4-pro; provider=OpenAI; scenario=80% Nano / 15% Mini / 5% Pro escalation; routing distribution; total monthly calls; blended spend; cost savings vs pure Pro; accuracy retention; routing verdict; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-08; measurement versus assumption=explicit | Unavailable — 80% Nano / 15% Mini / 5% Pro escalation is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch68-gpt-5-4-pro-m3-r370% Nano / 20% Mini / 10% Pro escalation | model=gpt-5.4-pro; slug=gpt-5-4-pro; provider=OpenAI; scenario=70% Nano / 20% Mini / 10% Pro escalation; routing distribution; total monthly calls; blended spend; cost savings vs pure Pro; accuracy retention; routing verdict; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-08; measurement versus assumption=explicit | Unavailable — 70% Nano / 20% Mini / 10% Pro escalation is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch68-gpt-5-4-pro-m3-r4100% direct GPT-5.4 Pro execution | model=gpt-5.4-pro; slug=gpt-5-4-pro; provider=OpenAI; scenario=100% direct GPT-5.4 Pro execution; routing distribution; total monthly calls; blended spend; cost savings vs pure Pro; accuracy retention; routing verdict; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-08; measurement versus assumption=explicit | Unavailable — 100% direct GPT-5.4 Pro execution is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch68-gpt-5-4-pro-m3-r5unresolved routing confidence threshold trigger | model=gpt-5.4-pro; slug=gpt-5-4-pro; provider=OpenAI; scenario=unresolved routing confidence threshold trigger; routing distribution; total monthly calls; blended spend; cost savings vs pure Pro; accuracy retention; routing verdict; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-08; measurement versus assumption=explicit | Unavailable — unresolved routing confidence threshold trigger has no matched, dated bilateral observation. | FAIL CLOSED — manual, probe, or source evidence required |
batch68-gpt-5-4-pro-m3-r6model fall-through without verification | model=gpt-5.4-pro; slug=gpt-5-4-pro; provider=OpenAI; scenario=model fall-through without verification; routing distribution; total monthly calls; blended spend; cost savings vs pure Pro; accuracy retention; routing verdict; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-08; measurement versus assumption=explicit | Unavailable — model fall-through without verification is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
First-party provenance: OpenAI API pricing; verification date 2026-09-08. Missing or conflicting joins fail closed.
Method and limitations: formulas are deterministic; observed and assumed inputs are labeled; no missing provider, host, account, region, realm, alias, snapshot, revision, weight, artifact, control, tool, modality, workload, rate-period, timestamp, or result is transferred. Run the gpt-5-4-pro Batch 68 scenario →
How fast is GPT-5.4 Pro?
How much does GPT-5.4 Pro cost at scale?
| Tokens / month | Est. cost (blended 3:1) |
|---|---|
| 100,000 | $6.75 |
| 1,000,000 | $67.50 |
| 10,000,000 | $675.00 |
| 100,000,000 | $6750.00 |
How does GPT-5.4 Pro compare with other models?
What should you explore next for GPT-5.4 Pro?
What are common questions about GPT-5.4 Pro?
Is GPT-5.4 Pro cheaper than Claude Opus 5?
GPT-5.4 Pro costs $67.50/M blended tokens, Claude Opus 5 costs $30.00/M — Claude Opus 5 is cheaper.
How much does 1 million tokens cost with GPT-5.4 Pro?
At a 3:1 input:output ratio, 1 million blended tokens costs approximately $67.50. Pure input costs $30.00/M; pure output costs $180.00/M.
What does GPT-5.4 Pro cost at high volume?
At 100 million blended tokens a month, GPT-5.4 Pro costs approximately $6750.00. See the cost-at-scale table below for other volumes.