OpenAI GPT-5.4 Nano API Pricing: Rapid Edge Triage & Classification
Examine OpenAI GPT-5.4 Nano API pricing ($0.20/M input, $1.25/M output), ultra-low latency intent classification, sub-second routing, and batch savings.
How much does GPT-5.4 Nano cost per million tokens?
OpenAI GPT-5.4 Nano costs $0.20 per million input tokens and $1.25 per million output tokens ($0.4625/M blended at 3:1). Engineered for high-throughput classification, sub-100ms intent routing, and real-time guardrails. Verified 2026-09-08.
How much does GPT-5.4 Nano 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 0.78× verbosity factor.
| Request shape | Input tokens | Output tokens | Cost / 1,000 requests |
|---|---|---|---|
| Short | 100 | 50 | $0.0688 |
| Medium | 1,000 | 500 | $0.6875 |
| Long | 4,000 | 2,000 | $2.7500 |
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: 2026-06-16T20:31:30.728Z.
Three model-specific legacy pricing decisions
GPT-5.4 Nano owns high-volume classification, routing, and short-generation economics; image, latency, and quota units are not substituted.
1. Fixed model-specific workload bills
| Workload | Input / output | 100K requests | Evidence boundary |
|---|---|---|---|
| Classification | 300 / 30 | $9.75 | 100K / 1M / 10M ladder |
| Routing | 500 / 80 | $20.00 | 100K / 1M / 10M ladder |
| Short generation | 1,000 / 500 | $82.50 | Text tokens |
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. Nano → Luna migration premium
| Fixed shape | GPT-5.4 Nano | GPT-5.6 Luna | Numeric decision boundary |
|---|---|---|---|
| Classification · 300 / 30 | $10.26 | $50.00 | 387% accepted-result uplift required after fixed retry assumptions (5% → 4%) |
| Routing · 500 / 80 | $21.05 | $102.08 | 387% accepted-result uplift required after fixed retry assumptions (5% → 4%) |
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. Budget-impact and missing-input ledger
| Traffic / evidence | Result | Safe treatment |
|---|---|---|
| 100K requests | $10.26 | Fixed first workload; text-token units |
| 1M requests | $97.50 | Linear token spend only; no volume discount inferred |
| 10M requests | $975.00 | Budget exposure; quota and latency remain unavailable |
| Latency and quota: Unavailable | Unavailable | Do not infer, zero-price, or import a neighboring model’s mechanic |
| Cache and batch: Unavailable | Unavailable | Do not infer, zero-price, or import a neighboring model’s mechanic |
| Shutdown date: Unavailable; no indefinite-availability inference | 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 |
Nano-to-Luna premium by workload shape
| Workload | Nano cost | Luna cost | Absolute premium | Premium | Accepted-result uplift required |
|---|---|---|---|---|---|
| Classification | $9.75 | $48.00 | $38.25 | 392.3% | 392.3% |
| Routing | $20.00 | $98.00 | $78.00 | 390.0% | 390.0% |
| Short generation | $82.50 | $400.00 | $317.50 | 384.8% | 384.8% |
Premium = Luna cost − Nano cost; percentage premium and required accepted-result uplift = (Luna ÷ Nano − 1) × 100 at each fixed shape.
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 Nano; 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-nano (slug gpt-5-4-nano). First-party provider pricing and API documentation remain fact owners.
Ultra-budget token pricing and high-volume classification matrix
Frozen Batch 68 scenario board. Formula / deterministic rule: monthly_spend = calls * ((in_tokens * 0.20 + out_tokens * 1.25) / 1M) Boundary: Owns GPT-5.4 Nano token tariff modeling and high-volume classification spend.
| Frozen scenario / field ID | Model, identity, provider, and evidence fields | Result | State |
|---|---|---|---|
batch68-gpt-5-4-nano-m1-r1100K intent routing classifications | model=gpt-5.4-nano; slug=gpt-5-4-nano; provider=OpenAI; scenario=100K intent routing classifications; workload; prompt tokens; completion tokens; standard spend; cached spend; batch spend; cost winner; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-08; measurement versus assumption=explicit | Unavailable — 100K intent routing classifications is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch68-gpt-5-4-nano-m1-r2500K customer inquiry triage calls | model=gpt-5.4-nano; slug=gpt-5-4-nano; provider=OpenAI; scenario=500K customer inquiry triage calls; workload; prompt tokens; completion tokens; standard spend; cached spend; batch spend; cost winner; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-08; measurement versus assumption=explicit | Unavailable — 500K customer inquiry triage calls is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch68-gpt-5-4-nano-m1-r32M automated content moderation passes | model=gpt-5.4-nano; slug=gpt-5-4-nano; provider=OpenAI; scenario=2M automated content moderation passes; workload; prompt tokens; completion tokens; standard spend; cached spend; batch spend; cost winner; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-08; measurement versus assumption=explicit | Unavailable — 2M automated content moderation passes is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch68-gpt-5-4-nano-m1-r4prompt caching reuse (50% input discount) | model=gpt-5.4-nano; slug=gpt-5-4-nano; provider=OpenAI; scenario=prompt caching reuse (50% input discount); workload; prompt tokens; completion tokens; standard spend; cached spend; batch spend; cost winner; 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-nano-m1-r5batch processing API queue (50% discount) | model=gpt-5.4-nano; slug=gpt-5-4-nano; provider=OpenAI; scenario=batch processing API queue (50% discount); workload; prompt tokens; completion tokens; standard spend; cached spend; batch spend; cost winner; 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-nano-m1-r6unresolved billing currency | model=gpt-5.4-nano; slug=gpt-5-4-nano; provider=OpenAI; scenario=unresolved billing currency; workload; prompt tokens; completion tokens; standard spend; cached spend; batch spend; cost winner; 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.
Sub-second latency SLA and intent classification turnaround audit
Frozen Batch 68 scenario board. Formula / deterministic rule: turnaround = ttft + (tokens_out / tps); optimized for lowest TTFT Boundary: Owns turnaround time benchmarks and user experience responsiveness.
| Frozen scenario / field ID | Model, identity, provider, and evidence fields | Result | State |
|---|---|---|---|
batch68-gpt-5-4-nano-m2-r1real-time intent classification (<80ms) | model=gpt-5.4-nano; slug=gpt-5-4-nano; provider=OpenAI; scenario=real-time intent classification (<80ms); task; response SLA; TTFT; generation speed; SLA compliance; responsiveness champion; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-08; measurement versus assumption=explicit | Unavailable — real-time intent classification (<80ms) is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch68-gpt-5-4-nano-m2-r2customer support routing ticket (<150ms) | model=gpt-5.4-nano; slug=gpt-5-4-nano; provider=OpenAI; scenario=customer support routing ticket (<150ms); task; response SLA; TTFT; generation speed; SLA compliance; responsiveness champion; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-08; measurement versus assumption=explicit | Unavailable — customer support routing ticket (<150ms) is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch68-gpt-5-4-nano-m2-r3content moderation guardrail pass (<120ms) | model=gpt-5.4-nano; slug=gpt-5-4-nano; provider=OpenAI; scenario=content moderation guardrail pass (<120ms); task; response SLA; TTFT; generation speed; SLA compliance; responsiveness champion; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-08; measurement versus assumption=explicit | Unavailable — content moderation guardrail pass (<120ms) is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch68-gpt-5-4-nano-m2-r4high-concurrency request surge | model=gpt-5.4-nano; slug=gpt-5-4-nano; provider=OpenAI; scenario=high-concurrency request surge; task; response SLA; TTFT; generation speed; SLA compliance; responsiveness champion; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-08; measurement versus assumption=explicit | Unavailable — high-concurrency request surge is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch68-gpt-5-4-nano-m2-r5network transit buffer | model=gpt-5.4-nano; slug=gpt-5-4-nano; provider=OpenAI; scenario=network transit buffer; task; response SLA; TTFT; generation speed; SLA compliance; responsiveness champion; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-08; measurement versus assumption=explicit | Unavailable — network transit buffer is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch68-gpt-5-4-nano-m2-r6unmeasured speed fixture | model=gpt-5.4-nano; slug=gpt-5-4-nano; provider=OpenAI; scenario=unmeasured speed fixture; task; response SLA; TTFT; generation speed; SLA compliance; responsiveness champion; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-08; measurement versus assumption=explicit | Unavailable — unmeasured speed fixture 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.
Two-tier triage architecture: Nano triage vs Mini execution
Frozen Batch 68 scenario board. Formula / deterministic rule: blended_cost = nano_volume * nano_cost + mini_volume * mini_cost Boundary: Owns architectural routing between fast Nano triage and deeper Mini execution.
| Frozen scenario / field ID | Model, identity, provider, and evidence fields | Result | State |
|---|---|---|---|
batch68-gpt-5-4-nano-m3-r1100% GPT-5.4 Nano baseline ($0.20/$1.25) | model=gpt-5.4-nano; slug=gpt-5-4-nano; provider=OpenAI; scenario=100% GPT-5.4 Nano baseline ($0.20/$1.25); escalation mix; total monthly queries; blended spend; cost savings vs pure Mini; accuracy retention; routing recommendation; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-08; measurement versus assumption=explicit | Unavailable — 100% GPT-5.4 Nano baseline ($0.20/$1.25) is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch68-gpt-5-4-nano-m3-r290% Nano triage / 10% Mini escalation | model=gpt-5.4-nano; slug=gpt-5-4-nano; provider=OpenAI; scenario=90% Nano triage / 10% Mini escalation; escalation mix; total monthly queries; blended spend; cost savings vs pure Mini; accuracy retention; routing recommendation; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-08; measurement versus assumption=explicit | Unavailable — 90% Nano triage / 10% Mini escalation is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch68-gpt-5-4-nano-m3-r380% Nano triage / 20% Mini escalation | model=gpt-5.4-nano; slug=gpt-5-4-nano; provider=OpenAI; scenario=80% Nano triage / 20% Mini escalation; escalation mix; total monthly queries; blended spend; cost savings vs pure Mini; accuracy retention; routing recommendation; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-08; measurement versus assumption=explicit | Unavailable — 80% Nano triage / 20% Mini escalation is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch68-gpt-5-4-nano-m3-r450% Nano triage / 50% Mini escalation | model=gpt-5.4-nano; slug=gpt-5-4-nano; provider=OpenAI; scenario=50% Nano triage / 50% Mini escalation; escalation mix; total monthly queries; blended spend; cost savings vs pure Mini; accuracy retention; routing recommendation; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-08; measurement versus assumption=explicit | Unavailable — 50% Nano triage / 50% Mini escalation is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch68-gpt-5-4-nano-m3-r5100% direct GPT-5.4 Mini execution | model=gpt-5.4-nano; slug=gpt-5-4-nano; provider=OpenAI; scenario=100% direct GPT-5.4 Mini execution; escalation mix; total monthly queries; blended spend; cost savings vs pure Mini; accuracy retention; routing recommendation; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-08; measurement versus assumption=explicit | Unavailable — 100% direct GPT-5.4 Mini execution is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch68-gpt-5-4-nano-m3-r6unresolved routing confidence threshold trigger | model=gpt-5.4-nano; slug=gpt-5-4-nano; provider=OpenAI; scenario=unresolved routing confidence threshold trigger; escalation mix; total monthly queries; blended spend; cost savings vs pure Mini; accuracy retention; routing recommendation; 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 |
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-nano Batch 68 scenario →
How fast is GPT-5.4 Nano?
How much does GPT-5.4 Nano cost at scale?
| Tokens / month | Est. cost (blended 3:1) |
|---|---|
| 100,000 | $0.05 |
| 1,000,000 | $0.46 |
| 10,000,000 | $4.63 |
| 100,000,000 | $46.25 |
How does GPT-5.4 Nano compare with other models?
What should you explore next for GPT-5.4 Nano?
What are common questions about GPT-5.4 Nano?
Is GPT-5.4 Nano cheaper than Codestral?
GPT-5.4 Nano costs $0.46/M blended tokens, Codestral costs $0.45/M — Codestral is cheaper.
How much does 1 million tokens cost with GPT-5.4 Nano?
At a 3:1 input:output ratio, 1 million blended tokens costs approximately $0.46. Pure input costs $0.20/M; pure output costs $1.25/M.
What does GPT-5.4 Nano cost at high volume?
At 100 million blended tokens a month, GPT-5.4 Nano costs approximately $46.25. See the cost-at-scale table below for other volumes.