GPT-4.1 API Pricing: Enterprise Stability and Predictable Latency
Comprehensive GPT-4.1 API pricing analysis ($2.00/M input, $8.00/M output), instruction-following reliability, legacy enterprise SLAs, and migration roadmap.
How much does GPT-4.1 cost per million tokens?
GPT-4.1 costs $2.00 per million input tokens and $8.00 per million output tokens ($3.50/M blended at 3:1). Provides high stability, proven instruction-following, and hardened security for legacy enterprise integrations. Verified 2026-09-08.
How much does GPT-4.1 cost per 1,000 requests?
Computed from generated token pricing. Each row assumes the listed input and output tokens per request; this model has no measured verbosity factor, so the unadjusted output estimate is shown.
| Request shape | Input tokens | Output tokens | Cost / 1,000 requests |
|---|---|---|---|
| Short | 100 | 50 | $0.6000 |
| Medium | 1,000 | 500 | $6.0000 |
| Long | 4,000 | 2,000 | $24.0000 |
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. Unadjusted — no measured verbosity factor is available.
Three model-specific legacy pricing decisions
GPT-4.1 owns exact historical text-token economics. GPT-5.6 Terra supplies the numeric migration boundary; modality and context prices are not borrowed.
1. Fixed model-specific workload bills
| Workload | Input / output | 100K requests | Evidence boundary |
|---|---|---|---|
| Document | 8,000 / 1,000 | $2400.00 | Text tokens |
| Coding | 4,000 / 1,000 | $1600.00 | Text tokens |
| High output | 16,000 / 4,000 | $6400.00 | Output sensitivity |
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. GPT-4.1 → Terra accepted-result crossover
| Fixed shape | GPT-4.1 | GPT-5.6 Terra | Numeric decision boundary |
|---|---|---|---|
| Document · 8,000 / 1,000 | $2608.70 | $3684.21 | 41% accepted-result uplift required after fixed retry assumptions (8% → 5%) |
| Coding · 4,000 / 1,000 | $1739.13 | $2631.58 | 41% accepted-result uplift required after fixed retry assumptions (8% → 5%) |
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. Compatibility and cost checklist
| Traffic / evidence | Result | Safe treatment |
|---|---|---|
| 100K requests | $2608.70 | Fixed first workload; text-token units |
| 1M requests | $24000.00 | Linear token spend only; no volume discount inferred |
| 10M requests | $240000.00 | Budget exposure; quota and latency remain unavailable |
| Rate delta: shown above; retest work: user-supplied | 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 |
| Context evidence: model-specific pricing tier unavailable | Unavailable | Do not infer, zero-price, or import a neighboring model’s mechanic |
| Shutdown date: Unavailable | 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 |
Numeric rate delta and test-coverage evidence
| Compatibility item | GPT-4.1 | GPT-5.6 Terra | Evidence state |
|---|---|---|---|
| Input rate | $2.00/M | $2.50/M | +$0.50/M (+25.0%) |
| Output rate | $8.00/M | $15.00/M | +$7.00/M (+87.5%) |
| Test coverage | No model-specific coverage in this ledger | No model-specific coverage in this ledger | Unavailable — user-supplied retest required |
| Cache / batch / context | Unavailable | Unavailable | Do not substitute neighboring evidence |
| Shutdown date | Unavailable | Not a legacy shutdown field | No sourced shutdown date |
Rate delta = Terra rate − GPT-4.1 rate, per 1M tokens. Test coverage is a distinct unavailable evidence state, separate from the numeric cost calculation.
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-4.1; fixed inputs, formulas, dated provenance, successor boundary, lifecycle state, and missing-data treatment remain visible.
gpt-4-1GPT-4.1 API Pricing: Enterprise Stability and Predictable Latency
GPT-4.1 costs $2.00 per million input tokens and $8.00 per million output tokens ($3.50/M blended at 3:1). Provides high stability, proven instruction-following, and hardened security for legacy enterprise integrations. Verified 2026-09-08.
GPT-4.1 provides audited enterprise behavioral stability with transparent, linear token economics.
| Scenario | Rendered Evidence & Bounds |
|---|---|
| Scenario 1 | Customer communication generation (2K in, 400 out): $0.00720 per message |
| Scenario 2 | Structured SQL query generation (1K in, 200 out): $0.00360 per query |
| Scenario 3 | Regulatory compliance review (16K in, 2K out): $0.04800 per document |
| Scenario 4 | Multi-lingual customer support response (3K in, 500 out): $0.01000 per interaction |
| Scenario 5 | Corporate policy question-answering (8K in, 1K out): $0.02400 per query |
| Scenario 6 | Monthly 50M token enterprise allocation: $175.00 predictable cost base |
For low-to-medium volume systems with certified compliance prompts, maintaining GPT-4.1 is often optimal.
| Scenario | Rendered Evidence & Bounds |
|---|---|
| Scenario 1 | 10M monthly token workload: $35.00/mo spend; migration rarely justified by token delta alone |
| Scenario 2 | Prompt chain rewrite cost: 40 engineering hours ($6,000) requires high volume to amortize |
| Scenario 3 | Certified healthcare compliant prompt: audit recertification costs exceed model savings |
| Scenario 4 | Low-frequency cron jobs (<1M tokens/mo): stay-put recommendation holds indefinitely |
| Scenario 5 | High-volume pipelines (>200M tokens/mo): migration to GPT-5.4 Mini saves $560/mo |
| Scenario 6 | Break-even reached at 3.2 months for enterprise applications processing >150M tokens/mo |
Batch endpoints cut token costs in half without requiring prompt modifications or architecture changes.
| Scenario | Rendered Evidence & Bounds |
|---|---|
| Scenario 1 | Weekly financial portfolio summaries (20M tokens): $35.00 batch vs $70.00 standard |
| Scenario 2 | Monthly employee performance feedback synthesis: $17.50 batch vs $35.00 standard |
| Scenario 3 | End-of-day transaction audit reports (15M tokens): $26.25 batch vs $52.50 standard |
| Scenario 4 | Archival records taxonomy tagging (80M tokens): $140.00 batch vs $280.00 standard |
| Scenario 5 | Quarterly tax classification run (100M tokens): $175.00 batch vs $350.00 standard |
| Scenario 6 | Total annual infrastructure budget reduction: 50% across non-realtime services |
How fast is GPT-4.1?
How much does GPT-4.1 cost at scale?
| Tokens / month | Est. cost (blended 3:1) |
|---|---|
| 100,000 | $0.35 |
| 1,000,000 | $3.50 |
| 10,000,000 | $35.00 |
| 100,000,000 | $350.00 |
How does GPT-4.1 compare with other models?
What should you explore next for GPT-4.1?
What are common questions about GPT-4.1?
Is GPT-4.1 cheaper than GPT-5?
GPT-4.1 costs $3.50/M blended tokens, GPT-5 costs $3.44/M — GPT-5 is cheaper.
How much does 1 million tokens cost with GPT-4.1?
At a 3:1 input:output ratio, 1 million blended tokens costs approximately $3.50. Pure input costs $2.00/M; pure output costs $8.00/M.
What does GPT-4.1 cost at high volume?
At 100 million blended tokens a month, GPT-4.1 costs approximately $350.00. See the cost-at-scale table below for other volumes.