OpenAI API Pricing 2026: Complete Guide to Every Model — GPT-5.4, o3, Embeddings, DALL-E, and More

TokenMix Research Lab · 2026-04-05

OpenAI API Pricing 2026: Complete Guide to Every Model — GPT-5.4, o3, Embeddings, DALL-E, and More

OpenAI API Pricing in 2026: Complete Guide to Every Model, Token Cost, and Discount

OpenAI API pricing in 2026 spans from $0.03/M tokens (text embeddings) to $180/M tokens ([GPT-5.4](https://tokenmix.ai/blog/gpt-5-api-pricing) Pro output). The lineup includes four GPT-5.4 tiers, two reasoning models (o3, o4-mini), legacy GPT-4o, embeddings, DALL-E 3, Whisper, and TTS. Caching saves up to 90%, batch processing saves 50%, and fine-tuning costs 3-6x base training rates. This guide covers every OpenAI model's pricing, the surcharges and discounts most guides skip, and real cost calculations at different usage levels. All pricing verified against [OpenAI's official pricing page](https://openai.com/api/pricing/) and tracked by [TokenMix.ai](https://tokenmix.ai) as of April 2026.

Table of Contents

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OpenAI API Pricing Quick Reference

All prices per 1 million tokens, OpenAI direct API, April 2026:

Language Models

| Model | Input | Cached Input | Output | Batch Input | Batch Output | Context | | --- | --- | --- | --- | --- | --- | --- | | **GPT-5.4** | $2.50 | $0.25 | $15.00 | $1.25 | $7.50 | 1.1M* | | **GPT-5.4 Mini** | $0.75 | $0.075 | $4.50 | $0.375 | $2.25 | 400K | | **GPT-5.4 Nano** | $0.20 | $0.02 | $1.25 | $0.10 | $0.625 | 400K | | **GPT-5.4 Pro** | $30.00 | -- | $180.00 | $15.00 | $90.00 | 1.1M* | | **o3** | $2.00 | $0.50 | $16.00 | $1.00 | $8.00 | 200K | | **o4-mini** | $1.10 | $0.275 | $4.40 | $0.55 | $2.20 | 200K | | GPT-4o | $2.50 | $1.25 | $10.00 | $1.25 | $5.00 | 128K | | GPT-4o-mini | $0.15 | $0.075 | $0.60 | $0.075 | $0.30 | 128K |

*GPT-5.4 and GPT-5.4 Pro charge 2x on requests exceeding 272K input tokens.

Other Models

| Model | Pricing | Unit | | --- | --- | --- | | **text-embedding-3-large** | $0.13 | Per 1M tokens | | **text-embedding-3-small** | $0.02 | Per 1M tokens | | **DALL-E 3 (Standard)** | $0.040 | Per image (1024x1024) | | **DALL-E 3 (HD)** | $0.080 | Per image (1024x1024) | | **DALL-E 3 (HD)** | $0.120 | Per image (1792x1024) | | **Whisper** | $0.006 | Per minute of audio | | **TTS** | $15.00 | Per 1M characters | | **TTS HD** | $30.00 | Per 1M characters |

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GPT-5.4 Family Pricing: Nano, Mini, Standard, and Pro

OpenAI's GPT-5.4 lineup has four tiers. Each serves a different workload type.

GPT-5.4 Nano — $0.20/$1.25

The cheapest GPT-5.4 variant. Designed for high-volume, low-complexity tasks.

| Spec | GPT-5.4 Nano | | --- | --- | | Input | $0.20/M | | Output | $1.25/M | | Cached Input | $0.02/M | | Batch Input | $0.10/M | | Context | 400K | | Best for | Classification, routing, simple extraction |

GPT-5.4 Nano competes directly with GPT-4o-mini on capability while offering a larger [context window](https://tokenmix.ai/blog/llm-context-window-explained) (400K vs 128K). At $0.20/$1.25, it is the budget choice for tasks that do not require frontier reasoning.

When to use Nano: intent classification, content filtering, simple entity extraction, routing decisions. When not to use Nano: complex code generation, nuanced writing, multi-step reasoning.

GPT-5.4 Mini — $0.75/$4.50

The balanced middle tier. Enough quality for most production workloads at a fraction of the flagship price.

| Spec | GPT-5.4 Mini | | --- | --- | | Input | $0.75/M | | Output | $4.50/M | | Cached Input | $0.075/M | | Batch Input | $0.375/M | | Context | 400K | | Best for | Production chatbots, document processing, general assistance |

GPT-5.4 Mini matches or exceeds GPT-4o quality at significantly lower output cost ($4.50 vs $10.00). For teams currently on GPT-4o, Mini is an immediate cost reduction with no quality loss.

GPT-5.4 Standard — $2.50/$15.00

The flagship. Best overall quality across OpenAI's lineup (excluding Pro's extended reasoning).

| Spec | GPT-5.4 | | --- | --- | | Input | $2.50/M | | Output | $15.00/M | | Cached Input | $0.25/M | | Batch Input | $1.25/M | | Context | 1.1M* | | SWE-bench | ~80% | | MMLU | ~91% | | Best for | Complex coding, research, critical production tasks |

*2x surcharge on requests exceeding 272K input tokens.

Standard GPT-5.4 is the workhorse for demanding applications. It outperforms [Claude Sonnet 4.6](https://tokenmix.ai/blog/claude-api-cost) on coding (80% vs 73% SWE-bench) and trails only [DeepSeek V4](https://tokenmix.ai/blog/deepseek-api-pricing) (81%).

GPT-5.4 Pro — $30.00/$180.00

The extended reasoning model. 12x the cost of Standard, reserved for the hardest problems.

| Spec | GPT-5.4 Pro | | --- | --- | | Input | $30.00/M | | Output | $180.00/M | | Batch Input | $15.00/M | | Context | 1.1M* | | SWE-bench Pro | 57.7% | | Terminal-Bench | 75.1% | | Best for | Complex proofs, multi-file refactoring, research-grade analysis |

GPT-5.4 Pro uses an extended reasoning budget that produces higher accuracy on the most challenging tasks. The SWE-bench Pro score (57.7%) and Terminal-Bench score (75.1%) reflect its strength on problems where Standard GPT-5.4 fails.

Use Pro only when the quality improvement is worth 12x the cost — typically when failure costs exceed the API premium.

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The 272K Context Surcharge

GPT-5.4 and GPT-5.4 Pro support 1.1 million tokens of context. But requests exceeding 272K input tokens trigger a 2x surcharge:

| GPT-5.4 | Up to 272K | Over 272K | | --- | --- | --- | | Input | $2.50/M | $5.00/M | | Cached Input | $0.25/M | $0.50/M | | Output | $15.00/M | $15.00/M |

Key detail: output pricing does not increase. Only input and cached input double. This is different from Anthropic's Claude, which doubles both input and output pricing past 200K tokens.

Cost Impact Example

Processing a 500K token document with 5K token output:

Without surcharge awareness: 500K x $2.50/M + 5K x $15.00/M = $1.325

Actual cost: 272K x $2.50/M + 228K x $5.00/M + 5K x $15.00/M = $0.68 + $1.14 + $0.075 = **$1.895**

The real cost is 43% higher than the naive calculation. Always account for the surcharge when estimating long-context workloads.

Surcharge Comparison Across Providers

| Provider | Surcharge Threshold | Post-Surcharge Input | Post-Surcharge Output | | --- | --- | --- | --- | | **OpenAI (GPT-5.4)** | 272K | $5.00/M | $15.00/M (unchanged) | | Anthropic (Claude Sonnet 4.6) | 200K | $6.00/M | $30.00/M | | Google (Gemini 2.5 Pro) | 200K | $2.50/M | $20.00/M | | DeepSeek (V4) | None | $0.30/M (flat) | $0.50/M (flat) |

GPT-5.4 has the highest surcharge threshold and does not increase output pricing. For long-context work, this makes GPT-5.4 cheaper than Claude Sonnet 4.6 despite similar base pricing.

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Reasoning Models: o3 and o4-mini Pricing

OpenAI's reasoning models use [chain-of-thought](https://tokenmix.ai/blog/chain-of-thought-prompting) processing for complex tasks. They are separate model endpoints from GPT-5.4.

o3 — $2.00/$16.00

| Spec | o3 | | --- | --- | | Input | $2.00/M | | Cached Input | $0.50/M | | Output | $16.00/M | | Batch Input | $1.00/M | | Batch Output | $8.00/M | | Context | 200K | | Best for | Complex math, multi-step reasoning, research-grade analysis |

o3 generates internal reasoning tokens that count toward output. A request that produces 1K tokens of visible output might generate 10K+ tokens of reasoning, all billed at $16/M output.

Effective cost per visible output token can be 5-20x higher than the listed rate, depending on problem complexity.

o4-mini — $1.10/$4.40

| Spec | o4-mini | | --- | --- | | Input | $1.10/M | | Cached Input | $0.275/M | | Output | $4.40/M | | Batch Input | $0.55/M | | Batch Output | $2.20/M | | Context | 200K | | Best for | Moderate reasoning tasks at budget pricing |

[o4-mini](https://tokenmix.ai/blog/openai-o4-mini-o3-pro) is the cost-efficient reasoning model. It handles most reasoning tasks at roughly half of o3's output cost. Use o3 only when o4-mini's reasoning depth is insufficient.

When to Use Reasoning Models vs GPT-5.4

| Task Type | Recommended Model | Why | | --- | --- | --- | | Simple Q&A, chat | GPT-5.4 Nano or Mini | Reasoning overhead unnecessary | | Code generation | GPT-5.4 Standard | Strong coding without reasoning cost | | Complex math | o4-mini or o3 | Reasoning significantly improves accuracy | | Multi-step logic | o4-mini | Good reasoning at moderate cost | | Research-grade proofs | o3 or GPT-5.4 Pro | Maximum reasoning depth |

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Legacy Models: GPT-4o and GPT-4o-mini

GPT-4o and GPT-4o-mini remain available but are no longer the recommended default.

| Model | Input | Output | Context | Status | | --- | --- | --- | --- | --- | | GPT-4o | $2.50/M | $10.00/M | 128K | Supported, not recommended | | GPT-4o-mini | $0.15/M | $0.60/M | 128K | Supported, budget option |

**GPT-4o vs GPT-5.4 Mini:** GPT-5.4 Mini costs more on input ($0.75 vs $2.50 — wait, GPT-4o is $2.50 input, Mini is $0.75 input). GPT-5.4 Mini is cheaper on input and offers a 400K context window vs 128K. Output is cheaper on GPT-4o ($10 vs $4.50 — actually Mini at $4.50 is cheaper). In summary: GPT-5.4 Mini is cheaper on both input and output with a larger context window and better quality. There is no reason to choose GPT-4o for new projects.

**GPT-4o-mini** remains the cheapest OpenAI option at $0.15/$0.60. For ultra-budget workloads where GPT-5.4 Nano's $0.20/$1.25 is too expensive, GPT-4o-mini is viable, but its 128K context is a limitation.

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Embedding Models Pricing

OpenAI offers two [embedding model](https://tokenmix.ai/blog/text-embedding-models-comparison) sizes:

| Model | Price/M tokens | Dimensions | Best For | | --- | --- | --- | --- | | text-embedding-3-large | $0.13/M | 3072 (default) | High-quality semantic search, RAG | | text-embedding-3-small | $0.02/M | 1536 (default) | Budget-friendly embeddings |

Cost Calculations

Embedding 1 million documents (average 500 tokens each = 500M tokens): - text-embedding-3-large: 500M x $0.13/M = **$65.00** - text-embedding-3-small: 500M x $0.02/M = **$10.00**

Both models support dimension reduction through the API — you can request fewer dimensions to reduce storage costs at the expense of some quality.

Embedding Pricing vs Competitors

| Provider | Model | Price/M tokens | | --- | --- | --- | | OpenAI | text-embedding-3-large | $0.13 | | OpenAI | text-embedding-3-small | $0.02 | | Google | text-embedding-005 | Free (up to limits) | | Voyage AI | voyage-3 | $0.06 |

Google's embedding model is free within usage limits, making it the cheapest option for [RAG](https://tokenmix.ai/blog/rag-tutorial-2026) pipelines. OpenAI's embeddings are competitive on quality.

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Image Generation: DALL-E 3 Pricing

| Resolution | Quality | Price per Image | | --- | --- | --- | | 1024 x 1024 | Standard | $0.040 | | 1024 x 1024 | HD | $0.080 | | 1024 x 1792 | Standard | $0.080 | | 1024 x 1792 | HD | $0.120 |

[DALL-E](https://tokenmix.ai/blog/dall-e-api-pricing) 3 pricing is per-image, not per-token. No batch discount is available. For high-volume image generation, costs add up quickly: - 1,000 standard images/month: $40 - 10,000 standard images/month: $400 - 1,000 HD wide images/month: $120

Comparison to Alternatives

Midjourney and Stable Diffusion offer subscription-based pricing that can be more economical at high volumes. DALL-E 3's advantage is tight integration with the OpenAI API — you can generate images programmatically alongside text processing in a single pipeline.

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Audio Models: Whisper and TTS Pricing

Whisper (Speech-to-Text)

| Model | Price | Unit | | --- | --- | --- | | Whisper | $0.006 | Per minute of audio |

Cost examples: - 100 hours of audio/month: $36.00 - 1,000 hours of audio/month: $360.00

[Whisper](https://tokenmix.ai/blog/whisper-api-pricing) is highly cost-effective for transcription. The quality matches or exceeds most commercial transcription services at a fraction of the cost.

TTS (Text-to-Speech)

| Model | Price | Unit | | --- | --- | --- | | TTS | $15.00 | Per 1M characters | | TTS HD | $30.00 | Per 1M characters |

Cost examples (TTS standard): - 100K characters/month (~50K words): $1.50 - 1M characters/month (~500K words): $15.00

TTS HD provides higher-quality audio with better prosody and naturalness at 2x the cost.

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Cached Input Tokens: How to Save 90%

OpenAI's input caching automatically reduces costs for repeated input prefixes. This is one of the most impactful cost optimization tools available.

How Caching Works

When consecutive API requests share the same input prefix (system prompt, reference documents, few-shot examples), OpenAI automatically caches the shared tokens. Subsequent requests are charged at the cached input rate — 90% off standard pricing.

| Model | Standard Input | Cached Input | Discount | | --- | --- | --- | --- | | GPT-5.4 | $2.50/M | $0.25/M | 90% | | GPT-5.4 Mini | $0.75/M | $0.075/M | 90% | | GPT-5.4 Nano | $0.20/M | $0.02/M | 90% | | o3 | $2.00/M | $0.50/M | 75% | | o4-mini | $1.10/M | $0.275/M | 75% |

Note: Reasoning models (o3, o4-mini) offer 75% cache discounts, not 90%.

Caching Impact Example

System prompt: 15K tokens. User message: 2K tokens. 50,000 requests/month.

Without caching (all tokens at standard rate): - Input: (15K + 2K) x 50,000 x $2.50/M = $2,125

With caching (system prompt cached after first request): - Cached: 15K x 50,000 x $0.25/M = $187.50 - Uncached: 2K x 50,000 x $2.50/M = $250 - Total: **$437.50** (79% savings)

Caching is automatic — no code changes required. Just ensure your system prompt stays consistent across requests.

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Batch API: 50% Off for Async Workloads

OpenAI's [Batch API](https://tokenmix.ai/blog/openai-batch-api-pricing) processes requests asynchronously at half price, with results delivered within 24 hours.

Batch Pricing

| Model | Standard Output | Batch Output | Savings | | --- | --- | --- | --- | | GPT-5.4 | $15.00/M | $7.50/M | 50% | | GPT-5.4 Mini | $4.50/M | $2.25/M | 50% | | GPT-5.4 Nano | $1.25/M | $0.625/M | 50% | | o3 | $16.00/M | $8.00/M | 50% |

When Batch Makes Sense

Batch processing is ideal for: - Document classification or extraction pipelines - Content generation queues - Data labeling and annotation - Evaluation and testing workloads - Any workload where results within 24 hours is acceptable

Combined Savings: Cache + Batch

Applying both discounts simultaneously:

| Model | Standard Cost | Cache + Batch Cost | Total Savings | | --- | --- | --- | --- | | GPT-5.4 Input | $2.50/M | $0.125/M | 95% | | GPT-5.4 Output | $15.00/M | $7.50/M | 50% | | GPT-5.4 Mini Input | $0.75/M | $0.0375/M | 95% | | GPT-5.4 Mini Output | $4.50/M | $2.25/M | 50% |

At maximum discount, GPT-5.4 input costs $0.125/M — approaching DeepSeek V4's standard rate of $0.30/M. Output remains significantly more expensive ($7.50 vs $0.50).

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Fine-Tuning Costs

Fine-tuning OpenAI models incurs three cost components: training, input inference, and output inference.

Fine-Tuning Pricing

| Model | Training/M tokens | Fine-Tuned Input/M | Fine-Tuned Output/M | | --- | --- | --- | --- | | GPT-4o | $25.00 | $3.75 | $15.00 | | GPT-4o-mini | $3.00 | $0.30 | $1.20 |

Fine-tuned models cost 50-100% more on input inference than base models. The training cost is one-time per training run.

Fine-Tuning Cost Example

Training on 10M tokens, then running 1M inference requests (1K input + 500 output each): - Training: 10M x $25.00/M = $250 (one-time, GPT-4o) - Monthly inference input: 1M x 1K x $3.75/M = $3,750 - Monthly inference output: 1M x 500 x $15.00/M = $7,500 - Monthly total: **$11,250** + $250 training amortized

Fine-tuning makes economic sense when it reduces token usage (shorter prompts replace few-shot examples) or improves quality enough to reduce retry rates.

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OpenAI API Pricing vs Competitors

Flagship Model Comparison

| Model | Input/M | Output/M | Cached Input/M | SWE-bench | | --- | --- | --- | --- | --- | | **GPT-5.4** | $2.50 | $15.00 | $0.25 | ~80% | | Claude Sonnet 4.6 | $3.00 | $15.00 | $0.30 | ~73% | | Gemini 2.5 Pro | $1.25 | $10.00 | $0.315 | ~78% | | DeepSeek V4 | $0.30 | $0.50 | $0.07 | ~81% |

GPT-5.4 is the second most expensive flagship (after Claude) but offers the best coding performance among Western providers. Gemini undercuts GPT by 50% on input. DeepSeek is 8-30x cheaper.

Budget Model Comparison

| Model | Input/M | Output/M | | --- | --- | --- | | **GPT-5.4 Nano** | $0.20 | $1.25 | | **GPT-4o-mini** | $0.15 | $0.60 | | Gemini 2.0 Flash | $0.10 | $0.40 | | DeepSeek V4 | $0.30 | $0.50 |

At the budget tier, GPT-4o-mini and Gemini Flash offer the lowest absolute costs. GPT-5.4 Nano costs slightly more but delivers better quality.

TokenMix.ai provides unified access to all these models through a single API — compare real-time pricing and switch models without code changes at [tokenmix.ai](https://tokenmix.ai).

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Real-World Cost Scenarios

Scenario 1: Startup SaaS (10K users, 20 API calls each/month)

Average per call: 3K input, 1K output. Model: GPT-5.4 Mini.

| Component | Cost | | --- | --- | | Input (200K calls x 3K tokens) | $450 | | Output (200K calls x 1K tokens) | $900 | | **Monthly Total** | **$1,350** | | With caching (shared system prompt) | **~$550** |

Scenario 2: Enterprise Document Processing (50K docs/month)

Average per document: 20K tokens input, 2K output. Model: GPT-5.4.

| Component | Standard | Batch + Cache | | --- | --- | --- | | Input | $2,500 | $125 (cache + batch) | | Output | $1,500 | $750 (batch) | | **Monthly Total** | **$4,000** | **$875** |

Batch + cache saves 78% on this workload.

Scenario 3: AI Agent with Reasoning (5K complex tasks/month)

Average per task: 15K input, 50K output (including reasoning tokens). Model: o3.

| Component | Cost | | --- | --- | | Input (5K x 15K tokens) | $150 | | Output (5K x 50K tokens) | $4,000 | | **Monthly Total** | **$4,150** |

Reasoning model output costs dominate. Consider o4-mini at $4.40/M output if o3-level reasoning is not required — monthly output drops to $1,100.

Scenario 4: Image Generation Pipeline (5K images/month)

| Quality | Resolution | Monthly Cost | | --- | --- | --- | | Standard | 1024x1024 | $200 | | HD | 1024x1024 | $400 | | HD | 1024x1792 | $600 |

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How to Minimize Your OpenAI API Bill

Strategy 1: Use the Right Model Tier

Most workloads do not need GPT-5.4 Standard. Audit your API calls and route by complexity:

| Task Complexity | Model | Cost vs Standard | | --- | --- | --- | | Simple (classification, routing) | GPT-5.4 Nano | 92% cheaper | | Medium (chat, summaries) | GPT-5.4 Mini | 70% cheaper | | Complex (coding, analysis) | GPT-5.4 Standard | Baseline | | Extreme (proofs, research) | GPT-5.4 Pro | 12x more |

Strategy 2: Enable Caching

Keep system prompts and reference context consistent across requests. Caching is automatic and saves 90% on repeated input tokens.

Strategy 3: Use Batch Processing

Any workload that tolerates 24-hour latency should use the Batch API for 50% savings on all token costs.

Strategy 4: Optimize Prompts

Shorter prompts cost less. Remove redundant instructions, use concise few-shot examples, and trim system prompts to essential content. A 20% reduction in prompt length directly reduces cost by 20%.

Strategy 5: Route Through a Unified API

TokenMix.ai routes requests to the cheapest model that meets your quality threshold. Set quality requirements, and the platform automatically selects between GPT-5.4, Claude, Gemini, and DeepSeek based on task type and cost.

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Decision Guide: Choosing the Right OpenAI Model

| Your Need | Best OpenAI Model | Monthly Cost (100K requests) | | --- | --- | --- | | Cheapest possible | GPT-4o-mini | ~$115 | | Budget with better quality | GPT-5.4 Nano | ~$220 | | Production default | GPT-5.4 Mini | ~$790 | | Maximum quality | GPT-5.4 Standard | ~$2,625 | | Extended reasoning | o4-mini | ~$825 | | Research-grade reasoning | o3 | ~$2,700 | | Hardest problems only | GPT-5.4 Pro | ~$31,500 |

Estimates based on 3K input + 1.5K output tokens per request.

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**Related:** [Compare all model pricing in our complete LLM API pricing comparison](https://tokenmix.ai/blog/llm-api-pricing-comparison)

Conclusion

OpenAI API pricing in 2026 rewards optimization. The gap between naive usage ($2.50/$15 on everything) and optimized usage (right model + caching + batch) can exceed 90%. GPT-5.4 Nano handles simple tasks at $0.20/$1.25. Caching drops repeated input to $0.25/M. Batch cuts everything in half.

The competitive landscape matters too. Gemini 2.5 Pro undercuts GPT-5.4 by 50% on input. DeepSeek V4 is 8-30x cheaper. For cost-sensitive workloads, the right provider might not be OpenAI at all.

The practical strategy: use GPT-5.4 where its quality advantage justifies the premium (complex coding, critical production), and route cost-sensitive workloads to cheaper alternatives. TokenMix.ai makes this seamless through a single API with automatic model routing, caching, and provider failover.

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FAQ

How much does the OpenAI API cost in 2026?

OpenAI API pricing ranges from $0.15/$0.60 per million tokens (GPT-4o-mini) to $30/$180 (GPT-5.4 Pro). The most commonly used model, GPT-5.4 Standard, costs $2.50/M input and $15.00/M output. Caching reduces input to $0.25/M (90% off), and batch processing halves all prices.

What is the cheapest OpenAI model?

GPT-4o-mini at $0.15/$0.60 per million tokens is the cheapest. GPT-5.4 Nano at $0.20/$1.25 is the cheapest in the GPT-5.4 family with better quality and a larger 400K context window. For most new projects, GPT-5.4 Nano is the better budget choice.

How does ChatGPT API pricing work?

The ChatGPT API (now the OpenAI API) charges per token — separate rates for input tokens (what you send) and output tokens (what the model generates). There is no monthly subscription for API access; you pay only for what you use. Cached input tokens and batch processing offer significant discounts.

Is OpenAI API cheaper than Claude or Gemini?

Compared to Claude Sonnet 4.6 ($3.00/$15), GPT-5.4 ($2.50/$15) is 17% cheaper on input and equal on output. Compared to Gemini 2.5 Pro ($1.25/$10), GPT-5.4 is 2x more expensive on input and 50% more on output. DeepSeek V4 ($0.30/$0.50) is 8-30x cheaper than all of them. Use [TokenMix.ai](https://tokenmix.ai) to compare real-time pricing across all providers.

Does OpenAI offer a free API tier?

No ongoing free tier. New accounts may receive a small amount of free credits. After credits expire, all usage is pay-as-you-go. Google's Gemini API offers 1,500 free requests per day, making it the most accessible free option.

What is the difference between GPT-5.4 and GPT-5.4 Pro?

GPT-5.4 Pro ($30/$180) is 12x more expensive than Standard ($2.50/$15). Pro uses an extended reasoning budget that improves performance on the hardest problems: SWE-bench Pro improves from 49% to 57.7%, Terminal-Bench from 55% to 75.1%. Use Pro only when the quality improvement on hard tasks justifies the 12x cost multiplier.

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*Author: TokenMix Research Lab | Last Updated: April 2026 | Data Source: [OpenAI Official Pricing](https://openai.com/api/pricing/), [Anthropic Pricing](https://www.anthropic.com/pricing), [Google AI Pricing](https://ai.google.dev/pricing), [TokenMix.ai](https://tokenmix.ai)*