GPT API Family
Use one EvoLink API to access GPT-5 models. Compare GPT-5.5, GPT-5.4, GPT-5.2, and GPT-5.1 on API pricing, context window, reasoning fit, and capabilities — then pick the right model for your workload.
4 models
Covers different strengths and cost tiers
Unified API access
OpenAI compatible, fast onboarding
Choose by workflow
Match model to task before integrating
Compare the GPT models
Choose based on your primary constraint: reasoning depth, context length, or cost.
| Model | Best for | Input / MTok | Output / MTok | Context | Cached input |
|---|---|---|---|---|---|
GPT-5.5 Flagship | Advanced reasoning, demanding workflows, and newer GPT-5.5 API evaluation. | $4.00 | $24.00 | 1M | $0.40 |
GPT-5.4 Previous Flagship | Complex reasoning, 1M+ context analysis, computer use, and agent orchestration. | $2.00 | $12.00 | 1.05M | $0.20 |
GPT-5.2 Best Value | Production coding, reasoning, and multi-turn conversations at 400K context. | $1.75 | $14.00 | 400K | $0.175 |
GPT-5.1 Budget | High-volume tasks where cost matters most: summarization, classification, and generation. | $1.25 | $10.00 | 400K | $0.125 |
How to decide which GPT model to use
Follow these 4 rules to narrow down your choice.
Start with task complexity
Complex reasoning, code generation, multi-turn tool use, and high-accuracy output — start with GPT-5.5.
Then check context length
Long documents, codebases, logs, research papers, multi-turn history — compare GPT-5.4.
Then check call frequency
Support, summarization, classification, tagging, batch text processing — compare GPT-5.2 or GPT-5.1.
Finally, consider whether to fix a model
If the same workflow mixes light and heavy tasks, consider EvoLink Smart Router instead of hardcoding one model for every step.
Smart Router →If you already know your task type, find the recommended starting point in the table below.
Choose a GPT model by workflow: reasoning, coding, summarization, and high-volume tasks
Match your primary task to the right GPT model.
| Your task | Recommended start | Good fit if... | Watch out for |
|---|---|---|---|
| Complex reasoning and coding | GPT-5.5 | You need higher accuracy, multi-step reasoning, code generation, tool use, or complex problem decomposition | Higher cost — not recommended for simple high-frequency tasks |
| Long document or codebase analysis | GPT-5.4 | Your input is long — contracts, papers, logs, codebases, or multi-turn context | Watch input token cost — estimate context size first |
| Everyday Q&A, summarization, classification | GPT-5.2 | You need stable results while keeping cost under control | Good default starting point for most production tasks |
| High-frequency lightweight tasks | GPT-5.1 | Tasks are simple, call volume is high, cost sensitivity is primary | Not suited for complex reasoning or high-value outputs |
| Mixed-complexity text tasks | EvoLink Smart Router | Same workflow has both simple and complex tasks | Best when you don't want to maintain manual model routing logic |
GPT API workflows: agents, chat, summarization, and content processing
See how GPT models fit into real products, agents, and content processing pipelines.
Reasoning and coding
For code generation, bug fixing, test case generation, complex logic analysis, and tool-calling agents. If the output directly affects product quality or development efficiency, start testing with GPT-5.5. If context is especially long, compare GPT-5.4.
High-volume chat and support
For support bots, in-app assistants, knowledge base Q&A, and high-frequency multi-turn conversations. If per-request value is low but call volume is high, test with GPT-5.2 first, then stress-test cost with GPT-5.1.
Summarization and classification
For long-text summaries, tag classification, structured extraction, review categorization, and batch content processing. These tasks usually don't need the strongest model — GPT-5.2 often strikes a better balance between quality and cost.
Agent routing and mixed text tasks
For workflows where simple classification, retrieval, reasoning, and generation coexist in the same pipeline. If you don't want to hardcode a model for every step, use EvoLink Smart Router to handle routing at the API layer via evolink/auto.
Explore each GPT model
Use this page to compare, then visit individual model pages for pricing details, playground access, and integration guides.
Access GPT models through one EvoLink API
All GPT models are available through a single EvoLink API key and OpenAI-compatible endpoint. Switch between GPT-5.5, GPT-5.4, GPT-5.2, and GPT-5.1 by changing the model parameter — no separate accounts or keys needed.
Switch model="gpt-5.5" to model="gpt-5.2" without rebuilding your integration.How to think about GPT API cost: complex reasoning, long context, and high-frequency tasks
Complex reasoning amplifies output cost
Complex reasoning, code generation, and multi-turn tool use tend to produce longer outputs and work best with higher-capability models. If task value is high, GPT-5.5 quality may matter more than cost. For simple tasks, don't default to the most capable model.
Long context amplifies input cost
Document analysis, codebase understanding, log processing, and research summarization bring large input token volumes. If the bottleneck is input length rather than reasoning depth, GPT-5.4 may be more appropriate.
High-frequency tasks need low unit cost
Support, summarization, classification, and tagging at high volume should prioritize unit cost. Test with GPT-5.2 for quality first, then try GPT-5.1 to see if you can reduce cost further.
Pricing summary
All GPT-5 models use per-token pricing with cached input discounts. EvoLink lists current pricing on each model page, including GPT-5.5 and GPT-5.4 routes.
GPT-5.5
$4.00 input
$24.00 output
Context: 1M
Newest GPT option on EvoLink with 1M context, 128K max output, and tool support. EvoLink pricing: $4.00/$24.00 per 1M tokens (20% below OpenAI direct).
GPT-5.4
$2.00 input
$12.00 output
Context: 1.05M
Lower-cost established GPT route with 1.05M context, computer use, and 20% EvoLink discount ($2.00/$12.00).
GPT-5.2
$1.75 input
$14.00 output
Context: 400K
Best value for production reasoning and coding workloads at 400K context.
GPT-5.1
$1.25 input
$10.00 output
Context: 400K
Budget tier for high-volume tasks where cost matters most.
Related GPT guides
Use the family page to compare models, then visit guides for pricing details, comparisons, and integration.
GPT-5 API Pricing Guide 2026
Complete pricing breakdown for every GPT-5 model — base rates, cached input, EvoLink discounts, and cost optimization tips.
GPT-5.4 vs Claude Opus 4.6 vs Gemini 3.1 Pro
Three-way flagship comparison with pricing tables, benchmarks, and decision framework.
GPT-5.4 Pricing Deep Dive: Tiers, Caching & EvoLink Discount
GPT-5.4 specific pricing details including >272K input tier, cached input rules, and EvoLink 20% discount breakdown.
GPT-5.2 vs Gemini 3 Pro Comparison
Head-to-head comparison of GPT-5.2 and Gemini 3 Pro on pricing, benchmarks, and use cases.
Best LLM for Coding Agents
Compare Claude, GPT, DeepSeek, Qwen Coder, and Gemini for coding agent workloads — API cost, tool-call reliability, and fallback planning.
GPT API Family FAQ
Everything you need to know about the product and billing.