GPT-5 vs GPT-5 mini
Benchmarks, API Token Pricing, Context Window & Speed Comparison
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GPT-5 by OpenAI and GPT-5 mini by OpenAI represent two of the frontier AI models analyzed in our comprehensive 2026 AI benchmark and LLM comparison. In this head-to-head evaluation, we examine API token pricing, context window specifications, inference speed (tokens per second), and empirical reasoning performance. From a pure economic perspective, GPT-5 mini holds a notable pricing advantage for token ingestion. On output generation, GPT-5 mini is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, both models provide an identical memory horizon with 400K tokens. In latency-sensitive production environments, GPT-5 mini leads in tokens-per-second throughput, making it ideal for real-time conversational agents and high-concurrency workflows. Below is the complete empirical head-to-head breakdown across cost, speed, context, and capability matrices.
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GPT-5
Unified ReasonerA single model with both fast and reasoning modes, covering reasoning, coding, writing and tool use.
$1.25 / 1M
$10.00 / 1M
400K tokens
74.9%
GPT-5 mini
Efficient GPT-5A smaller GPT-5 tuned for responsive agents and everyday automation.
$0.25 / 1M
$2.00 / 1M
400K tokens
52%
Key Differences at a Glance
- GPT-5 mini is 5.0x cheaper for API usage (input + output tokens combined).
- GPT-5 mini is faster at 185 tok/s vs 135 tok/s.
- GPT-5 leads on SWE-bench coding (74.9% vs 52.0%).
| Feature | GPT-5 | GPT-5 mini |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 58 | 46 |
Provider | OpenAI | OpenAI |
Input Price Cost per million input tokens | $1.25 / 1M | $0.25 / 1M |
Output Price Cost per million output tokens | $10.00 / 1M | $2.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $1.34 / 1M | $0.27 / 1M |
Context Window Maximum input + output tokens | 400K tokens~600 A4 pages of text | 400K tokens~600 A4 pages of text |
Max Output Tokens Per single request | 128K | 128K |
Throughput Speed Tokens generated per second | 135 tok/s | 185 tok/s |
SWE-bench Verified Real-world software engineering | 74.9% | 52% |
GPQA Diamond Graduate-level reasoning | 85.7% | 66% |
Cached Input Price Prompt caching discount per 1M tokens | $0.13 / 1M | $0.03 / 1M |
Who Wins Where?
At-a-glance decision frameworkEmpirical Head-to-Head Benchmark Scores
Official evaluation metrics verified by independent third-party research labs.
Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.
Challenging questions created by domain experts to test complex PhD-level reasoning.
Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.
Crowdsourced human preference evaluation based on blind, head-to-head model battles.
Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.
Autonomous multi-step tasks executed inside a real command-line terminal environment.
Research-grade coding problems drawn from real scientific and numerical workloads.
Contamination-free competitive programming problems collected continuously over time.
American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.
Accuracy when reasoning over very large inputs that fill the model context window.
Tokens emitted per second during active generation streaming.
Latency & Response Time
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Real-Time Interactive Token Cost Simulator
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
GPT-5 · Strengths & Key Advantages
- One model with both fast and thinking modes
- Strong agentic coding and tool use
- Aggressively priced for a frontier model
- Adjustable reasoning effort for cost control
Considerations & Trade-offs
- At peak reasoning effort it still trails Claude and Gemini flagships
- High-effort thinking noticeably increases latency and cost
GPT-5 mini · Strengths & Key Advantages
- Cheap, fast and still capable of reasoning
- Retains the full 400K context window
- Reliable tool calling for agent workflows
- Handles multimodal input well for its size
Considerations & Trade-offs
- Substantially weaker than full GPT-5 on hard tasks
- Struggles with long, ambiguous multi-step plans
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | GPT-5 | GPT-5 mini |
|---|---|---|
Cost per Task Estimated USD to finish one task | $1.55 | $0.32 |
Output Tokens / Task Tokens generated per task | 55K | 50K |
Reasoning Tokens / Task Thinking tokens burned per task | 29K | 24K |
Technical Specifications
Architecture, release timeline, capabilities, and modalities.
| Feature | GPT-5 | GPT-5 mini |
|---|---|---|
| Official API Model ID (SDK) | gpt-5 | gpt-5-mini |
| API Protocol | OpenAI Responses API & Chat Completions v1 | OpenAI Responses API & Chat Completions v1 |
| Release Date | 2025-08 | 2025-08 |
| Knowledge Cutoff | September 2024 | September 2024 |
| Architecture | Unified reasoning model (fast + thinking modes) | Compact unified reasoning model |
| Parameters | Confidential | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM | 10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($1.25/1M in) across full 400K window | Flat rate ($0.25/1M in) across full 400K window |
| Prompt Cache Policy & TTL | Automatic prefix caching at $0.125/1M (no extra cache-write fee) | Automatic prefix caching at $0.025/1M (no extra cache-write fee) |
| Computer Use / GUI Agent | Supported (Screen coordinate grounding, browser & desktop GUI action loops) | Supported (Screen coordinate grounding, browser & desktop GUI action loops) |
| MCP & Parallel Tool Calling | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema |
| Web Search Grounding & Sandbox | Native Web Search tool + Hosted Code Interpreter & File Search RAG | Native Web Search tool + Hosted Code Interpreter & File Search RAG |
| Official Fine-Tuning Support | Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT) | Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT) |
| Multimodal Token Billing | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) |
| Quantization & Min GPU VRAM | Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API) | Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API) |
| Safety & Frontier Classification | OpenAI Preparedness Framework Audited & System Card Published | OpenAI Preparedness Framework Audited & System Card Published |
| Enterprise Compliance (ZDR/HIPAA/SOC2) | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier |
| Input Modalities | text, vision | text, vision |
| Output Modalities | text | text |
GPT-5 vs GPT-5 mini: Quick Answers
Which is more intelligent, GPT-5 or GPT-5 mini?
GPT-5 is more intelligent. It scores 58 compared with 46 on the composite Intelligence Index.
Which model is faster?
GPT-5 mini is faster, generating 185 tokens per second compared with 135 tokens per second.
Which model is cheaper to run?
GPT-5 mini is cheaper at $0.27 per 1M tokens blended, compared with $1.34 (7:2:1 cache:input:output ratio).
Which model has lower latency?
GPT-5 mini has lower latency, with a time to first token of 0.70s compared with 1.15s.
Verdict
Verdict & Model Selection Recommendation: Choose GPT-5 if your priority is A default frontier model for production apps and agents. Its performance in demanding tasks justifies its operational token cost. Choose GPT-5 mini if your workflow prioritizes Cost-sensitive agents, assistants and coding help. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.
Frequently asked questions
How does GPT-5 compare to GPT-5 mini in API token pricing and cost per token?+
GPT-5 costs $1.25 per 1M input tokens and $10.00 per 1M output tokens, whereas GPT-5 mini costs $0.25 input and $2.00 output. Overall, GPT-5 mini is the more cost-effective model for high-volume API pipelines. Both models support prompt caching discounts of up to 90% for repeated prompt prefixes.
Which model has a larger context window: GPT-5 or GPT-5 mini?+
Both GPT-5 and GPT-5 mini offer an identical context window of 400K tokens (~300k words). Both architectures provide equal capacity for large document ingestion, multi-file codebases, and extended multi-turn conversation histories.
Which AI model is better for software engineering and coding: GPT-5 or GPT-5 mini?+
GPT-5 scores 74.9% on SWE-bench Verified while GPT-5 mini scores 52%. For autonomous software engineering and multi-file debugging, GPT-5 holds the verified benchmark lead.
What is the difference in reasoning capability and extended thinking between GPT-5 and GPT-5 mini?+
GPT-5 features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, GPT-5 mini provides chain-of-thought reasoning depth for complex math and science.
How does inference speed (tokens per second) compare between GPT-5 and GPT-5 mini?+
GPT-5 generates approximately 135 tokens per second, while GPT-5 mini delivers 185 tokens per second. In latency-sensitive production environments, GPT-5 mini provides faster time-to-first-token (TTFT) and higher streaming response velocity.
Can you implement a tiered LLM routing setup combining GPT-5 and GPT-5 mini to optimize costs?+
Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to GPT-5 mini to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to GPT-5. This tiered routing pattern cuts overall API bills by up to 70%.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
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Benchmark scores, token prices, and rate limits evolve rapidly as AI labs release model updates. Always verify current specifications and pricing on the official provider documentation.
Sources: GetInfoUs Independent AI Benchmarks & Official API Specs