The new budget default for OpenAI API users: faster, cheaper, and smarter than GPT-4o with a context window that punches well above its price tier.
74
Coding
68
Writing
72
Research
0
Images
88
Value
82
Long Context
Use this when
High-volume production workloads — chatbots, summarization pipelines, and document Q&A — where cost efficiency matters more than peak reasoning.
Skip this if
You need deep multi-step reasoning, advanced mathematical problem-solving, or nuanced long-form creative writing — use GPT-5 or Claude Sonnet 4.6 instead.
Pricing
$0.25/1M in
$2.00/1M out
→0%since May 2026
Context
400k tokens
Speed
Very fast
GPT-5 Minispecs & pricing
Verified Sep 4, 2026 against the AI Gateway catalog
Output cost of $2/1M tokens is higher than some competing budget models (Gemini Flash at ~$0.60/1M output). At scale, output-heavy tasks may erode cost advantages — monitor token ratios carefully. Supersedes GPT-4o, which may be deprecated on a rolling basis.
Extremely affordable at $0.25/$2 per 1M tokens, undercutting Claude Haiku 3.5 and Gemini 2.0 Flash on price-per-output
400K context window is unusually large for a budget model, enabling full-codebase or long-document analysis
Inherits GPT-5's improved instruction adherence and structured output reliability over GPT-4o
Well-suited for chained agentic tasks where many cheap calls replace a few expensive ones
Weaknesses
Noticeably weaker on complex multi-step reasoning compared to GPT-5, Claude Sonnet 4.6, or Gemini 3.1 Pro
Creative writing quality lags behind full GPT-5 and Claude's writing-tuned models
No native image generation; multimodal input support depends on OpenAI's rollout specifics
Real-world use cases
What people actually use GPT-5 Mini for.
Ingesting a 300-page legal contract and extracting clause summaries with structured JSON output
Powering a customer support chatbot handling 10,000+ daily conversations within a tight API budget
Auto-generating unit tests and docstrings for a mid-size Python codebase uploaded in a single context window
How GPT-5 Mini compares
The nearest models people weigh against it, and what actually separates them.
vs Claude 3.5 Haiku — Against Claude 3.5 Haiku (Anthropic), GPT-5 Mini runs about 53% cheaper per token and takes 2x the context. Take GPT-5 Mini unless you specifically need what Claude 3.5 Haiku does better.
vs GPT-3.5 Turbo (older v0613) — Against GPT-3.5 Turbo (older v0613) (OpenAI), GPT-5 Mini runs about 25% cheaper per token and takes 97.7x the context. Take GPT-5 Mini unless you specifically need what GPT-3.5 Turbo (older v0613) does better.
vs GPT-4 Turbo — Against GPT-4 Turbo (OpenAI), GPT-5 Mini runs about 94% cheaper per token, takes 3.1x the context and answers faster. Take GPT-5 Mini unless you specifically need what GPT-4 Turbo does better.
Price History
GPT-5 Mini pricing over time
→0% since May 30
90 data points · tracked daily since May 30, 2026
Ready to try it?
Start using GPT-5 Mini
High-volume production workloads — chatbots, summarization pipelines, and document Q&A — where cost efficiency matters more than peak reasoning.. Start free — no card required.
Claude 3.5 Haiku is Anthropic's fastest and most affordable model in the Claude 3.5 family, designed for high-throughput tasks requiring quick responses without sacrificing Claude's core instruction-following quality. It handles a massive 200K context window while maintaining speed suitable for production pipelines.
Verdict
The fastest way to get Claude's quality in production — just don't confuse 'fast' with 'cheap'.
Quality score
64%
Pricing
$0.80/1M in
$4.00/1M out
Speed
Very fast
5/5 speed
Context
200k tokens
Output cost of $4/1M is notably higher than competing fast/mini models. Input cost at ~$0.80/1M is competitive. Best value emerges in input-heavy pipelines like document classification or RAG retrieval where output tokens are minimal.
High-volume, latency-sensitive applications like chatbots, classification, data extraction, and agentic tool use where speed and cost matter more than peak reasoning depth.
An older versioned snapshot of GPT-3.5 Turbo (v0613), OpenAI's once-dominant mid-tier language model optimized for fast chat completions and instruction following. This specific checkpoint is frozen in time, predating later capability improvements introduced in subsequent GPT-3.5 Turbo updates.
Verdict
A once-useful workhorse now completely overshadowed by cheaper, more capable successors.
Quality score
31%
Pricing
$1.00/1M in
$2.00/1M out
Speed
Very fast
5/5 speed
Context
4k tokens
This is a pinned legacy snapshot (v0613) and may eventually be deprecated by OpenAI. The 4,095-token context window is its most significant practical limitation. OpenAI's own GPT-4o mini offers drastically more context and better quality at a comparable price — strongly consider migrating.
LegacyBudgetFastShort ContextOpenAI
Best for
High-volume, cost-sensitive text tasks like classification, summarization, and simple Q&A where bleeding-edge quality is not required.
GPT-4 Turbo is OpenAI's high-capability flagship model featuring a 128K context window, trained on data up to April 2024. It delivers strong reasoning, coding, and instruction-following across complex tasks.
Verdict
A capable but aging flagship that has been outpaced by cheaper, faster successors in OpenAI's own lineup.
Quality score
75%
Pricing
$10.00/1M in
$30.00/1M out
Speed
Balanced
3/5 speed
Context
128k tokens
GPT-4 Turbo is available via the OpenAI API. It has largely been succeeded by GPT-4o, which is faster, supports vision natively, and is cheaper. Organizations should evaluate whether migrating to GPT-4o or o3 makes more sense before building new workflows on this model.
OpenAI: GPT-5 Mini (OpenAI) is now indexed. It supersedes GPT-4o. The new budget default for OpenAI API users: faster, cheaper, and smarter than GPT-4o with a context window that punches well above its price tier.
GPT-5 Mini costs $0.25 per million input tokens and $2 per million output tokens on the API, with cached input at $0.025 per million. A month of 10M input and 2M output tokens runs about $6.50 at list price, before any batch or caching discounts.
What is the context window of GPT-5 Mini?
GPT-5 Mini has a 400k tokens context window, with up to 128k tokens of output per response. That is the total of prompt plus response the model can hold in one request.
What is the knowledge cutoff of GPT-5 Mini?
GPT-5 Mini's training data runs through May 30, 2024, and the model was released on August 7, 2025. For anything after that date it needs web search or documents in the prompt.
What is GPT-5 Mini best for?
GPT-5 Mini is best for high-volume production workloads — chatbots, summarization pipelines, and document q&a — where cost efficiency matters more than peak reasoning.. It is a strong fit when that workflow matters more than the tradeoffs around budget pricing and very fast speed.
When should I avoid GPT-5 Mini?
You need deep multi-step reasoning, advanced mathematical problem-solving, or nuanced long-form creative writing — use GPT-5 or Claude Sonnet 4.6 instead.
What is a cheaper alternative to GPT-5 Mini?
GPT-5.1-Codex-Max (OpenAI) at $1.25/1M/1M input against GPT-5 Mini's $0.25/1M/1M. The strongest choice for serious software engineering work, provided you can absorb the output-side pricing. Compare it first if GPT-5 Mini's pricing is the thing stopping you.
What is a faster alternative to GPT-5 Mini?
Claude 3.5 Haiku — very fast against GPT-5 Mini's very fast, with 200k tokens of context. Worth the swap when response time is what your users notice rather than the last few points of reasoning depth.
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