At $2/1M output tokens, costs can accumulate in verbose code-generation tasks — monitor output token usage carefully in agentic loops. Not a general-purpose flagship replacement; best deployed alongside a stronger model for planning/reasoning layers.
Exceptional value for code tasks at $0.25/1M input tokens — roughly 10x cheaper than GPT-5.1 flagship
400K context window handles large repositories, multi-file diffs, and long test suites in a single pass
Codex-tuned weights give it an edge over generic budget models like GPT-4o-mini on syntax accuracy and boilerplate generation
Fast inference makes it suitable for real-time IDE integrations and agentic coding loops
Weaknesses
Weaker at complex multi-step algorithmic reasoning compared to full GPT-5.1 or Claude Sonnet 4.6
Non-code creative writing and nuanced instruction-following lag behind frontier models
No native image input support limits multimodal coding tasks like UI-from-screenshot generation
Real-world use cases
What people actually use GPT-5.1-Codex-Mini for.
Generating boilerplate REST API endpoints across a 50-file codebase loaded in full context
Running automated code review comments on large pull requests in a CI/CD pipeline
Powering an IDE autocomplete plugin that requires low-latency, high-throughput inference
How GPT-5.1-Codex-Mini compares
The nearest models people weigh against it, and what actually separates them.
vs GPT-5 Mini — Against GPT-5 Mini (OpenAI), GPT-5.1-Codex-Mini lands within a few percent on price. Which one wins depends on whether context depth or latency is your constraint.
vs Claude 3.5 Haiku — Against Claude 3.5 Haiku (Anthropic), GPT-5.1-Codex-Mini runs about 53% cheaper per token and takes 2x the context. Take GPT-5.1-Codex-Mini unless you specifically need what Claude 3.5 Haiku does better.
vs Devstral 2 2512 — Against Devstral 2 2512 (Mistral), GPT-5.1-Codex-Mini runs about 6% cheaper per token, takes 1.5x the context and answers faster. Take GPT-5.1-Codex-Mini unless you specifically need what Devstral 2 2512 does better.
Price History
GPT-5.1-Codex-Mini pricing over time
→0% since May 30
90 data points · tracked daily since May 30, 2026
Ready to try it?
Start using GPT-5.1-Codex-Mini
High-volume code generation, autocomplete pipelines, and developer tooling where cost efficiency matters more than peak reasoning depth.. Start free — no card required.
GPT-5 Mini is OpenAI's budget-tier distillation of GPT-5, designed for high-volume, cost-sensitive tasks that don't require full flagship reasoning depth. It supersedes GPT-4o with improved instruction following and a massively expanded 400K context window at a fraction of the cost.
Verdict
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.
Quality score
66%
Pricing
$0.25/1M in
$2.00/1M out
Speed
Very fast
5/5 speed
Context
400k tokens
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.
BudgetFastLong ContextHigh VolumeOpenAI
Best for
High-volume production workloads — chatbots, summarization pipelines, and document Q&A — where cost efficiency matters more than peak reasoning.
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.
Devstral 2 2512 is Mistral's second-generation code-specialized model, built specifically for software development tasks with a 256K context window. It targets developers needing a cost-efficient coding assistant without sacrificing meaningful capability.
Verdict
A purpose-built coding workhorse that punches well above its price tag for development teams running high-volume or agentic pipelines.
Quality score
55%
Pricing
$0.40/1M in
$2.00/1M out
Speed
Fast
4/5 speed
Context
262k tokens
The December 2025 (2512) release date suggests this is a recent iteration. Pricing at $0.40 input / $2.00 output is notably competitive for a code-specialist model with 256K context. Verify availability and rate limits via Mistral API or partner providers.
Code-specialistBudgetLong contextAgenticMistral
Best for
Budget-conscious developers who need a capable coding model for agentic workflows, code generation, and repository-scale context at a fraction of flagship pricing.
Pricing moves, ranking shifts, and capability updates.
New ModelMar 27, 2026
OpenAI: GPT-5.1-Codex-Mini — added to UseRightAI
OpenAI: GPT-5.1-Codex-Mini (OpenAI) is now indexed. It supersedes GPT-4o. The sharpest budget coding model available if you need speed, volume, and a long context window without breaking your API budget.
GPT-5.1-Codex-Mini costs $0.25 per million input tokens and $2 per million output tokens on the API, with cached input at $0.03 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-5.1-Codex-Mini?
GPT-5.1-Codex-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-5.1-Codex-Mini?
GPT-5.1-Codex-Mini's training data runs through September 30, 2024, and the model was released on November 12, 2025. For anything after that date it needs web search or documents in the prompt.
What is GPT-5.1-Codex-Mini best for?
GPT-5.1-Codex-Mini is best for high-volume code generation, autocomplete pipelines, and developer tooling where cost efficiency matters more than peak reasoning depth.. 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-5.1-Codex-Mini?
You need deep mathematical reasoning, complex architecture design decisions, or multimodal inputs — use GPT-5.1 or Claude Sonnet 4.6 instead.
What is a cheaper alternative to GPT-5.1-Codex-Mini?
GPT-5.1-Codex-Max (OpenAI) at $1.25/1M/1M input against GPT-5.1-Codex-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-5.1-Codex-Mini's pricing is the thing stopping you.
What is a faster alternative to GPT-5.1-Codex-Mini?
GPT-5 Mini — very fast against GPT-5.1-Codex-Mini's very fast, with 400k 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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