GPT-4.1 mini
Compact April 2025 model offering 200k context, near-instant inference, and sub-dollar token economics for high-scale agent fleets.
200k
~150k words input
$0.12 / $0.48
Prompt / Completion per 1M
84.5 % pass@1
MMLU
Cloud Managed
Zero local VRAM
Holistic Capability Distribution
Normalized 0-100 rating vectors balanced across intelligence, throughput, and economics.
Verified LLM Benchmarks
Empirical evaluations across academic reasoning, software engineering, agentic execution, and human preference.
Inference Latency & Generation Throughput
Empirical telemetry benchmarking generation throughput (Tokens/Second) and Time to First Token (TTFT).
Measured under concurrent production load
p95 latency: 490 ms
Across 4,800 monitored requests
Architectural Strengths vs. Operational Considerations
An objective technical balance sheet analyzing deployment advantages and production constraints.
Key Architectural Strengths
- Extremely low cost: $0.12 input / $0.48 output per 1M tokens.
- Sub-200ms time to first token with 135 tps emission.
- Expanded 200k context window.
Operational Considerations
- Complex multi-file software engineering requires larger models.
Hardware & Execution Parameters
Genealogical Provenance
Next iteration in OpenAI's ultra-cheap compact line.
openai gpt 4o mini
GPT-4.1 mini
Architecture Engineering & Capability Deep-Dive
Topology & Attention Mechanics
Distilled dense model optimized for memory bandwidth efficiency.
Evaluation Profile & Reasoning Capabilities
Fast intent matching, semantic filtering, and lightweight text transforms.
Inference Economics & Cost Optimization
Near-zero cost per interaction.
Primary Production Workloads & Suitability
Cloud Deployment Architecture & Hardware Sizing
Cloud Deployment Architecture
Distributed enterprise serving infrastructure, autoscaling semantics, and runtime execution profile.
Proprietary commercial model hosted on managed multi-region clusters with automatic autoscaling, high availability, and prompt prefix caching.
Multi-Tenant Cloud API
Continuous autoscaling with regional failover
0 GB Local VRAM
Inference executed on hyperscaler accelerator clusters
200k tokens
Supported with automated KV cache prefix compression
SDK Installation
Official Repositories & Papers
Compare Showdowns
GPT-4.1 mini vs GPT-4o mini
Compare GPT-4.1 mini against GPT-4o mini's verified benchmarks, context window, and pricing.
GPT-4.1 mini vs GPT-4.1 nano
Compare GPT-4.1 mini against GPT-4.1 nano's verified benchmarks, context window, and pricing.
GPT-4.1 mini vs OpenAI Decisions
Compare GPT-4.1 mini against OpenAI Decisions's verified benchmarks, context window, and pricing.
GPT-4.1 mini vs GPT-3.5 Turbo
Compare GPT-4.1 mini against GPT-3.5 Turbo's verified benchmarks, context window, and pricing.
Commercial Token Rates & Cost Estimator
$0.12 / 1M
Standard prompt context ingestion
$0.48 / 1M
Generated completion & thinking tokens
$0.03 / 1M
Re-used prompt prefix context
Monthly Production Cost Simulator
$27.00
Includes prompt caching
-$5.40
Saved via prefix context caching
Comparable Foundation Architectures
Alternative foundation models with comparable intelligence benchmarks, context windows, and deployment profiles.
GPT-4o mini
OpenAI's most cost-efficient compact multimodal model, replacing GPT-3.5 Turbo with superior intelligence, 128k context, and fractional pricing ($0.15/$0.60).
GPT-4.1 nano
OpenAI's micro-footprint foundation model optimized for ultra-low latency edge devices, sub-100ms routing, and pennies-per-million token economics ($0.05/$0.20).
OpenAI Decisions
OpenAI Decisions is OpenAI's dedicated high-throughput decision-making API powered by GPT-6 Luna, accessed via the POST /v1/decisions endpoint. Designed for agent routing, automated content moderation, and classification, it processes typed questions (predicates, categorical choices, and rubric scores) roughly 10x faster than standard generation, billed at $0.10 per million input tokens with zero output-token fees.
GPT-3.5 Turbo
OpenAI's foundational conversational model that launched the ChatGPT era, optimized for fast dialogue, summary generation, and lightweight JSON tasks.
SDK Installation & API Integration
import OpenAI from 'openai';
const client = new OpenAI();
const completion = await client.chat.completions.create({
model: 'gpt-4.1-mini',
messages: [{ role: 'user', content: 'Ping' }],
});
console.log(completion.choices[0].message.content);Frequently Asked Questions about GPT-4.1 mini
Engineering specifications, VRAM sizing, commercial licensing terms, token economics, and empirical benchmark evaluations.
Use GPT-4.1 mini when serving high-volume production traffic where latency and price are critical.