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GPT-5.4 nano

OpenAIbudget

OpenAI's ultra-efficient budget model designed for high-volume production workloads. Supports tool calling and MCP natively with a 400K context window at just $0.20/M input tokens. Replaces GPT-4o-mini as the go-to budget option.

Released 2026-03-12Knowledge cutoff: 2025-11
Medium confidence|Updated 56d ago|88% source confidence

Specifications

Context Window

400K tokens

Max Output

16.4K tokens

Input Price

$0.200 / 1M tokens

Output Price

$1.25 / 1M tokens

Latency Tier

Ultra Fast (speed score: 9.5/10)

Capability Profile

Speed
9.5/10
Cost Efficiency
9.5/10
Structured Output
8.5/10
Tool Use
8.5/10
Instruction Following
8/10
Safety & Enterprise
8/10
Long Context
7.5/10
Conversational
7.5/10
Coding
7/10
Factuality
7/10
Reasoning
6.5/10
Creativity
6/10
Multimodal
1/10

Feature Support

Vision No
Audio In No
Audio Out No
Video No
Image Generation No
Image Editing No
Function Calling Yes
JSON Mode Yes
Structured Output Yes
Streaming Yes
Reasoning No
Realtime No
Computer Use No
Web Search No

Best Use Cases

High-volume classification, extraction, and routing tasks
MCP-connected tool orchestration where the LLM is a dispatcher
Budget-friendly chatbot and customer support deployments
Structured data extraction from documents at scale
Pre-filtering and triage before escalation to a stronger model

Not Ideal For

Complex multi-step reasoning or mathematical proofs
Creative writing requiring depth and nuance
Multimodal tasks — text only, no vision
Expert-level code architecture decisions

Strengths

Native MCP support makes it an excellent tool-orchestration backbone
Exceptional cost-to-performance ratio — the cheapest GPT-5 family model
Very low latency with high throughput for interactive applications
Reliable JSON mode and function calling despite small size
400K context at budget pricing is remarkable

Weaknesses

No vision or multimodal capabilities
Noticeable quality drop on complex reasoning chains vs mini
Can be overconfident on topics it lacks knowledge about
Creative output is generic and formulaic
Struggles with ambiguous or underspecified prompts

Edge Cases & Notes

MCP tool-use capability is genuinely useful for agentic pipelines at this price
Batch API at 50% discount makes it $0.10/M input — approaching open-model self-host costs
Long context quality is good up to ~200K but degrades past that

Provider Notes

The new default for cost-sensitive OpenAI workloads. Batch API recommended for non-interactive use. Available on Azure OpenAI Service.

Benchmarks

MMLU82%
HumanEval85.7%
Arena Elo1240

Benchmark Notes

MMLU-Pro 82%. Significantly better than GPT-4o-mini on all benchmarks while being cheaper. HumanEval 85.7% shows solid coding for a budget model.

Research Meta

Last Evaluated

2026-04-01

Source Confidence

88%

Evaluation Method

Public benchmarks, cost-quality Pareto analysis, MCP tool-use evaluation

Needs Re-evaluation

No

Sources

  • OpenAI GPT-5.4 nano announcement (Mar 2026)
  • LMSYS Chatbot Arena
  • Artificial Analysis

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