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OpenAI · GPT
No. 10
GPT-5.4 mini
Affordable OpenAI workhorse for standard production routing.
Field notes
- Context window
- 400Ktokens
- Max output
- 128Ktokens
- Input price
- $0.75/ 1M tokens
- Output price
- $4.50/ 1M tokens
- Cached input
- $0.07/ 1M tokens
- Modalities
- Text, Image, Pdf
- Knowledge cutoff
- Oct 2025
- Released
- Mar 2026
- Approx. speed
- —
Overview
What this model is
GPT-5.4 mini is OpenAI's affordable production workhorse, handling the bulk of standard routed traffic at a fraction of flagship cost. It delivers solid reasoning and coding for everyday tasks with a 400K context and full multimodal input, and is a strong default for cost-conscious applications that escalate to GPT-5.5 for the hardest jobs.
Strengths
- Strong value for standard production work
- Good coding and reasoning for the price
- 400K-token context and multimodal input
- Fast and cheap enough for high volume
- Steep prompt-cache discount
Trade-offs
- Not frontier-reliable for long-horizon agentic coding
- Below flagship on hard reasoning
- Smaller context than the 5.4/5.5 flagships
Best for
- Standard production routing
- Cost-sensitive coding assistants
- Chat and support backends
- RAG and summarization at scale
- Lightweight agents
Not ideal for
- Hard autonomous coding runs
- Frontier research-grade reasoning
Capabilities
Capability profile
Normalized 0–100 scores, comparable across the whole catalog.
- Reasoning
- 84
- Coding
- 82
- Math
- 85
- Writing
- 85
- Knowledge
- 84
- Speed
- 85
- Agentic
- 80
- Vision
- 82
- Multilingual
- 86
- Long Context
- 85
Benchmarks
How it scores
Public benchmark results, with independent third-party results where available. Bars normalize percentages to 100 and Elo ratings to a 1500 ceiling.
Independent index
Artificial Analysis Intelligence Index
Composite of ~9–10 independent evals · Artificial Analysis
40/ 100
BenchmarkResult
Artificial Analysis Intelligence Indexindependent
GeneralArtificial Analysis
40%
SWE-bench Verifiedindependent
CodingSWE-bench
58.4%
MMLU-Pro
KnowledgeVendor-reported
55.3%
DeepSWEindependent
CodingDatacurve
24%