OpenAI, proprietary

# GPT-5.4 mini

> GPT-5.4 mini by OpenAI, released March 2026. Ranked #76 of 354 with a Noometry Index of 45.0. API: $0.75 in / $4.50 out per M tokens. 400K context. Scores, sources and comparisons.
- Canonical page: https://noometry.com/models/gpt-5-4-mini
- Last updated: 2026-10-10
- Title: GPT-5.4 mini Benchmarks, Price & Rank (October 2026)

GPT-5.4 mini by OpenAI ranks 76th of 354 ranked models on the Noometry Index as of October 2026, with a score of 45.0. Its strongest category is multimodal, where it ranks 56th. API pricing starts at $0.75 per million input tokens and $4.50 per million output tokens, with a 400K-token context window.

Last verified October 10, 2026

## Specifications

- **Noometry rank:** #76 of 354
- **Index score:** 45.0
- **Evidence:** Confirmed 46 results
- **Provider:** [OpenAI](https://noometry.com/providers/openai)
- **Released:** March 17, 2026
- **Weights:** Proprietary
- **Reasoning:** Yes
- **Context window:** 400K
- **Max output:** 128K
- **Input price:** $0.75 / M
- **Output price:** $4.50 / M
- **Blended price:** $1.69 / M
- **Output speed:** 10 tokens/s [Kagi](https://help.kagi.com/kagi/ai/llm-benchmark.html)
- **Value:** #140 of 219
- **Knowledge cutoff:** August 2025
- **Input:** text, image

## Category scores

Each category score combines every public result we have in that category.

GPT-5.4 mini category scores

1.  Coding 45.2
2.  Agentic & Tool Use 29.9
3.  Reasoning 30.4
4.  Math 45.5
5.  Knowledge 51.5
6.  Multimodal 39.7
7.  Multilingual 51.9
8.  Instruction Following 74.1
9.  Long Context 43.0
10.  Writing & Preference 64.0
11.  020406080

GPT-5.4 mini category ranks
| Category | Score | Rank | Results |
| --- | --- | --- | --- |
| [Coding](https://noometry.com/best/coding) | 45.2 | #72 | 5 |
| [Agentic & Tool Use](https://noometry.com/best/agentic) | 29.9 | #81 | 1 |
| [Reasoning](https://noometry.com/best/reasoning) | 30.4 | #85 | 11 |
| [Math](https://noometry.com/best/math) | 45.5 | #75 | 5 |
| [Knowledge](https://noometry.com/best/knowledge) | 51.5 | #67 | 4 |
| [Multimodal](https://noometry.com/best/multimodal) | 39.7 | #56 | 1 |
| [Multilingual](https://noometry.com/best/multilingual) | 51.9 | #96 | 1 |
| [Instruction Following](https://noometry.com/best/instruction-following) | 74.1 | #102 | 1 |
| [Long Context](https://noometry.com/best/long-context) | 43.0 | #112 | 1 |
| [Writing & Preference](https://noometry.com/best/writing) | 64.0 | #58 | 4 |

## Strengths and weaknesses

Categories where GPT-5.4 mini places highest and lowest among the models ranked in each, with its score against that category's median.

### Strongest categories

GPT-5.4 mini: strongest categories
| Category | Score | vs median | Rank |
| --- | --- | --- | --- |
| [Writing & Preference](https://noometry.com/best/writing) | 64.0 | +10.3 | #58 of 312, top 19% |
| [Coding](https://noometry.com/best/coding) | 45.2 | +6.5 | #72 of 340, top 22% |
| [Knowledge](https://noometry.com/best/knowledge) | 51.5 | +14.2 | #67 of 314, top 22% |

### Weakest categories

GPT-5.4 mini: weakest categories
| Category | Score | vs median | Rank |
| --- | --- | --- | --- |
| [Agentic & Tool Use](https://noometry.com/best/agentic) | 29.9 | −0.4 | #81 of 154, top 53% |
| [Multimodal](https://noometry.com/best/multimodal) | 39.7 | +1.1 | #56 of 128, top 44% |
| [Long Context](https://noometry.com/best/long-context) | 43.0 | +2.0 | #112 of 296, top 38% |

## Closest competitors

The models ranked just above and below GPT-5.4 mini. When scores are this close, price and speed are often the better way to choose.

Models ranked closest to GPT-5.4 mini
| Model | Rank | Score | Blended $/M | Speed |  |
| --- | --- | --- | --- | --- | --- |
| [Qwen3.7 Plus](https://noometry.com/models/qwen3-7-plus) | #72 | 45.3 | $0.70 | — | [Compare](https://noometry.com/compare/gpt-5-4-mini-vs-qwen3-7-plus) |
| [Hy4 preview](https://noometry.com/models/hy4-preview) | #73 | 45.3 | $1.13 | — | [Compare](https://noometry.com/compare/gpt-5-4-mini-vs-hy4-preview) |
| [MiMo-V2.5-Pro](https://noometry.com/models/mimo-v2-5-pro) | #74 | 45.2 | $0.54 | — | [Compare](https://noometry.com/compare/gpt-5-4-mini-vs-mimo-v2-5-pro) |
| [Gemini 2.5 Pro](https://noometry.com/models/gemini-2-5-pro) | #75 | 45.0 | $3.44 | 5 | [Compare](https://noometry.com/compare/gemini-2-5-pro-vs-gpt-5-4-mini) |
| [Amazon Nova Experimental Chat 26 02 10](https://noometry.com/models/amazon-nova-experimental-chat-26-02-10) | #77 | 44.5 | — | — | [Compare](https://noometry.com/compare/amazon-nova-experimental-chat-26-02-10-vs-gpt-5-4-mini) |
| [DeepSeek-V3.2-Exp](https://noometry.com/models/deepseek-v3-2-exp) | #78 | 44.3 | $0.29 | 16 | [Compare](https://noometry.com/compare/deepseek-v3-2-exp-vs-gpt-5-4-mini) |
| [Hy3](https://noometry.com/models/hy3) | #79 | 44.2 | $0.14 | — | [Compare](https://noometry.com/compare/gpt-5-4-mini-vs-hy3) |
| [Inkling](https://noometry.com/models/inkling) | #80 | 44.1 | $2.57 | — | [Compare](https://noometry.com/compare/gpt-5-4-mini-vs-inkling) |

Sponsored placements are available on pages like this one. [Advertise on Noometry](https://noometry.com/advertise)

## Benchmark results

Every published result we track, with its source. Bold rows are the ones used for ranking; where several exist we prefer independent runs over self-reported numbers.

### Coding

GPT-5.4 mini Coding benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [FrontierCode](https://noometry.com/benchmarks/frontiercode) | 27% | #28 of 37, top 76% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LMArena WebDev](https://noometry.com/benchmarks/arena-webdev) | 1397 | #74 of 113, top 66% | high | [LMArena](https://lmarena.ai/leaderboard/webdev) | 2026-10-08 |
| [SciCode](https://noometry.com/benchmarks/scicode) | 49.9% | #45 of 121, top 38% | xhigh | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [WeirdML](https://noometry.com/benchmarks/weirdml) | 60.3% | #32 of 119, top 27% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [WeirdML](https://noometry.com/benchmarks/weirdml) | 37.9% |  | none | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LMArena Coding](https://noometry.com/benchmarks/arena-coding) | 1438 | #100 of 294, top 35% | high | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [ALE-Bench](https://noometry.com/benchmarks/ale-bench) | 1,189 | #32 of 105, top 31% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |

### Agentic & Tool Use

GPT-5.4 mini Agentic & Tool Use benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [DeepResearch Bench](https://noometry.com/benchmarks/deepresearch-bench) | 36.3% | #22 of 24, top 92% | low | [Epoch AI](https://epoch.ai/benchmarks) |  |

### Reasoning

GPT-5.4 mini Reasoning benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [ARC-AGI-2](https://noometry.com/benchmarks/arc-agi-2) | 13.2% |  | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [ARC-AGI-2](https://noometry.com/benchmarks/arc-agi-2) | 1.1% |  | low | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [ARC-AGI-2](https://noometry.com/benchmarks/arc-agi-2) | 4.4% |  | medium | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [ARC-AGI-2](https://noometry.com/benchmarks/arc-agi-2) | 18.9% | #42 of 83, top 51% | xhigh | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [Kagi LLM Benchmark](https://noometry.com/benchmarks/kagi-reasoning) | 37.9% | #81 of 99, top 82% |  | [Kagi LLM Benchmark](https://help.kagi.com/kagi/ai/llm-benchmark.html) |  |
| [NYT Connections (extended)](https://noometry.com/benchmarks/nyt-connections) | 61.8% | #55 of 91, top 61% | xhigh reasoning | [Lech Mazur benchmarks](https://github.com/lechmazur/nyt-connections) |  |
| [ARC-AGI-1](https://noometry.com/benchmarks/arc-agi-1) | 58% |  | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [ARC-AGI-1](https://noometry.com/benchmarks/arc-agi-1) | 13% |  | low | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [ARC-AGI-1](https://noometry.com/benchmarks/arc-agi-1) | 40.8% |  | medium | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [ARC-AGI-1](https://noometry.com/benchmarks/arc-agi-1) | 63.7% | #48 of 83, top 58% | xhigh | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [CritPt](https://noometry.com/benchmarks/critpt) | 10% | #47 of 134, top 36% | xhigh | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [Chess Puzzles](https://noometry.com/benchmarks/chess-puzzles) | 18% |  | high | [Epoch AI](https://epoch.ai/benchmarks) | 2026-04-15 |
| [Chess Puzzles](https://noometry.com/benchmarks/chess-puzzles) | 3% |  | none | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-07 |
| [Chess Puzzles](https://noometry.com/benchmarks/chess-puzzles) | 24% | #45 of 129, top 35% | xhigh | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-07 |
| [Thematic Generalization](https://noometry.com/benchmarks/thematic-generalization) | 61.7% | #12 of 23, top 53% | xhigh reasoning | [Lech Mazur benchmarks](https://github.com/lechmazur/generalization) |  |
| [LMArena Hard Prompts](https://noometry.com/benchmarks/arena-hard-prompts) | 1424 | #98 of 297, top 33% | high | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [Mystery Game Puzzles](https://noometry.com/benchmarks/mystery-game-puzzles) | 8% |  | low | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-27 |
| [Mystery Game Puzzles](https://noometry.com/benchmarks/mystery-game-puzzles) | 7% |  | medium | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-27 |
| [Mystery Game Puzzles](https://noometry.com/benchmarks/mystery-game-puzzles) | 11% | #59 of 74, top 80% | none | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-27 |
| [DTBench](https://noometry.com/benchmarks/dtbench) | 80% | #76 of 151, top 51% | xhigh | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LMCA](https://noometry.com/benchmarks/lmca) | 40.8% | #44 of 125, top 36% | xhigh | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [Epoch Capabilities Index](https://noometry.com/benchmarks/epoch-capabilities-index) | 148.84 | #60 of 213, top 29% |  | [Epoch AI](https://epoch.ai/eci) | 2026-03-17 |
| [ForecastBench](https://noometry.com/benchmarks/forecastbench) | 57 | #63 of 72, top 88% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |

### Math

GPT-5.4 mini Math benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [FrontierMath (Tiers 1-3)](https://noometry.com/benchmarks/frontiermath) | 24.6% |  | low | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-28 |
| [FrontierMath (Tiers 1-3)](https://noometry.com/benchmarks/frontiermath) | 17.2% |  | none | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-28 |
| [FrontierMath (Tiers 1-3)](https://noometry.com/benchmarks/frontiermath) | 51.2% | #47 of 81, top 59% | xhigh | [Epoch AI](https://epoch.ai/benchmarks) | 2026-06-12 |
| [FrontierMath Tier 4](https://noometry.com/benchmarks/frontiermath-tier-4) | 9.8% | #53 of 63, top 85% | xhigh | [Epoch AI](https://epoch.ai/benchmarks) | 2026-06-12 |
| [OTIS Mock AIME 2024-2025](https://noometry.com/benchmarks/otis-mock-aime) | 87.2% |  | high | [Epoch AI](https://epoch.ai/benchmarks) | 2026-04-15 |
| [OTIS Mock AIME 2024-2025](https://noometry.com/benchmarks/otis-mock-aime) | 26.7% |  | none | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-07 |
| [OTIS Mock AIME 2024-2025](https://noometry.com/benchmarks/otis-mock-aime) | 88.9% | #54 of 173, top 32% | xhigh | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-07 |
| [ProofBench](https://noometry.com/benchmarks/proofbench) | 21% | #48 of 77, top 63% | xhigh | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LMArena Math](https://noometry.com/benchmarks/arena-math) | 1419 | #105 of 285, top 37% | high | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [FrontierMath (Feb 2025 set)](https://noometry.com/benchmarks/frontiermath-2025-02) | 28.3% | #20 of 68, top 30% | high | [Epoch AI](https://epoch.ai/benchmarks) | 2026-04-15 |
| [FrontierMath Tier 4 (v1)](https://noometry.com/benchmarks/frontiermath-tier-4-v1) | 2.1% | #44 of 55, top 80% | high | [Epoch AI](https://epoch.ai/benchmarks) | 2026-04-15 |

### Knowledge

GPT-5.4 mini Knowledge benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [GPQA Diamond](https://noometry.com/benchmarks/gpqa-diamond) | 83.6% |  | high | [Epoch AI](https://epoch.ai/benchmarks) | 2026-04-15 |
| [GPQA Diamond](https://noometry.com/benchmarks/gpqa-diamond) | 64.1% |  | none | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-07 |
| [GPQA Diamond](https://noometry.com/benchmarks/gpqa-diamond) | 86.9% | #57 of 186, top 31% | xhigh | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-07 |
| [SimpleQA Verified](https://noometry.com/benchmarks/simpleqa-verified) | 29.4% | #59 of 77, top 77% | high | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-27 |
| [Vectara Hallucination Rate](https://noometry.com/benchmarks/vectara-hallucination) (lower is better) | 5.5% | #17 of 96, top 18% |  | [Vectara Hallucination Leaderboard](https://github.com/vectara/hallucination-leaderboard) |  |
| [LMArena Expert](https://noometry.com/benchmarks/arena-expert) | 1435 | #90 of 273, top 33% | high | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Multimodal

GPT-5.4 mini Multimodal benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Vision](https://noometry.com/benchmarks/arena-vision) | 1245 | #59 of 122, top 49% | high | [LMArena](https://lmarena.ai/leaderboard/vision) | 2026-10-09 |

### Multilingual

GPT-5.4 mini Multilingual benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Non-English](https://noometry.com/benchmarks/arena-non-english) | 1405 | #97 of 297, top 33% | high | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Chinese](https://noometry.com/benchmarks/arena-chinese) | 1446 | #108 of 285, top 38% | high | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena French](https://noometry.com/benchmarks/arena-french) | 1440 | #83 of 223, top 38% | high | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena German](https://noometry.com/benchmarks/arena-german) | 1409 | #87 of 231, top 38% | high | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Japanese](https://noometry.com/benchmarks/arena-japanese) | 1374 | #84 of 211, top 40% | high | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Korean](https://noometry.com/benchmarks/arena-korean) | 1368 | #88 of 213, top 42% | high | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Russian](https://noometry.com/benchmarks/arena-russian) | 1417 | #84 of 283, top 30% | high | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Spanish](https://noometry.com/benchmarks/arena-spanish) | 1405 | #105 of 226, top 47% | high | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Instruction Following

GPT-5.4 mini Instruction Following benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Instruction Following](https://noometry.com/benchmarks/arena-instruction-following) | 1405 | #94 of 298, top 32% | high | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Long Context

GPT-5.4 mini Long Context benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Longer Query](https://noometry.com/benchmarks/arena-longer-query) | 1407 | #110 of 291, top 38% | high | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Writing & Preference

GPT-5.4 mini Writing & Preference benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Text](https://noometry.com/benchmarks/arena-text) | 1412 | #107 of 297, top 37% | high | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Creative Writing](https://noometry.com/benchmarks/arena-creative-writing) | 1370 | #110 of 295, top 38% | high | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [EQ-Bench Creative Writing](https://noometry.com/benchmarks/eqbench-creative-writing) | 1665 | #38 of 115, top 34% |  | [EQ-Bench](https://eqbench.com/creative_writing.html) |  |
| [LMArena Multi-Turn](https://noometry.com/benchmarks/arena-multi-turn) | 1429 | #84 of 295, top 29% | high | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

## API pricing by provider

GPT-5.4 mini API prices
| Route | Input $/M | Output $/M | Cached input $/M | Checked |
| --- | --- | --- | --- | --- |
| [azure](https://learn.microsoft.com/en-us/azure/ai-services/openai/concepts/models) | $0.75 | $4.50 | $0.075 | 2026-10-10 |
| [openai](https://platform.openai.com/docs/models) | $0.75 | $4.50 | $0.075 | 2026-10-10 |
| [openrouter](https://openrouter.ai/openai/gpt-5.4-mini) | $0.75 | $4.50 | $0.075 | 2026-10-10 |

[All OpenAI API prices →](https://noometry.com/llm-pricing/openai) [Estimate your cost →](https://noometry.com/tools/cost-calculator)

## Compare GPT-5.4 mini

-   [GPT-5.4 mini vs GPT-5 Mini](https://noometry.com/compare/gpt-5-4-mini-vs-gpt-5-mini)
-   [GPT-5.4 mini vs Gemini 2.5 Pro](https://noometry.com/compare/gemini-2-5-pro-vs-gpt-5-4-mini)
-   [GPT-5.4 mini vs Amazon Nova Experimental Chat 26 02 10](https://noometry.com/compare/amazon-nova-experimental-chat-26-02-10-vs-gpt-5-4-mini)
-   [GPT-5.4 mini vs MiMo-V2.5-Pro](https://noometry.com/compare/gpt-5-4-mini-vs-mimo-v2-5-pro)
-   [GPT-5.4 mini vs DeepSeek-V3.2-Exp](https://noometry.com/compare/deepseek-v3-2-exp-vs-gpt-5-4-mini)
-   [GPT-5.4 mini vs Hy4 preview](https://noometry.com/compare/gpt-5-4-mini-vs-hy4-preview)
-   [GPT-5.4 mini vs Hy3](https://noometry.com/compare/gpt-5-4-mini-vs-hy3)
-   [GPT-5.4 mini vs Claude Fable 5.1](https://noometry.com/compare/claude-fable-5-1-vs-gpt-5-4-mini)
-   [GPT-5.4 mini vs Gemini 3.8 Flash](https://noometry.com/compare/gemini-3-8-flash-vs-gpt-5-4-mini)
-   [GPT-5.4 mini vs Kimi K3](https://noometry.com/compare/gpt-5-4-mini-vs-kimi-k3)
-   [GPT-5.4 mini vs Grok 4.6](https://noometry.com/compare/gpt-5-4-mini-vs-grok-4-6)
-   [GPT-5.4 mini vs Qwen3.8 Max](https://noometry.com/compare/gpt-5-4-mini-vs-qwen3-8-max)
-   [GPT-5.4 mini vs GLM-5.3](https://noometry.com/compare/glm-5-3-vs-gpt-5-4-mini)
-   [GPT-5.4 mini vs Muse Spark 1.3](https://noometry.com/compare/gpt-5-4-mini-vs-muse-spark-1-3)

## Other OpenAI models

-   [GPT-6 Astra](https://noometry.com/models/gpt-6-astra)70.8
-   [GPT-6.1 Sol](https://noometry.com/models/gpt-6-1-sol)65.6
-   [GPT-5.6 Sol](https://noometry.com/models/gpt-5-6-sol)65.0
-   [GPT-5.5 Pro](https://noometry.com/models/gpt-5-5-pro)64.3
-   [GPT-5.5](https://noometry.com/models/gpt-5-5)63.4
-   [GPT-6 Sol](https://noometry.com/models/gpt-6-sol)61.8
-   [GPT-5.4](https://noometry.com/models/gpt-5-4)59.4
-   [GPT-5.6 Terra](https://noometry.com/models/gpt-5-6-terra)59.2

## Frequently asked questions

### How good is GPT-5.4 mini?

GPT-5.4 mini by OpenAI ranks 76th of 354 ranked models on the Noometry Index as of October 2026, with a score of 45.0. Its strongest category is multimodal, where it ranks 56th. API pricing starts at $0.75 per million input tokens and $4.50 per million output tokens, with a 400K-token context window.

### How much does GPT-5.4 mini cost?

GPT-5.4 mini costs $0.75 per million input tokens and $4.50 per million output tokens on OpenAI's own API, with cached input at $0.075.

### What is GPT-5.4 mini's context window?

GPT-5.4 mini accepts up to 400K tokens of input and can write up to 128K tokens in one response.

### Is GPT-5.4 mini open source?

No. GPT-5.4 mini is proprietary and available only through OpenAI's API and partner platforms.

### How fast is GPT-5.4 mini?

GPT-5.4 mini generated about 10 output tokens per second in the Kagi LLM Benchmark's timed runs. Speed varies by provider, load and reasoning effort.

### What are GPT-5.4 mini's strengths and weaknesses?

Relative to other ranked models, GPT-5.4 mini places best in writing & preference, coding, knowledge and lowest in agentic & tool use, multimodal, long context.

### What is GPT-5.4 mini best at?

Its best category is multimodal, where it ranks 56th on Noometry.

### Cite this page

Noometry. (2026). GPT-5.4 mini benchmarks and pricing. Retrieved October 10, 2026, from https://noometry.com/models/gpt-5-4-mini

Quote Noometry with a link back to this page. It is also available in [Markdown](https://noometry.com/md/models/gpt-5-4-mini.md).