OpenAI, proprietary

# GPT-4.1 mini

> GPT-4.1 mini by OpenAI, released April 2025. Ranked #240 of 354 with a Noometry Index of 33.6. API: $0.40 in / $1.60 out per M tokens. 1.05M context. Scores, sources and comparisons.
- Canonical page: https://noometry.com/models/gpt-4-1-mini
- Last updated: 2026-10-10
- Title: GPT-4.1 mini Benchmarks, Price & Rank (October 2026)

GPT-4.1 mini by OpenAI ranks 240th of 354 ranked models on the Noometry Index as of October 2026, with a score of 33.6. Its strongest category is agentic & tool use, where it ranks 55th. API pricing starts at $0.40 per million input tokens and $1.60 per million output tokens, with a 1.05M-token context window.

Last verified October 10, 2026

## Specifications

- **Noometry rank:** #240 of 354
- **Index score:** 33.6
- **Evidence:** Confirmed 47 results
- **Provider:** [OpenAI](https://noometry.com/providers/openai)
- **Released:** April 14, 2025
- **Weights:** Proprietary
- **Reasoning:** No
- **Context window:** 1.05M
- **Max output:** 33K
- **Input price:** $0.40 / M
- **Output price:** $1.60 / M
- **Blended price:** $0.70 / M
- **Output speed:** 86 tokens/s [Kagi](https://help.kagi.com/kagi/ai/llm-benchmark.html)
- **Value:** #97 of 219
- **Knowledge cutoff:** April 2024
- **Input:** text, image, pdf

## Category scores

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

GPT-4.1 mini category scores

1.  Coding 30.6
2.  Agentic & Tool Use 33.3
3.  Reasoning 10.8
4.  Math 24.1
5.  Knowledge 34.7
6.  Multimodal 35.8
7.  Multilingual 45.7
8.  Instruction Following 73.7
9.  Long Context 31.8
10.  Writing & Preference 48.6
11.  020406080

GPT-4.1 mini category ranks
| Category | Score | Rank | Results |
| --- | --- | --- | --- |
| [Coding](https://noometry.com/best/coding) | 30.6 | #293 | 7 |
| [Agentic & Tool Use](https://noometry.com/best/agentic) | 33.3 | #55 | 1 |
| [Reasoning](https://noometry.com/best/reasoning) | 10.8 | #340 | 9 |
| [Math](https://noometry.com/best/math) | 24.1 | #270 | 5 |
| [Knowledge](https://noometry.com/best/knowledge) | 34.7 | #194 | 5 |
| [Multimodal](https://noometry.com/best/multimodal) | 35.8 | #82 | 1 |
| [Multilingual](https://noometry.com/best/multilingual) | 45.7 | #166 | 1 |
| [Instruction Following](https://noometry.com/best/instruction-following) | 73.7 | #118 | 2 |
| [Long Context](https://noometry.com/best/long-context) | 31.8 | #275 | 2 |
| [Writing & Preference](https://noometry.com/best/writing) | 48.6 | #199 | 5 |

## Strengths and weaknesses

Categories where GPT-4.1 mini places highest and lowest among the models ranked in each, with its score against that category's median.

### Strongest categories

GPT-4.1 mini: strongest categories
| Category | Score | vs median | Rank |
| --- | --- | --- | --- |
| [Agentic & Tool Use](https://noometry.com/best/agentic) | 33.3 | +2.9 | #55 of 154, top 36% |
| [Instruction Following](https://noometry.com/best/instruction-following) | 73.7 | +2.4 | #118 of 305, top 39% |
| [Multilingual](https://noometry.com/best/multilingual) | 45.7 | −1.7 | #166 of 297, top 56% |

### Weakest categories

GPT-4.1 mini: weakest categories
| Category | Score | vs median | Rank |
| --- | --- | --- | --- |
| [Reasoning](https://noometry.com/best/reasoning) | 10.8 | −12.8 | #340 of 350, top 98% |
| [Long Context](https://noometry.com/best/long-context) | 31.8 | −9.1 | #275 of 296, top 93% |
| [Coding](https://noometry.com/best/coding) | 30.6 | −8.1 | #293 of 340, top 87% |

## Closest competitors

The models ranked just above and below GPT-4.1 mini. When scores are this close, price and speed are often the better way to choose.

Models ranked closest to GPT-4.1 mini
| Model | Rank | Score | Blended $/M | Speed |  |
| --- | --- | --- | --- | --- | --- |
| [Qwen3.5-9B](https://noometry.com/models/qwen3-5-9b) | #236 | 33.8 | $0.11 | — | [Compare](https://noometry.com/compare/gpt-4-1-mini-vs-qwen3-5-9b) |
| [Codellama 70b Instruct](https://noometry.com/models/codellama-70b-instruct) | #237 | 33.7 | — | — | [Compare](https://noometry.com/compare/codellama-70b-instruct-vs-gpt-4-1-mini) |
| [Qwen3 8B](https://noometry.com/models/qwen3-8b) | #238 | 33.7 | $0.31 | — | [Compare](https://noometry.com/compare/gpt-4-1-mini-vs-qwen3-8b) |
| [Grok-2 (Dec 2024)](https://noometry.com/models/grok-2) | #239 | 33.7 | — | — | [Compare](https://noometry.com/compare/gpt-4-1-mini-vs-grok-2) |
| [GPT-5 Nano](https://noometry.com/models/gpt-5-nano) | #241 | 33.5 | $0.14 | 4 | [Compare](https://noometry.com/compare/gpt-4-1-mini-vs-gpt-5-nano) |
| [Mercury 2.5](https://noometry.com/models/mercury-2-5) | #242 | 33.5 | $0.0675 | — | [Compare](https://noometry.com/compare/gpt-4-1-mini-vs-mercury-2-5) |
| [Mistral Small](https://noometry.com/models/mistral-small) | #243 | 33.4 | $0.26 | 120 | [Compare](https://noometry.com/compare/gpt-4-1-mini-vs-mistral-small) |
| [Nova 2.0 Pro Preview](https://noometry.com/models/nova-2-0-pro-preview) | #244 | 33.4 | — | — | [Compare](https://noometry.com/compare/gpt-4-1-mini-vs-nova-2-0-pro-preview) |

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-4.1 mini Coding benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [SWE-bench Verified (bash only)](https://noometry.com/benchmarks/swe-bench-bash-only) | 23.9% | #34 of 39, top 88% |  | [SWE-bench](https://www.swebench.com/) | 2025-07-20 |
| [Aider Polyglot](https://noometry.com/benchmarks/aider-polyglot) | 32.4% | #32 of 44, top 73% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [SciCode](https://noometry.com/benchmarks/scicode) | 40.4% | #76 of 121, top 63% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [WeirdML](https://noometry.com/benchmarks/weirdml) | 37.6% | #86 of 119, top 73% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [BigCodeBench Instruct](https://noometry.com/benchmarks/bigcodebench-instruct) | 48.9% | #6 of 64, top 10% |  | [BigCodeBench](https://bigcode-bench.github.io/) | 2025-04-14 |
| [LMArena Coding](https://noometry.com/benchmarks/arena-coding) | 1367 | #160 of 294, top 55% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [CadEval](https://noometry.com/benchmarks/cadeval) | 16% | #13 of 14, top 93% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |

### Agentic & Tool Use

GPT-4.1 mini Agentic & Tool Use benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [Berkeley Function Calling Leaderboard](https://noometry.com/benchmarks/bfcl) | 50.5% | #19 of 49, top 39% | fc | [Berkeley Function Calling Leaderboard](https://gorilla.cs.berkeley.edu/leaderboard.html) |  |

### Reasoning

GPT-4.1 mini Reasoning benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [ARC-AGI-2](https://noometry.com/benchmarks/arc-agi-2) | 0% | #75 of 83, top 91% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [Kagi LLM Benchmark](https://noometry.com/benchmarks/kagi-reasoning) | 48.6% | #68 of 99, top 69% |  | [Kagi LLM Benchmark](https://help.kagi.com/kagi/ai/llm-benchmark.html) |  |
| [ARC-AGI-1](https://noometry.com/benchmarks/arc-agi-1) | 3.5% | #81 of 83, top 98% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [CritPt](https://noometry.com/benchmarks/critpt) | 0% | #110 of 134, top 83% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [Chess Puzzles](https://noometry.com/benchmarks/chess-puzzles) | 7% | #87 of 129, top 68% |  | [Epoch AI](https://epoch.ai/benchmarks) | 2026-07-15 |
| [LMArena Hard Prompts](https://noometry.com/benchmarks/arena-hard-prompts) | 1349 | #161 of 297, top 55% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [Mystery Game Puzzles](https://noometry.com/benchmarks/mystery-game-puzzles) | 7% | #66 of 74, top 90% |  | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-27 |
| [DTBench](https://noometry.com/benchmarks/dtbench) | 68.8% | #94 of 151, top 63% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LMCA](https://noometry.com/benchmarks/lmca) | 21.1% | #92 of 125, top 74% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [Epoch Capabilities Index](https://noometry.com/benchmarks/epoch-capabilities-index) | 135.01 | #127 of 213, top 60% |  | [Epoch AI](https://epoch.ai/eci) | 2025-04-14 |

### Math

GPT-4.1 mini Math benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [FrontierMath (Tiers 1-3)](https://noometry.com/benchmarks/frontiermath) | 6.7% | #76 of 81, top 94% |  | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-27 |
| [OTIS Mock AIME 2024-2025](https://noometry.com/benchmarks/otis-mock-aime) | 44.7% | #115 of 173, top 67% |  | [Epoch AI](https://epoch.ai/benchmarks) | 2025-04-14 |
| [Omni-MATH](https://noometry.com/benchmarks/omni-math) | 49.1% | #16 of 57, top 29% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| [LMArena Math](https://noometry.com/benchmarks/arena-math) | 1343 | #166 of 285, top 59% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [MATH Level 5](https://noometry.com/benchmarks/math-level-5) | 87.3% | #18 of 79, top 23% |  | [Epoch AI](https://epoch.ai/benchmarks) | 2025-04-14 |
| [FrontierMath (Feb 2025 set)](https://noometry.com/benchmarks/frontiermath-2025-02) | 4.5% | #48 of 68, top 71% |  | [Epoch AI](https://epoch.ai/benchmarks) | 2025-04-14 |

### Knowledge

GPT-4.1 mini Knowledge benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [GPQA Diamond](https://noometry.com/benchmarks/gpqa-diamond) | 65.8% | #104 of 186, top 56% |  | [Epoch AI](https://epoch.ai/benchmarks) | 2025-04-14 |
| [SimpleQA Verified](https://noometry.com/benchmarks/simpleqa-verified) | 12.7% | #71 of 77, top 93% |  | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-31 |
| [MMLU-Pro](https://noometry.com/benchmarks/mmlu-pro) | 78.3% | #22 of 58, top 38% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| [GPQA (HELM)](https://noometry.com/benchmarks/helm-gpqa) | 61.4% | #21 of 57, top 37% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| [LMArena Expert](https://noometry.com/benchmarks/arena-expert) | 1338 | #161 of 273, top 59% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Multimodal

GPT-4.1 mini Multimodal benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Vision](https://noometry.com/benchmarks/arena-vision) | 1181 | #86 of 122, top 71% |  | [LMArena](https://lmarena.ai/leaderboard/vision) | 2026-10-09 |

### Multilingual

GPT-4.1 mini Multilingual benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Non-English](https://noometry.com/benchmarks/arena-non-english) | 1318 | #166 of 297, top 56% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Chinese](https://noometry.com/benchmarks/arena-chinese) | 1329 | #178 of 285, top 63% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena French](https://noometry.com/benchmarks/arena-french) | 1358 | #142 of 223, top 64% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena German](https://noometry.com/benchmarks/arena-german) | 1351 | #129 of 231, top 56% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Japanese](https://noometry.com/benchmarks/arena-japanese) | 1290 | #126 of 211, top 60% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Korean](https://noometry.com/benchmarks/arena-korean) | 1298 | #131 of 213, top 62% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Russian](https://noometry.com/benchmarks/arena-russian) | 1324 | #165 of 283, top 59% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Spanish](https://noometry.com/benchmarks/arena-spanish) | 1319 | #155 of 226, top 69% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Instruction Following

GPT-4.1 mini Instruction Following benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [IFEval](https://noometry.com/benchmarks/ifeval) | 90.4% | #9 of 57, top 16% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| [LMArena Instruction Following](https://noometry.com/benchmarks/arena-instruction-following) | 1333 | #156 of 298, top 53% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Long Context

GPT-4.1 mini Long Context benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [Fiction.LiveBench](https://noometry.com/benchmarks/fiction-livebench) | 44.4% | #39 of 47, top 83% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LMArena Longer Query](https://noometry.com/benchmarks/arena-longer-query) | 1344 | #156 of 291, top 54% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Writing & Preference

GPT-4.1 mini Writing & Preference benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Text](https://noometry.com/benchmarks/arena-text) | 1340 | #162 of 297, top 55% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Creative Writing](https://noometry.com/benchmarks/arena-creative-writing) | 1300 | #165 of 295, top 56% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [EQ-Bench Creative Writing](https://noometry.com/benchmarks/eqbench-creative-writing) | 1147 | #87 of 115, top 76% |  | [EQ-Bench](https://eqbench.com/creative_writing.html) |  |
| [WildBench](https://noometry.com/benchmarks/wildbench) | 83.8% | #17 of 57, top 30% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| [LMArena Multi-Turn](https://noometry.com/benchmarks/arena-multi-turn) | 1354 | #153 of 295, top 52% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

## API pricing by provider

GPT-4.1 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) | $0.40 | $1.60 | $0.10 | 2026-10-10 |
| [openai](https://platform.openai.com/docs/models) | $0.40 | $1.60 | $0.10 | 2026-10-10 |
| [openrouter](https://openrouter.ai/openai/gpt-4.1-mini) | $0.40 | $1.60 | $0.10 | 2026-10-10 |

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

## Compare GPT-4.1 mini

-   [GPT-4.1 mini vs GPT-4o mini](https://noometry.com/compare/gpt-4-1-mini-vs-gpt-4o-mini)
-   [GPT-4.1 mini vs Grok-2 (Dec 2024)](https://noometry.com/compare/gpt-4-1-mini-vs-grok-2)
-   [GPT-4.1 mini vs GPT-5 Nano](https://noometry.com/compare/gpt-4-1-mini-vs-gpt-5-nano)
-   [GPT-4.1 mini vs Qwen3 8B](https://noometry.com/compare/gpt-4-1-mini-vs-qwen3-8b)
-   [GPT-4.1 mini vs Mercury 2.5](https://noometry.com/compare/gpt-4-1-mini-vs-mercury-2-5)
-   [GPT-4.1 mini vs Codellama 70b Instruct](https://noometry.com/compare/codellama-70b-instruct-vs-gpt-4-1-mini)
-   [GPT-4.1 mini vs Mistral Small](https://noometry.com/compare/gpt-4-1-mini-vs-mistral-small)
-   [GPT-4.1 mini vs Claude Fable 5.1](https://noometry.com/compare/claude-fable-5-1-vs-gpt-4-1-mini)
-   [GPT-4.1 mini vs Gemini 3.8 Flash](https://noometry.com/compare/gemini-3-8-flash-vs-gpt-4-1-mini)
-   [GPT-4.1 mini vs Kimi K3](https://noometry.com/compare/gpt-4-1-mini-vs-kimi-k3)
-   [GPT-4.1 mini vs Grok 4.6](https://noometry.com/compare/gpt-4-1-mini-vs-grok-4-6)
-   [GPT-4.1 mini vs Qwen3.8 Max](https://noometry.com/compare/gpt-4-1-mini-vs-qwen3-8-max)
-   [GPT-4.1 mini vs GLM-5.3](https://noometry.com/compare/glm-5-3-vs-gpt-4-1-mini)
-   [GPT-4.1 mini vs Muse Spark 1.3](https://noometry.com/compare/gpt-4-1-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-4.1 mini?

GPT-4.1 mini by OpenAI ranks 240th of 354 ranked models on the Noometry Index as of October 2026, with a score of 33.6. Its strongest category is agentic & tool use, where it ranks 55th. API pricing starts at $0.40 per million input tokens and $1.60 per million output tokens, with a 1.05M-token context window.

### How much does GPT-4.1 mini cost?

GPT-4.1 mini costs $0.40 per million input tokens and $1.60 per million output tokens on OpenAI's own API, with cached input at $0.10.

### What is GPT-4.1 mini's context window?

GPT-4.1 mini accepts up to 1.05M tokens of input and can write up to 33K tokens in one response.

### Is GPT-4.1 mini open source?

No. GPT-4.1 mini is proprietary and available only through OpenAI's API and partner platforms.

### How fast is GPT-4.1 mini?

GPT-4.1 mini generated about 86 output tokens per second in the Kagi LLM Benchmark's timed runs. Speed varies by provider, load and reasoning effort.

### What are GPT-4.1 mini's strengths and weaknesses?

Relative to other ranked models, GPT-4.1 mini places best in agentic & tool use, instruction following, multilingual and lowest in reasoning, long context, coding.

### What is GPT-4.1 mini best at?

Its best category is agentic & tool use, where it ranks 55th on Noometry.

### Cite this page

Noometry. (2026). GPT-4.1 mini benchmarks and pricing. Retrieved October 10, 2026, from https://noometry.com/models/gpt-4-1-mini

Quote Noometry with a link back to this page. It is also available in [Markdown](https://noometry.com/md/models/gpt-4-1-mini.md).