Language modelActive

GPT-4.1 mini

OpenAI

Released: April 14, 2025
Data date: September 8, 2026

Intelligence: Not ranked
Overall score
Speed: 111.5 tokens/s
Output throughput
Price: $0.4 · $1.6
Input · Output / 1M tokens
Input: Text, Image
Output: Text

No published category-wide ranking is available for this model.

Entries 1-12 of 97. Page 1 of 9.

Published benchmarks

Each chart compares models in the same documented test and highlights the current model.

VISTA

Overall

What this benchmark measures: 758 image-text tasks combine OCR, spatial understanding, object recognition, and open-ended visual reasoning.

Context: The dataset is private and uses task-specific rubrics, making independent reproduction difficult.

Higher is better11 modelsGPT-4.1 mini: Rank 9 of 11Data date: August 26, 2026

1.Gemini 2.5 Pro54.63%

2.GPT-5.4 Pro53.89%

3.GPT-5 pro52.39%

4.o3-pro51.63%

5.GPT-5.450.89%

6.GPT-5 mini50.39%

7.GPT-549.69%

8.GPT-4.145.34%

9.GPT-4.1 mini41.14%

10.Llama 4 Maverick38.33%

11.GPT-4.1 nano26.55%

Scale: 0% - 100%

Source: Scale AI

CC BY 4.0

gradually.ai

Methodology and context

Comparison cohort: scale-vista-private-overall
Metric: rubric score
Scale: 0-100
Participants: 11
Methodology and context: 758 single-turn image-text tasks with structured yes-no rubrics.. Source model ID: curated/gpt-4.1-mini. Source model name: GPT-4.1 mini. Provider reported by source: OpenAI. Evaluator: Scale AI. Dataset type: public. Attempts: pass@1. Score display: 41.14% ± 0.58. Source ID: scale-ai. Evidence capture ID: curated-scale-ai-2026-08-26-5edf9af15d2e. Source payload hash: 5edf9af15d2e4bb35a694ad24c9d764cfdc08543d3ae92cf5a387efbda259c8c. Parser version: curated-v1. Imported at: 2026-09-04

Source: Scale AI

Finance

4 measurements

CorpFin v2

Exact Pages

Higher is better3 modelsGPT-4.1 mini: Rank 2 of 3Data date: August 11, 2026

1.GPT-4.162.82%

2.GPT-4.1 mini59.44%

3.GPT-4.1 nano48.95%

Scale: 0% - 100%

Source: Vals AI

CC BY 4.0

gradually.ai

Methodology and context

Comparison cohort: vals-corp-fin-v2:2:exact_pages
Metric: accuracy
Scale: 0-100
Participants: 3
Methodology and context: Source model ID: openai/gpt-4.1-mini-2025-04-14. Source model name: GPT-4.1 mini. Provider reported by source: OpenAI. Model snapshot: gpt-4.1-mini-2025-04-14. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-08-06. Reasoning effort: high. Temperature: 1. Maximum output tokens: 32768. Latency in seconds: 3.307. Standard error: 1.676. Cost per task in USD: 0.000891. Source ID: vals-ai. Evidence capture ID: vals-corp_fin_v2-2026-08-11-d9e58d191cd9. Source payload hash: d9e58d191cd9f1690e3b59f0a37055813038531410f2d73e765676893c0f9526. Parser version: vals-astro-v2. Imported at: 2026-08-11

Source: Vals AI

CorpFin v2

Max Fitting Context

Higher is better3 modelsGPT-4.1 mini: Rank 2 of 3Data date: August 11, 2026

1.GPT-4.160.84%

2.GPT-4.1 mini55.01%

3.GPT-4.1 nano38.46%

Scale: 0% - 100%

Source: Vals AI

CC BY 4.0

gradually.ai

Methodology and context

Comparison cohort: vals-corp-fin-v2:2:max_fitting_context
Metric: accuracy
Scale: 0-100
Participants: 3
Methodology and context: Source model ID: openai/gpt-4.1-mini-2025-04-14. Source model name: GPT-4.1 mini. Provider reported by source: OpenAI. Model snapshot: gpt-4.1-mini-2025-04-14. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-08-06. Reasoning effort: high. Temperature: 1. Maximum output tokens: 32768. Latency in seconds: 8.221. Standard error: 1.698. Cost per task in USD: 0.051823. Source ID: vals-ai. Evidence capture ID: vals-corp_fin_v2-2026-08-11-d9e58d191cd9. Source payload hash: d9e58d191cd9f1690e3b59f0a37055813038531410f2d73e765676893c0f9526. Parser version: vals-astro-v2. Imported at: 2026-08-11

Source: Vals AI

CorpFin v2

Overall

Higher is better50 modelsGPT-4.1 mini: Rank 40 of 50Data date: September 4, 2026

1.Claude Opus 573.19%

2.Claude Fable 571.83%

3.Kimi K371.56%

4.Inkling Small69.62%

5.Inkling68.57%

6.Grok 4.368.53%

7.GPT-5.568.42%

8.Kimi K2.568.26%

9.Grok 4.567.41%

10.Claude Sonnet 566.98%

11.Kimi K2.666.74%

12.Gemini 3 Flash66.43%

13.Grok 4.666.16%

14.GLM-5.266.12%

15.GPT-5.6 Terra65.31%

16.GPT-5.465.27%

17.Gemini 3.5 Flash64.69%

18.Gemini 3.1 Pro Preview64.49%

19.GLM-5.164.45%

20.GPT-5.6 Sol64.38%

21.GPT-5.6 Luna64.22%

22.Gemini 3.6 Flash63.33%

23.GPT-4.163.05%

24.GLM-562.9%

25.MiMo-V2.5-Pro61.42%

26.DeepSeek-V4-Pro61.38%

27.GPT-5.4 nano61.19%

28.GPT-561.07%

29.GLM-4.560.96%

30.GPT-5.4 mini60.92%

31.Gemini 2.5 Pro60.8%

32.Gemini 3.5 Flash-Lite60.68%

33.Kimi K2 Thinking60.57%

34.GPT-5 mini60.18%

35.MiMo-V2.559.91%

36.o359.71%

37.Gemini 3.1 Flash-Lite59.36%

38.o4-mini58.97%

39.GPT OSS 120B58.24%

40.GPT-4.1 mini57.93%

41.GLM-4.656.84%

42.DeepSeek-V3 032454.74%

43.Trinity Large Thinking54.66%

44.DeepSeek-R154.12%

45.GPT OSS 20B53.15%

46.DeepSeek-V352.49%

47.GLM-4.746.39%

48.GPT-4o mini45.46%

49.o3-mini45.3%

50.GPT-4.1 nano42.08%

Scale: 0% - 100%

Source: Vals AI

CC BY 4.0

gradually.ai

Methodology and context

Comparison cohort: vals-corp-fin-v2:2:overall
Metric: accuracy
Scale: 0-100
Participants: 50
Methodology and context: Source model ID: openai/gpt-4.1-mini-2025-04-14. Source model name: GPT-4.1 mini. Model snapshot: gpt-4.1-mini-2025-04-14. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-08-12. Latency in seconds: 6.443. Cost per task in USD: 0.026113. Source ID: vals-ai. Evidence capture ID: vals-corp_fin_v2-2026-09-04-46dad6684551. Source payload hash: 46dad668455190ee4239b7c743d00d81c6fd3127e0d87123c518ec107c13b44d. Parser version: vals-astro-v2. Imported at: 2026-09-04

Source: Vals AI

CorpFin v2

Shared Max Context

Higher is better3 modelsGPT-4.1 mini: Rank 2 of 3Data date: August 11, 2026

1.GPT-4.165.5%

2.GPT-4.1 mini59.32%

3.GPT-4.1 nano38.81%

Scale: 0% - 100%

Source: Vals AI

CC BY 4.0

gradually.ai

Methodology and context

Comparison cohort: vals-corp-fin-v2:2:shared_max_context
Metric: accuracy
Scale: 0-100
Participants: 3
Methodology and context: Source model ID: openai/gpt-4.1-mini-2025-04-14. Source model name: GPT-4.1 mini. Provider reported by source: OpenAI. Model snapshot: gpt-4.1-mini-2025-04-14. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-08-06. Reasoning effort: high. Temperature: 1. Maximum output tokens: 32768. Latency in seconds: 7.8. Standard error: 1.677. Cost per task in USD: 0.025626. Source ID: vals-ai. Evidence capture ID: vals-corp_fin_v2-2026-08-11-d9e58d191cd9. Source payload hash: d9e58d191cd9f1690e3b59f0a37055813038531410f2d73e765676893c0f9526. Parser version: vals-astro-v2. Imported at: 2026-08-11

Source: Vals AI

Reasoning

3 measurements

GPQA Diamond

Few-Shot CoT

Higher is better3 modelsGPT-4.1 mini: Rank 1 of 3Data date: August 11, 2026

1.GPT-4.1 mini64.65%

2.GPT-4.164.14%

3.GPT-4.1 nano51.01%

Scale: 0% - 100%

Source: Vals AI

CC BY 4.0

gradually.ai

Methodology and context

Comparison cohort: vals-gpqa:1:diamond_few_shot_cot
Metric: accuracy
Scale: 0-100
Participants: 3
Methodology and context: Source model ID: openai/gpt-4.1-mini-2025-04-14. Source model name: GPT-4.1 mini. Provider reported by source: OpenAI. Model snapshot: gpt-4.1-mini-2025-04-14. Evaluator: Vals AI. Dataset type: public. Leaderboard date: 2026-08-09. Reasoning effort: high. Temperature: 1. Maximum output tokens: 32768. Latency in seconds: 8.974. Standard error: 3.397. Cost per task in USD: 0.002537. Source ID: vals-ai. Evidence capture ID: vals-gpqa-2026-08-11-d3325290a404. Source payload hash: d3325290a40411054e05ecb86812143465b4d8eee24a0f71f6cf5dfee5b232a1. Parser version: vals-astro-v2. Imported at: 2026-08-11

Source: Vals AI

GPQA Diamond

Zero-Shot CoT

Higher is better3 modelsGPT-4.1 mini: Rank 1 of 3Data date: August 11, 2026

1.GPT-4.1 mini71.21%

2.GPT-4.166.67%

3.GPT-4.1 nano50.51%

Scale: 0% - 100%

Source: Vals AI

CC BY 4.0

gradually.ai

Methodology and context

Comparison cohort: vals-gpqa:1:diamond_zero_shot_cot
Metric: accuracy
Scale: 0-100
Participants: 3
Methodology and context: Source model ID: openai/gpt-4.1-mini-2025-04-14. Source model name: GPT-4.1 mini. Provider reported by source: OpenAI. Model snapshot: gpt-4.1-mini-2025-04-14. Evaluator: Vals AI. Dataset type: public. Leaderboard date: 2026-08-09. Reasoning effort: high. Temperature: 1. Maximum output tokens: 32768. Latency in seconds: 9.589. Standard error: 3.25. Cost per task in USD: 0.002112. Source ID: vals-ai. Evidence capture ID: vals-gpqa-2026-08-11-d3325290a404. Source payload hash: d3325290a40411054e05ecb86812143465b4d8eee24a0f71f6cf5dfee5b232a1. Parser version: vals-astro-v2. Imported at: 2026-08-11

Source: Vals AI

GPQA Diamond

Overall

Higher is better54 modelsGPT-4.1 mini: Rank 47 of 54Data date: September 4, 2026

1.Gemini 3.1 Pro Preview95.45%

2.GPT-5.6 Sol95.2%

3.Grok 4.694.7%

4.Gemini 3.8 Flash94.44%

5.Gemini 3.7 Flash93.94%

6.Claude Opus 593.43%

6.Gemini 3.6 Flash93.43%

8.Claude Fable 593.18%

8.GPT-5.593.18%

10.Grok 4.592.93%

10.Kimi K392.93%

12.Gemini 3.5 Flash92.68%

13.GPT-5.491.67%

13.GPT-5.6 Luna91.67%

15.Grok 4.391.41%

16.GPT-5.6 Terra90.91%

17.DeepSeek-V4-Pro89.39%

18.Kimi K2.689.14%

19.Claude Sonnet 588.89%

20.GLM-5.388.13%

21.Gemini 3 Flash87.88%

22.Inkling87.12%

23.GLM-5.3-Flash86.36%

24.GLM-5.285.61%

24.GPT-585.61%

26.GLM-5.184.52%

27.Kimi K2.584.09%

27.o384.09%

29.Gemini 3.5 Flash-Lite83.84%

30.Inkling Small83.59%

31.GLM-583.33%

32.GPT-5.4 mini83.08%

33.MiMo-V2.5-Pro82.58%

34.MiMo-V2.581.57%

35.Gemini 3.1 Flash-Lite81.06%

36.GPT-5 mini80.3%

37.GLM-4.780.05%

38.GPT OSS 120B78.54%

38.Kimi K2 Thinking78.54%

40.GPT-5.4 nano77.53%

41.o3-mini75.51%

42.GLM-4.674.5%

42.o4-mini74.5%

44.o173.23%

45.GLM-4.572.22%

46.GPT OSS 20B68.94%

47.GPT-4.1 mini67.93%

48.GPT-4.165.4%

49.GPT-5 nano63.38%

50.DeepSeek-V3 032461.62%

51.DeepSeek-V354.55%

52.GPT-4.1 nano50.76%

53.GPT-4o mini44.19%

54.Command R+31.06%

Scale: 0% - 100%

Source: Vals AI

CC BY 4.0

gradually.ai

Methodology and context

Comparison cohort: vals-gpqa:1:overall
Metric: accuracy
Scale: 0-100
Participants: 54
Methodology and context: Source model ID: openai/gpt-4.1-mini-2025-04-14. Source model name: GPT-4.1 mini. Model snapshot: gpt-4.1-mini-2025-04-14. Evaluator: Vals AI. Dataset type: public. Leaderboard date: 2026-09-01. Latency in seconds: 9.282. Cost per task in USD: 0.002324. Source ID: vals-ai. Evidence capture ID: vals-gpqa-2026-09-04-fc438726f0d8. Source payload hash: fc438726f0d8523d320f02d75ae372a3fa38b28b36f70fe318d119f55153560d. Parser version: vals-astro-v2. Imported at: 2026-09-04

Source: Vals AI

Coding

4 measurements

LiveCodeBench v6

Easy

Higher is better3 modelsGPT-4.1 mini: Rank 1 of 3Data date: August 11, 2026

1.GPT-4.1 mini95.34%

2.GPT-4.194.72%

3.GPT-4.1 nano85.4%

Scale: 0% - 100%

Source: Vals AI

CC BY 4.0

gradually.ai

Methodology and context

Comparison cohort: vals-lcb:1:easy
Metric: accuracy
Scale: 0-100
Participants: 3
Methodology and context: Source model ID: openai/gpt-4.1-mini-2025-04-14. Source model name: GPT-4.1 mini. Provider reported by source: OpenAI. Model snapshot: gpt-4.1-mini-2025-04-14. Evaluator: Vals AI. Dataset type: public. Leaderboard date: 2026-08-09. Reasoning effort: high. Temperature: 1. Maximum output tokens: 32768. Latency in seconds: 2.25. Standard error: 1.174. Cost per task in USD: 0.000377. Source ID: vals-ai. Evidence capture ID: vals-lcb-2026-08-11-0342bcc364e4. Source payload hash: 0342bcc364e4426ffb24589c2752c9225be61fbd26db8deba5bdab9775ce5a75. Parser version: vals-astro-v2. Imported at: 2026-08-11

Source: Vals AI

LiveCodeBench v6

Hard

Higher is better3 modelsGPT-4.1 mini: Rank 1 of 3Data date: August 11, 2026

1.GPT-4.1 mini21.43%

2.GPT-4.113.14%

3.GPT-4.1 nano8.29%

Scale: 0% - 100%

Source: Vals AI

CC BY 4.0

gradually.ai

Methodology and context

Comparison cohort: vals-lcb:1:hard
Metric: accuracy
Scale: 0-100
Participants: 3
Methodology and context: Source model ID: openai/gpt-4.1-mini-2025-04-14. Source model name: GPT-4.1 mini. Provider reported by source: OpenAI. Model snapshot: gpt-4.1-mini-2025-04-14. Evaluator: Vals AI. Dataset type: public. Leaderboard date: 2026-08-09. Reasoning effort: high. Temperature: 1. Maximum output tokens: 32768. Latency in seconds: 62.607. Standard error: 2.193. Cost per task in USD: 0.002221. Source ID: vals-ai. Evidence capture ID: vals-lcb-2026-08-11-0342bcc364e4. Source payload hash: 0342bcc364e4426ffb24589c2752c9225be61fbd26db8deba5bdab9775ce5a75. Parser version: vals-astro-v2. Imported at: 2026-08-11

Source: Vals AI

LiveCodeBench v6

Medium

Higher is better3 modelsGPT-4.1 mini: Rank 1 of 3Data date: August 11, 2026

1.GPT-4.1 mini57.7%

2.GPT-4.156.14%

3.GPT-4.1 nano34.47%

Scale: 0% - 100%

Source: Vals AI

CC BY 4.0

gradually.ai

Methodology and context

Comparison cohort: vals-lcb:1:medium
Metric: accuracy
Scale: 0-100
Participants: 3
Methodology and context: Source model ID: openai/gpt-4.1-mini-2025-04-14. Source model name: GPT-4.1 mini. Provider reported by source: OpenAI. Model snapshot: gpt-4.1-mini-2025-04-14. Evaluator: Vals AI. Dataset type: public. Leaderboard date: 2026-08-09. Reasoning effort: high. Temperature: 1. Maximum output tokens: 32768. Latency in seconds: 17.92. Standard error: 2.524. Cost per task in USD: 0.000936. Source ID: vals-ai. Evidence capture ID: vals-lcb-2026-08-11-0342bcc364e4. Source payload hash: 0342bcc364e4426ffb24589c2752c9225be61fbd26db8deba5bdab9775ce5a75. Parser version: vals-astro-v2. Imported at: 2026-08-11

Source: Vals AI

LiveCodeBench v6

Overall

Higher is better56 modelsGPT-4.1 mini: Rank 50 of 56Data date: September 4, 2026

1.Claude Fable 589.78%

2.Gemini 3.8 Flash89.48%

3.Claude Opus 589.03%

4.Gemini 3.7 Flash88.65%

5.Gemini 3.1 Pro Preview88.49%

6.Grok 4.688.22%

7.Gemini 3.6 Flash88.08%

8.Gemini 3.5 Flash87.6%

9.DeepSeek-V4-Pro87.48%

10.Grok 4.587.35%

11.GPT-5.3-Codex87.31%

12.Kimi K387.19%

13.Kimi K2.686.77%

14.GPT-5 mini86.61%

15.Inkling Small85.93%

16.GPT-5.6 Terra85.93%

17.GPT-585.91%

18.Gemini 3 Flash85.59%

19.Inkling85.52%

20.GPT-5.585.3%

21.Grok 4.384.49%

22.GPT-5.484.14%

23.GPT-5.4 nano84.01%

24.o383.91%

25.Kimi K2.583.87%

26.GPT OSS 120B83.23%

27.GPT-5.6 Sol82.6%

28.Claude Sonnet 582.43%

29.GLM-4.782.23%

30.o4-mini82.21%

31.Kimi K2.7 Code82.05%

32.GLM-581.87%

33.MiMo-V2.581.51%

34.GPT-5.4 mini81.47%

35.GLM-5.181.38%

36.MiMo-V2.5-Pro81.35%

37.GLM-4.681.04%

38.GLM-5.380.54%

39.GLM-5.3-Flash80.51%

40.GPT OSS 20B80.39%

41.Gemini 3.1 Flash-Lite80.12%

42.Gemini 3.5 Flash-Lite79.01%

43.o3-mini71.48%

44.DeepSeek-R170.22%

45.GPT-5 nano70.22%

46.GLM-5.269.5%

47.GLM-4.567.45%

48.DeepSeek-V3 032465.48%

49.Kimi K2 Thinking63.15%

50.GPT-4.1 mini58.16%

51.GPT-4.154.67%

52.o150.26%

53.GPT-4o43.44%

54.GPT-4.1 nano42.72%

55.GPT-4o mini26.42%

56.Command R+18.24%

Scale: 0% - 100%

Source: Vals AI

CC BY 4.0

gradually.ai

Methodology and context

Comparison cohort: vals-lcb:1:overall
Metric: accuracy
Scale: 0-100
Participants: 56
Methodology and context: Source model ID: openai/gpt-4.1-mini-2025-04-14. Source model name: GPT-4.1 mini. Model snapshot: gpt-4.1-mini-2025-04-14. Evaluator: Vals AI. Dataset type: public. Leaderboard date: 2026-09-01. Latency in seconds: 27.592. Cost per task in USD: 0.001178. Source ID: vals-ai. Evidence capture ID: vals-lcb-2026-09-04-95ca83387127. Source payload hash: 95ca83387127df287e9a6d928c411c98c9b65b4cefeee46eb4008ca1521f5ed4. Parser version: vals-astro-v2. Imported at: 2026-09-04

Source: Vals AI

Recorded measurement details

Every observation retains its source value and published test conditions.

VISTA: Overall (Show measurement, test conditions, and source)

Source value: 41.14
Score: 41.14
Metric: rubric score
Unit: %
Benchmark version: 758 private prompt-image pairs
Category: multimodal
Task: overall
Task label: Overall
Direction: Higher is better
Comparison cohort: scale-vista-private-overall
Confidence interval: 0.58
Source type: official-leaderboard
Evaluator: Scale AI
Status: active
Retrieved at: 2026-08-26
Methodology: 758 single-turn image-text tasks with structured yes-no rubrics.. Source model ID: curated/gpt-4.1-mini. Source model name: GPT-4.1 mini. Provider reported by source: OpenAI. Evaluator: Scale AI. Dataset type: public. Attempts: pass@1. Score display: 41.14% ± 0.58. Source ID: scale-ai. Evidence capture ID: curated-scale-ai-2026-08-26-5edf9af15d2e. Source payload hash: 5edf9af15d2e4bb35a694ad24c9d764cfdc08543d3ae92cf5a387efbda259c8c. Parser version: curated-v1. Imported at: 2026-09-04
Comparison methodology: 758 single-turn image-text tasks with structured yes-no rubrics.

Source Scale AI

CorpFin v2: Exact Pages (Show measurement, test conditions, and source)

Source value: 59.441
Score: 59.441
Metric: accuracy
Unit: %
Benchmark version: 2
Category: finance
Task: exact_pages
Task label: Exact Pages
Direction: Higher is better
Comparison cohort: vals-corp-fin-v2:2:exact_pages
Source type: independent-evaluator
Evaluator: Vals AI
Status: active
Retrieved at: 2026-08-11
Methodology: Source model ID: openai/gpt-4.1-mini-2025-04-14. Source model name: GPT-4.1 mini. Provider reported by source: OpenAI. Model snapshot: gpt-4.1-mini-2025-04-14. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-08-06. Reasoning effort: high. Temperature: 1. Maximum output tokens: 32768. Latency in seconds: 3.307. Standard error: 1.676. Cost per task in USD: 0.000891. Source ID: vals-ai. Evidence capture ID: vals-corp_fin_v2-2026-08-11-d9e58d191cd9. Source payload hash: d9e58d191cd9f1690e3b59f0a37055813038531410f2d73e765676893c0f9526. Parser version: vals-astro-v2. Imported at: 2026-08-11
Comparison methodology: Reasoning effort: high. Temperature: 1. Maximum output tokens: 32768

Source Vals AI

CorpFin v2: Max Fitting Context (Show measurement, test conditions, and source)

Source value: 55.012
Score: 55.012
Metric: accuracy
Unit: %
Benchmark version: 2
Category: finance
Task: max_fitting_context
Task label: Max Fitting Context
Direction: Higher is better
Comparison cohort: vals-corp-fin-v2:2:max_fitting_context
Source type: independent-evaluator
Evaluator: Vals AI
Status: active
Retrieved at: 2026-08-11
Methodology: Source model ID: openai/gpt-4.1-mini-2025-04-14. Source model name: GPT-4.1 mini. Provider reported by source: OpenAI. Model snapshot: gpt-4.1-mini-2025-04-14. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-08-06. Reasoning effort: high. Temperature: 1. Maximum output tokens: 32768. Latency in seconds: 8.221. Standard error: 1.698. Cost per task in USD: 0.051823. Source ID: vals-ai. Evidence capture ID: vals-corp_fin_v2-2026-08-11-d9e58d191cd9. Source payload hash: d9e58d191cd9f1690e3b59f0a37055813038531410f2d73e765676893c0f9526. Parser version: vals-astro-v2. Imported at: 2026-08-11
Comparison methodology: Reasoning effort: high. Temperature: 1. Maximum output tokens: 32768

Source Vals AI

CorpFin v2: Overall (Show measurement, test conditions, and source)

Source value: 57.926
Score: 57.926
Metric: accuracy
Unit: %
Benchmark version: 2
Category: finance
Task: overall
Task label: Overall
Direction: Higher is better
Comparison cohort: vals-corp-fin-v2:2:overall
Source type: independent-evaluator
Evaluator: Vals AI
Status: active
Retrieved at: 2026-09-04
Methodology: Source model ID: openai/gpt-4.1-mini-2025-04-14. Source model name: GPT-4.1 mini. Model snapshot: gpt-4.1-mini-2025-04-14. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-08-12. Latency in seconds: 6.443. Cost per task in USD: 0.026113. Source ID: vals-ai. Evidence capture ID: vals-corp_fin_v2-2026-09-04-46dad6684551. Source payload hash: 46dad668455190ee4239b7c743d00d81c6fd3127e0d87123c518ec107c13b44d. Parser version: vals-astro-v2. Imported at: 2026-09-04

Source Vals AI

CorpFin v2: Shared Max Context (Show measurement, test conditions, and source)

Source value: 59.324
Score: 59.324
Metric: accuracy
Unit: %
Benchmark version: 2
Category: finance
Task: shared_max_context
Task label: Shared Max Context
Direction: Higher is better
Comparison cohort: vals-corp-fin-v2:2:shared_max_context
Source type: independent-evaluator
Evaluator: Vals AI
Status: active
Retrieved at: 2026-08-11
Methodology: Source model ID: openai/gpt-4.1-mini-2025-04-14. Source model name: GPT-4.1 mini. Provider reported by source: OpenAI. Model snapshot: gpt-4.1-mini-2025-04-14. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-08-06. Reasoning effort: high. Temperature: 1. Maximum output tokens: 32768. Latency in seconds: 7.8. Standard error: 1.677. Cost per task in USD: 0.025626. Source ID: vals-ai. Evidence capture ID: vals-corp_fin_v2-2026-08-11-d9e58d191cd9. Source payload hash: d9e58d191cd9f1690e3b59f0a37055813038531410f2d73e765676893c0f9526. Parser version: vals-astro-v2. Imported at: 2026-08-11
Comparison methodology: Reasoning effort: high. Temperature: 1. Maximum output tokens: 32768

Source Vals AI

GPQA Diamond: Few-Shot CoT (Show measurement, test conditions, and source)

Source value: 64.646
Score: 64.646
Metric: accuracy
Unit: %
Benchmark version: 1
Category: reasoning
Task: diamond_few_shot_cot
Task label: Few-Shot CoT
Direction: Higher is better
Comparison cohort: vals-gpqa:1:diamond_few_shot_cot
Source type: independent-evaluator
Evaluator: Vals AI
Status: active
Retrieved at: 2026-08-11
Methodology: Source model ID: openai/gpt-4.1-mini-2025-04-14. Source model name: GPT-4.1 mini. Provider reported by source: OpenAI. Model snapshot: gpt-4.1-mini-2025-04-14. Evaluator: Vals AI. Dataset type: public. Leaderboard date: 2026-08-09. Reasoning effort: high. Temperature: 1. Maximum output tokens: 32768. Latency in seconds: 8.974. Standard error: 3.397. Cost per task in USD: 0.002537. Source ID: vals-ai. Evidence capture ID: vals-gpqa-2026-08-11-d3325290a404. Source payload hash: d3325290a40411054e05ecb86812143465b4d8eee24a0f71f6cf5dfee5b232a1. Parser version: vals-astro-v2. Imported at: 2026-08-11
Comparison methodology: Reasoning effort: high. Temperature: 1. Maximum output tokens: 32768

Source Vals AI

GPQA Diamond: Zero-Shot CoT (Show measurement, test conditions, and source)

Source value: 71.212
Score: 71.212
Metric: accuracy
Unit: %
Benchmark version: 1
Category: reasoning
Task: diamond_zero_shot_cot
Task label: Zero-Shot CoT
Direction: Higher is better
Comparison cohort: vals-gpqa:1:diamond_zero_shot_cot
Source type: independent-evaluator
Evaluator: Vals AI
Status: active
Retrieved at: 2026-08-11
Methodology: Source model ID: openai/gpt-4.1-mini-2025-04-14. Source model name: GPT-4.1 mini. Provider reported by source: OpenAI. Model snapshot: gpt-4.1-mini-2025-04-14. Evaluator: Vals AI. Dataset type: public. Leaderboard date: 2026-08-09. Reasoning effort: high. Temperature: 1. Maximum output tokens: 32768. Latency in seconds: 9.589. Standard error: 3.25. Cost per task in USD: 0.002112. Source ID: vals-ai. Evidence capture ID: vals-gpqa-2026-08-11-d3325290a404. Source payload hash: d3325290a40411054e05ecb86812143465b4d8eee24a0f71f6cf5dfee5b232a1. Parser version: vals-astro-v2. Imported at: 2026-08-11
Comparison methodology: Reasoning effort: high. Temperature: 1. Maximum output tokens: 32768

Source Vals AI

GPQA Diamond: Overall (Show measurement, test conditions, and source)

Source value: 67.929
Score: 67.929
Metric: accuracy
Unit: %
Benchmark version: 1
Category: reasoning
Task: overall
Task label: Overall
Direction: Higher is better
Comparison cohort: vals-gpqa:1:overall
Source type: independent-evaluator
Evaluator: Vals AI
Status: active
Retrieved at: 2026-09-04
Methodology: Source model ID: openai/gpt-4.1-mini-2025-04-14. Source model name: GPT-4.1 mini. Model snapshot: gpt-4.1-mini-2025-04-14. Evaluator: Vals AI. Dataset type: public. Leaderboard date: 2026-09-01. Latency in seconds: 9.282. Cost per task in USD: 0.002324. Source ID: vals-ai. Evidence capture ID: vals-gpqa-2026-09-04-fc438726f0d8. Source payload hash: fc438726f0d8523d320f02d75ae372a3fa38b28b36f70fe318d119f55153560d. Parser version: vals-astro-v2. Imported at: 2026-09-04

Source Vals AI

LiveCodeBench v6: Easy (Show measurement, test conditions, and source)

Source value: 95.342
Score: 95.342
Metric: accuracy
Unit: %
Benchmark version: 1
Category: coding
Task: easy
Task label: Easy
Direction: Higher is better
Comparison cohort: vals-lcb:1:easy
Source type: independent-evaluator
Evaluator: Vals AI
Status: active
Retrieved at: 2026-08-11
Methodology: Source model ID: openai/gpt-4.1-mini-2025-04-14. Source model name: GPT-4.1 mini. Provider reported by source: OpenAI. Model snapshot: gpt-4.1-mini-2025-04-14. Evaluator: Vals AI. Dataset type: public. Leaderboard date: 2026-08-09. Reasoning effort: high. Temperature: 1. Maximum output tokens: 32768. Latency in seconds: 2.25. Standard error: 1.174. Cost per task in USD: 0.000377. Source ID: vals-ai. Evidence capture ID: vals-lcb-2026-08-11-0342bcc364e4. Source payload hash: 0342bcc364e4426ffb24589c2752c9225be61fbd26db8deba5bdab9775ce5a75. Parser version: vals-astro-v2. Imported at: 2026-08-11
Comparison methodology: Reasoning effort: high. Temperature: 1. Maximum output tokens: 32768

Source Vals AI

LiveCodeBench v6: Hard (Show measurement, test conditions, and source)

Source value: 21.429
Score: 21.429
Metric: accuracy
Unit: %
Benchmark version: 1
Category: coding
Task: hard
Task label: Hard
Direction: Higher is better
Comparison cohort: vals-lcb:1:hard
Source type: independent-evaluator
Evaluator: Vals AI
Status: active
Retrieved at: 2026-08-11
Methodology: Source model ID: openai/gpt-4.1-mini-2025-04-14. Source model name: GPT-4.1 mini. Provider reported by source: OpenAI. Model snapshot: gpt-4.1-mini-2025-04-14. Evaluator: Vals AI. Dataset type: public. Leaderboard date: 2026-08-09. Reasoning effort: high. Temperature: 1. Maximum output tokens: 32768. Latency in seconds: 62.607. Standard error: 2.193. Cost per task in USD: 0.002221. Source ID: vals-ai. Evidence capture ID: vals-lcb-2026-08-11-0342bcc364e4. Source payload hash: 0342bcc364e4426ffb24589c2752c9225be61fbd26db8deba5bdab9775ce5a75. Parser version: vals-astro-v2. Imported at: 2026-08-11
Comparison methodology: Reasoning effort: high. Temperature: 1. Maximum output tokens: 32768

Source Vals AI

LiveCodeBench v6: Medium (Show measurement, test conditions, and source)

Source value: 57.702
Score: 57.702
Metric: accuracy
Unit: %
Benchmark version: 1
Category: coding
Task: medium
Task label: Medium
Direction: Higher is better
Comparison cohort: vals-lcb:1:medium
Source type: independent-evaluator
Evaluator: Vals AI
Status: active
Retrieved at: 2026-08-11
Methodology: Source model ID: openai/gpt-4.1-mini-2025-04-14. Source model name: GPT-4.1 mini. Provider reported by source: OpenAI. Model snapshot: gpt-4.1-mini-2025-04-14. Evaluator: Vals AI. Dataset type: public. Leaderboard date: 2026-08-09. Reasoning effort: high. Temperature: 1. Maximum output tokens: 32768. Latency in seconds: 17.92. Standard error: 2.524. Cost per task in USD: 0.000936. Source ID: vals-ai. Evidence capture ID: vals-lcb-2026-08-11-0342bcc364e4. Source payload hash: 0342bcc364e4426ffb24589c2752c9225be61fbd26db8deba5bdab9775ce5a75. Parser version: vals-astro-v2. Imported at: 2026-08-11
Comparison methodology: Reasoning effort: high. Temperature: 1. Maximum output tokens: 32768

Source Vals AI

LiveCodeBench v6: Overall (Show measurement, test conditions, and source)

Source value: 58.158
Score: 58.158
Metric: accuracy
Unit: %
Benchmark version: 1
Category: coding
Task: overall
Task label: Overall
Direction: Higher is better
Comparison cohort: vals-lcb:1:overall
Source type: independent-evaluator
Evaluator: Vals AI
Status: active
Retrieved at: 2026-09-04
Methodology: Source model ID: openai/gpt-4.1-mini-2025-04-14. Source model name: GPT-4.1 mini. Model snapshot: gpt-4.1-mini-2025-04-14. Evaluator: Vals AI. Dataset type: public. Leaderboard date: 2026-09-01. Latency in seconds: 27.592. Cost per task in USD: 0.001178. Source ID: vals-ai. Evidence capture ID: vals-lcb-2026-09-04-95ca83387127. Source payload hash: 95ca83387127df287e9a6d928c411c98c9b65b4cefeee46eb4008ca1521f5ed4. Parser version: vals-astro-v2. Imported at: 2026-09-04

Source Vals AI

Our model tests

Community tests you can inspect

Compare how the models respond to the same prompt. Each test shows the first attempt, with no subsequent fixes to the generated code. These results do not contribute to an overall score.

Pelican on a bicycle

A community classic for free-form SVG drawing.

GPT-4.1 mini

Not tested yet

Prompt and test conditions

Generate an SVG of a pelican riding a bicycle

Token limit including reasoning: 8,192 tokens

Task origin (Simon Willison)

GPT-4.1 mini

Published benchmarks

VISTA

Finance

CorpFin v2

CorpFin v2

CorpFin v2

CorpFin v2

Reasoning

GPQA Diamond

GPQA Diamond

GPQA Diamond

Coding

LiveCodeBench v6

LiveCodeBench v6

LiveCodeBench v6

LiveCodeBench v6

Recorded measurement details

Community tests you can inspect

Pelican on a bicycle

Specifications and access

Additional source observations

Published prices

100 API requests

Compare this model

Sources and data date