Language modelActive

Gemini 3.1 Flash-Lite

Google

Released: February 2026
Data date: September 8, 2026

Intelligence: Not ranked
Overall score
Speed: 315 tokens/s
Output throughput
Price: $0.25 · $1.5
Input · Output / 1M tokens
Input: Text, Image, Audio, Video
Output: Text

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

Entries 1-12 of 130. Page 1 of 11.

Published benchmarks

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

TutorBench

Overall

What this benchmark measures: 1,490 tasks test adaptive explanations, feedback, and hints across six STEM subjects.

Context: A Claude 4 Sonnet judge scores weighted rubrics, so strong results do not prove safe tutoring of real learners.

Higher is better8 modelsGemini 3.1 Flash-Lite: Rank 6 of 8Data date: August 26, 2026

1.GPT-5.4 Pro56.62%

2.Gemini 2.5 Pro55.65%

3.GPT-555.33%

4.o3-pro54.62%

5.Gemini 3.1 Pro Preview52.99%

6.Gemini 3.1 Flash-Lite51.5%

7.Llama 4 Maverick40.2%

8.GPT-4o36.12%

Scale: 0% - 100%

Source: Scale AI

CC BY 4.0

gradually.ai

Methodology and context

Comparison cohort: scale-tutorbench-overall
Metric: weighted rubric score
Scale: 0-100
Participants: 8
Methodology and context: 1,490 tasks with weighted rubrics and Claude 4 Sonnet as judge.. Source model ID: curated/gemini-3.1-flash-lite. Source model name: Gemini 3.1 Flash-Lite. Provider reported by source: Google. Evaluator: Scale AI. Dataset type: public. Attempts: pass@1. Score display: 51.5% ± 1.04. Source ID: scale-ai. Evidence capture ID: curated-scale-ai-2026-08-26-b9d2857e0533. Source payload hash: b9d2857e0533b70e6dacdf8d12a36816aa5704941213476aa6e699f087ec4ff0. Parser version: curated-v1. Imported at: 2026-09-04

Source: Scale AI

Coding

4 measurements

Code Migration

CLI

Higher is better6 modelsGemini 3.1 Flash-Lite: Rank 6 of 6Data date: August 11, 2026

1.Gemini 3.6 Flash19.33%

2.Gemini 3.5 Flash17.18%

3.Gemini 3.1 Pro Preview10.83%

4.Gemini 3 Flash8.52%

5.Gemini 3.5 Flash-Lite5.88%

6.Gemini 3.1 Flash-Lite5.73%

Scale: 0% - 100%

Source: Vals AI

CC BY 4.0

gradually.ai

Methodology and context

Comparison cohort: vals-code-migration:1:cli
Metric: accuracy
Scale: 0-100
Participants: 6
Methodology and context: Source model ID: google/gemini-3.1-flash-lite-preview. Source model name: Gemini 3.1 Flash-Lite. Provider reported by source: Google. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-08-09. Reasoning effort: high. Temperature: 1. Maximum output tokens: 65536. Latency in seconds: 87.657. Standard error: 1.363. Cost per task in USD: 0.052306. Source ID: vals-ai. Evidence capture ID: vals-code-migration-2026-08-11-3a2d5ce718a3. Source payload hash: 3a2d5ce718a34b36c00a1447644df407304422f4ce9a7feb98488c4a04ea39cd. Parser version: vals-astro-v2. Imported at: 2026-08-11

Source: Vals AI

Code Migration

COBOL

Higher is better6 modelsGemini 3.1 Flash-Lite: Rank 5 of 6Data date: August 11, 2026

1.Gemini 3.6 Flash65.71%

2.Gemini 3.5 Flash55.46%

3.Gemini 3.1 Pro Preview36.75%

4.Gemini 3.5 Flash-Lite6.96%

5.Gemini 3.1 Flash-Lite1.25%

6.Gemini 3 Flash0%

Scale: 0% - 100%

Source: Vals AI

CC BY 4.0

gradually.ai

Methodology and context

Comparison cohort: vals-code-migration:1:cobol
Metric: accuracy
Scale: 0-100
Participants: 6
Methodology and context: Source model ID: google/gemini-3.1-flash-lite-preview. Source model name: Gemini 3.1 Flash-Lite. Provider reported by source: Google. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-08-09. Reasoning effort: high. Temperature: 1. Maximum output tokens: 65536. Latency in seconds: 107.549. Standard error: 1.25. Cost per task in USD: 0.055194. Source ID: vals-ai. Evidence capture ID: vals-code-migration-2026-08-11-3a2d5ce718a3. Source payload hash: 3a2d5ce718a34b36c00a1447644df407304422f4ce9a7feb98488c4a04ea39cd. Parser version: vals-astro-v2. Imported at: 2026-08-11

Source: Vals AI

Code Migration

Code Quality

Higher is better6 modelsGemini 3.1 Flash-Lite: Rank 3 of 6Data date: August 11, 2026

1.Gemini 3.6 Flash3.3 rating

2.Gemini 3.5 Flash2.79 rating

3.Gemini 3.1 Flash-Lite2.66 rating

4.Gemini 3 Flash2.66 rating

5.Gemini 3.5 Flash-Lite2.65 rating

6.Gemini 3.1 Pro Preview2.54 rating

Scale: 0 rating - 3.3 rating

Source: Vals AI

CC BY 4.0

gradually.ai

Methodology and context

Comparison cohort: vals-code-migration:1:code_quality
Metric: mean reviewer code-quality rating
Scale: No upper bound is documented. The chart spans the recorded values and zero.
Participants: 6
Methodology and context: Source model ID: google/gemini-3.1-flash-lite-preview. Source model name: Gemini 3.1 Flash-Lite. Provider reported by source: Google. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-08-09. Reasoning effort: high. Temperature: 1. Maximum output tokens: 65536. Latency in seconds: 92.63. Standard error: 0.038. Cost per task in USD: 0.053028. Score display: 2.664 / 5. Source ID: vals-ai. Evidence capture ID: vals-code-migration-2026-08-11-3a2d5ce718a3. Source payload hash: 3a2d5ce718a34b36c00a1447644df407304422f4ce9a7feb98488c4a04ea39cd. Parser version: vals-astro-v2. Imported at: 2026-08-11

Source: Vals AI

Code Migration

Overall

Higher is better35 modelsGemini 3.1 Flash-Lite: Rank 35 of 35Data date: September 4, 2026

1.GPT-6 Astra67.74%

2.Claude Opus 557.47%

3.Claude Fable 555.07%

4.GPT-5.6 Sol52.92%

5.GPT-5.6 Terra47.8%

6.GPT-5.545.16%

7.Grok 4.644.57%

8.GPT-5.6 Luna44.55%

9.Claude Sonnet 544.39%

10.GLM-5.344.22%

11.GLM-5.237.87%

12.Grok 4.536.6%

13.Gemini 3.8 Flash36.55%

14.GPT-5.434.98%

15.Gemini 3.7 Flash34.8%

16.Gemini 3.6 Flash30.93%

17.Kimi K2.627.77%

18.Gemini 3.5 Flash26.75%

19.DeepSeek-V4-Pro26.2%

20.GLM-5.125.77%

21.Kimi K2.7 Code25.39%

22.MiMo-V2.5-Pro21.56%

23.GLM-5.3-Flash20.52%

24.Gemini 3.1 Pro Preview17.31%

25.Kimi K316.1%

26.GPT-5.4 nano14.47%

27.MiMo-V2.514.23%

28.Inkling Small13.68%

29.GPT-5.4 mini12.94%

30.Inkling11.79%

31.Kimi K2.56.96%

32.Grok 4.36.8%

33.Gemini 3 Flash6.39%

34.Gemini 3.5 Flash-Lite6.15%

35.Gemini 3.1 Flash-Lite4.61%

Scale: 0% - 100%

Source: Vals AI

CC BY 4.0

gradually.ai

Methodology and context

Comparison cohort: vals-code-migration:1:overall
Metric: accuracy
Scale: 0-100
Participants: 35
Methodology and context: Source model ID: google/gemini-3.1-flash-lite-preview. Source model name: Gemini 3.1 Flash-Lite. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-09-03. Latency in seconds: 92.63. Cost per task in USD: 0.053028. Source ID: vals-ai. Evidence capture ID: vals-code-migration-2026-09-04-37e66450d0d6. Source payload hash: 37e66450d0d6f681e77c4fe9942f74c0aa743078002f50aef50932407223f88f. Parser version: vals-astro-v2. Imported at: 2026-09-04

Source: Vals AI

Finance

7 measurements

CorpFin v2

Exact Pages

Higher is better6 modelsGemini 3.1 Flash-Lite: Rank 6 of 6Data date: August 11, 2026

1.Gemini 3 Flash68.07%

2.Gemini 3.5 Flash62.82%

3.Gemini 3.6 Flash61.07%

4.Gemini 3.1 Pro Preview60.84%

5.Gemini 3.5 Flash-Lite57.46%

6.Gemini 3.1 Flash-Lite56.64%

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: 6
Methodology and context: Source model ID: google/gemini-3.1-flash-lite-preview. Source model name: Gemini 3.1 Flash-Lite. Provider reported by source: Google. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-08-06. Reasoning effort: high. Temperature: 1. Maximum output tokens: 65536. Latency in seconds: 3.379. Standard error: 1.692. Cost per task in USD: 0.001726. 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 better6 modelsGemini 3.1 Flash-Lite: Rank 6 of 6Data date: August 11, 2026

1.Gemini 3.1 Pro Preview66.9%

2.Gemini 3.5 Flash66.67%

3.Gemini 3.6 Flash65.39%

4.Gemini 3 Flash63.52%

5.Gemini 3.5 Flash-Lite62.35%

6.Gemini 3.1 Flash-Lite60.61%

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: 6
Methodology and context: Source model ID: google/gemini-3.1-flash-lite-preview. Source model name: Gemini 3.1 Flash-Lite. Provider reported by source: Google. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-08-06. Reasoning effort: high. Temperature: 1. Maximum output tokens: 65536. Latency in seconds: 4.003. Standard error: 1.668. Cost per task in USD: 0.048652. 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 modelsGemini 3.1 Flash-Lite: Rank 37 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: google/gemini-3.1-flash-lite-preview. Source model name: Gemini 3.1 Flash-Lite. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-08-12. Latency in seconds: 4.03. Cost per task in USD: 0.022927. 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 better6 modelsGemini 3.1 Flash-Lite: Rank 6 of 6Data date: August 11, 2026

1.Gemini 3 Flash67.72%

2.Gemini 3.1 Pro Preview65.73%

3.Gemini 3.5 Flash64.57%

4.Gemini 3.6 Flash63.52%

5.Gemini 3.5 Flash-Lite62.24%

6.Gemini 3.1 Flash-Lite60.84%

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: 6
Methodology and context: Source model ID: google/gemini-3.1-flash-lite-preview. Source model name: Gemini 3.1 Flash-Lite. Provider reported by source: Google. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-08-06. Reasoning effort: high. Temperature: 1. Maximum output tokens: 65536. Latency in seconds: 4.708. Standard error: 1.666. Cost per task in USD: 0.018404. 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

EMB

Comps

Higher is better5 modelsGemini 3.1 Flash-Lite: Rank 5 of 5Data date: August 11, 2026

1.Gemini 3.6 Flash70.02%

2.Gemini 3.5 Flash69.79%

3.Gemini 3.5 Flash-Lite46.42%

4.Gemini 3.1 Pro Preview44.51%

5.Gemini 3.1 Flash-Lite10.48%

Scale: 0% - 100%

Source: Vals AI

CC BY 4.0

gradually.ai

Methodology and context

Comparison cohort: vals-emb:1:comps
Metric: accuracy
Scale: 0-100
Participants: 5
Methodology and context: Source model ID: google/gemini-3.1-flash-lite-preview. Source model name: Gemini 3.1 Flash-Lite. Provider reported by source: Google. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-08-06. Reasoning effort: high. Temperature: 1. Maximum output tokens: 65536. Latency in seconds: 101.863. Standard error: 3.475. Cost per task in USD: 0.182456. Source ID: vals-ai. Evidence capture ID: vals-emb-2026-08-11-e3c855e236e4. Source payload hash: e3c855e236e40ec36df381a2b071729e420cedac89f9952ba182537e87054999. Parser version: vals-astro-v2. Imported at: 2026-08-11

Source: Vals AI

EMB

Dataroom

Higher is better5 modelsGemini 3.1 Flash-Lite: Rank 5 of 5Data date: August 11, 2026

1.Gemini 3.5 Flash80.92%

2.Gemini 3.1 Pro Preview79.17%

3.Gemini 3.6 Flash72.97%

4.Gemini 3.5 Flash-Lite57.69%

5.Gemini 3.1 Flash-Lite15.18%

Scale: 0% - 100%

Source: Vals AI

CC BY 4.0

gradually.ai

Methodology and context

Comparison cohort: vals-emb:1:dataroom
Metric: accuracy
Scale: 0-100
Participants: 5
Methodology and context: Source model ID: google/gemini-3.1-flash-lite-preview. Source model name: Gemini 3.1 Flash-Lite. Provider reported by source: Google. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-08-06. Reasoning effort: high. Temperature: 1. Maximum output tokens: 65536. Latency in seconds: 84.269. Standard error: 5.151. Cost per task in USD: 0.050422. Source ID: vals-ai. Evidence capture ID: vals-emb-2026-08-11-e3c855e236e4. Source payload hash: e3c855e236e40ec36df381a2b071729e420cedac89f9952ba182537e87054999. Parser version: vals-astro-v2. Imported at: 2026-08-11

Source: Vals AI

EMB

DCF

Higher is better5 modelsGemini 3.1 Flash-Lite: Rank 5 of 5Data date: August 11, 2026

1.Gemini 3.6 Flash59.41%

2.Gemini 3.5 Flash58.36%

3.Gemini 3.1 Pro Preview46.39%

4.Gemini 3.5 Flash-Lite33.61%

5.Gemini 3.1 Flash-Lite5.1%

Scale: 0% - 100%

Source: Vals AI

CC BY 4.0

gradually.ai

Methodology and context

Comparison cohort: vals-emb:1:dcf
Metric: accuracy
Scale: 0-100
Participants: 5
Methodology and context: Source model ID: google/gemini-3.1-flash-lite-preview. Source model name: Gemini 3.1 Flash-Lite. Provider reported by source: Google. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-08-06. Reasoning effort: high. Temperature: 1. Maximum output tokens: 65536. Latency in seconds: 64.7. Standard error: 1.006. Cost per task in USD: 0.046823. Source ID: vals-ai. Evidence capture ID: vals-emb-2026-08-11-e3c855e236e4. Source payload hash: e3c855e236e40ec36df381a2b071729e420cedac89f9952ba182537e87054999. Parser version: vals-astro-v2. Imported at: 2026-08-11

Source: Vals AI

Recorded measurement details

Every observation retains its source value and published test conditions.

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

Source value: 51.5
Score: 51.5
Metric: weighted rubric score
Unit: %
Benchmark version: 1,490-task release
Category: education
Task: overall
Task label: Overall
Direction: Higher is better
Comparison cohort: scale-tutorbench-overall
Confidence interval: 1.04
Source type: official-leaderboard
Evaluator: Scale AI
Status: active
Retrieved at: 2026-08-26
Methodology: 1,490 tasks with weighted rubrics and Claude 4 Sonnet as judge.. Source model ID: curated/gemini-3.1-flash-lite. Source model name: Gemini 3.1 Flash-Lite. Provider reported by source: Google. Evaluator: Scale AI. Dataset type: public. Attempts: pass@1. Score display: 51.5% ± 1.04. Source ID: scale-ai. Evidence capture ID: curated-scale-ai-2026-08-26-b9d2857e0533. Source payload hash: b9d2857e0533b70e6dacdf8d12a36816aa5704941213476aa6e699f087ec4ff0. Parser version: curated-v1. Imported at: 2026-09-04
Comparison methodology: 1,490 tasks with weighted rubrics and Claude 4 Sonnet as judge.

Source Scale AI

Code Migration: CLI (Show measurement, test conditions, and source)

Source value: 5.729
Score: 5.729
Metric: accuracy
Unit: %
Benchmark version: 1
Category: coding
Task: cli
Task label: CLI
Direction: Higher is better
Comparison cohort: vals-code-migration:1:cli
Source type: independent-evaluator
Evaluator: Vals AI
Status: active
Retrieved at: 2026-08-11
Methodology: Source model ID: google/gemini-3.1-flash-lite-preview. Source model name: Gemini 3.1 Flash-Lite. Provider reported by source: Google. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-08-09. Reasoning effort: high. Temperature: 1. Maximum output tokens: 65536. Latency in seconds: 87.657. Standard error: 1.363. Cost per task in USD: 0.052306. Source ID: vals-ai. Evidence capture ID: vals-code-migration-2026-08-11-3a2d5ce718a3. Source payload hash: 3a2d5ce718a34b36c00a1447644df407304422f4ce9a7feb98488c4a04ea39cd. Parser version: vals-astro-v2. Imported at: 2026-08-11
Comparison methodology: Reasoning effort: high. Temperature: 1. Maximum output tokens: 65536

Source Vals AI

Code Migration: COBOL (Show measurement, test conditions, and source)

Source value: 1.25
Score: 1.25
Metric: accuracy
Unit: %
Benchmark version: 1
Category: coding
Task: cobol
Task label: COBOL
Direction: Higher is better
Comparison cohort: vals-code-migration:1:cobol
Source type: independent-evaluator
Evaluator: Vals AI
Status: active
Retrieved at: 2026-08-11
Methodology: Source model ID: google/gemini-3.1-flash-lite-preview. Source model name: Gemini 3.1 Flash-Lite. Provider reported by source: Google. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-08-09. Reasoning effort: high. Temperature: 1. Maximum output tokens: 65536. Latency in seconds: 107.549. Standard error: 1.25. Cost per task in USD: 0.055194. Source ID: vals-ai. Evidence capture ID: vals-code-migration-2026-08-11-3a2d5ce718a3. Source payload hash: 3a2d5ce718a34b36c00a1447644df407304422f4ce9a7feb98488c4a04ea39cd. Parser version: vals-astro-v2. Imported at: 2026-08-11
Comparison methodology: Reasoning effort: high. Temperature: 1. Maximum output tokens: 65536

Source Vals AI

Code Migration: Code Quality (Show measurement, test conditions, and source)

Source value: 2.664
Score: 2.664
Metric: mean reviewer code-quality rating
Unit: rating
Benchmark version: 1
Category: coding
Task: code_quality
Task label: Code Quality
Direction: Higher is better
Comparison cohort: vals-code-migration:1:code_quality
Source type: independent-evaluator
Evaluator: Vals AI
Status: active
Retrieved at: 2026-08-11
Methodology: Source model ID: google/gemini-3.1-flash-lite-preview. Source model name: Gemini 3.1 Flash-Lite. Provider reported by source: Google. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-08-09. Reasoning effort: high. Temperature: 1. Maximum output tokens: 65536. Latency in seconds: 92.63. Standard error: 0.038. Cost per task in USD: 0.053028. Score display: 2.664 / 5. Source ID: vals-ai. Evidence capture ID: vals-code-migration-2026-08-11-3a2d5ce718a3. Source payload hash: 3a2d5ce718a34b36c00a1447644df407304422f4ce9a7feb98488c4a04ea39cd. Parser version: vals-astro-v2. Imported at: 2026-08-11
Comparison methodology: Reasoning effort: high. Temperature: 1. Maximum output tokens: 65536

Source Vals AI

Code Migration: Overall (Show measurement, test conditions, and source)

Source value: 4.609
Score: 4.609
Metric: accuracy
Unit: %
Benchmark version: 1
Category: coding
Task: overall
Task label: Overall
Direction: Higher is better
Comparison cohort: vals-code-migration:1:overall
Source type: independent-evaluator
Evaluator: Vals AI
Status: active
Retrieved at: 2026-09-04
Methodology: Source model ID: google/gemini-3.1-flash-lite-preview. Source model name: Gemini 3.1 Flash-Lite. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-09-03. Latency in seconds: 92.63. Cost per task in USD: 0.053028. Source ID: vals-ai. Evidence capture ID: vals-code-migration-2026-09-04-37e66450d0d6. Source payload hash: 37e66450d0d6f681e77c4fe9942f74c0aa743078002f50aef50932407223f88f. Parser version: vals-astro-v2. Imported at: 2026-09-04

Source Vals AI

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

Source value: 56.643
Score: 56.643
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: google/gemini-3.1-flash-lite-preview. Source model name: Gemini 3.1 Flash-Lite. Provider reported by source: Google. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-08-06. Reasoning effort: high. Temperature: 1. Maximum output tokens: 65536. Latency in seconds: 3.379. Standard error: 1.692. Cost per task in USD: 0.001726. 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: 65536

Source Vals AI

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

Source value: 60.606
Score: 60.606
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: google/gemini-3.1-flash-lite-preview. Source model name: Gemini 3.1 Flash-Lite. Provider reported by source: Google. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-08-06. Reasoning effort: high. Temperature: 1. Maximum output tokens: 65536. Latency in seconds: 4.003. Standard error: 1.668. Cost per task in USD: 0.048652. 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: 65536

Source Vals AI

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

Source value: 59.363
Score: 59.363
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: google/gemini-3.1-flash-lite-preview. Source model name: Gemini 3.1 Flash-Lite. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-08-12. Latency in seconds: 4.03. Cost per task in USD: 0.022927. 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: 60.839
Score: 60.839
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: google/gemini-3.1-flash-lite-preview. Source model name: Gemini 3.1 Flash-Lite. Provider reported by source: Google. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-08-06. Reasoning effort: high. Temperature: 1. Maximum output tokens: 65536. Latency in seconds: 4.708. Standard error: 1.666. Cost per task in USD: 0.018404. 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: 65536

Source Vals AI

EMB: Comps (Show measurement, test conditions, and source)

Source value: 10.48
Score: 10.48
Metric: accuracy
Unit: %
Benchmark version: 1
Category: finance
Task: comps
Task label: Comps
Direction: Higher is better
Comparison cohort: vals-emb:1:comps
Source type: independent-evaluator
Evaluator: Vals AI
Status: active
Retrieved at: 2026-08-11
Methodology: Source model ID: google/gemini-3.1-flash-lite-preview. Source model name: Gemini 3.1 Flash-Lite. Provider reported by source: Google. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-08-06. Reasoning effort: high. Temperature: 1. Maximum output tokens: 65536. Latency in seconds: 101.863. Standard error: 3.475. Cost per task in USD: 0.182456. Source ID: vals-ai. Evidence capture ID: vals-emb-2026-08-11-e3c855e236e4. Source payload hash: e3c855e236e40ec36df381a2b071729e420cedac89f9952ba182537e87054999. Parser version: vals-astro-v2. Imported at: 2026-08-11
Comparison methodology: Reasoning effort: high. Temperature: 1. Maximum output tokens: 65536

Source Vals AI

EMB: Dataroom (Show measurement, test conditions, and source)

Source value: 15.178
Score: 15.178
Metric: accuracy
Unit: %
Benchmark version: 1
Category: finance
Task: dataroom
Task label: Dataroom
Direction: Higher is better
Comparison cohort: vals-emb:1:dataroom
Source type: independent-evaluator
Evaluator: Vals AI
Status: active
Retrieved at: 2026-08-11
Methodology: Source model ID: google/gemini-3.1-flash-lite-preview. Source model name: Gemini 3.1 Flash-Lite. Provider reported by source: Google. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-08-06. Reasoning effort: high. Temperature: 1. Maximum output tokens: 65536. Latency in seconds: 84.269. Standard error: 5.151. Cost per task in USD: 0.050422. Source ID: vals-ai. Evidence capture ID: vals-emb-2026-08-11-e3c855e236e4. Source payload hash: e3c855e236e40ec36df381a2b071729e420cedac89f9952ba182537e87054999. Parser version: vals-astro-v2. Imported at: 2026-08-11
Comparison methodology: Reasoning effort: high. Temperature: 1. Maximum output tokens: 65536

Source Vals AI

EMB: DCF (Show measurement, test conditions, and source)

Source value: 5.098
Score: 5.098
Metric: accuracy
Unit: %
Benchmark version: 1
Category: finance
Task: dcf
Task label: DCF
Direction: Higher is better
Comparison cohort: vals-emb:1:dcf
Source type: independent-evaluator
Evaluator: Vals AI
Status: active
Retrieved at: 2026-08-11
Methodology: Source model ID: google/gemini-3.1-flash-lite-preview. Source model name: Gemini 3.1 Flash-Lite. Provider reported by source: Google. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-08-06. Reasoning effort: high. Temperature: 1. Maximum output tokens: 65536. Latency in seconds: 64.7. Standard error: 1.006. Cost per task in USD: 0.046823. Source ID: vals-ai. Evidence capture ID: vals-emb-2026-08-11-e3c855e236e4. Source payload hash: e3c855e236e40ec36df381a2b071729e420cedac89f9952ba182537e87054999. Parser version: vals-astro-v2. Imported at: 2026-08-11
Comparison methodology: Reasoning effort: high. Temperature: 1. Maximum output tokens: 65536

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.

Gemini 3.1 Flash-Lite

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)

Evidence

Sources and data date

Every statement links to its underlying documentation or leaderboard.

Speed: Google. Output speed after the first streaming chunk, not total response time. Classified as deprecated by Artificial Analysis. Artificial Analysis maintains only the default 10K-input workload there. Retrieved September 8, 2026.
Artificial Analysis Methodology
Price: Base API prices without caching or batch discounts. Higher context tiers and other rates are listed under Costs.
Pricing
Input: Documented modalities. Retrieved September 8, 2026.
Model documentation
Output: Documented modalities. Retrieved September 8, 2026.
Model documentation

Research date September 8, 2026. 4 source URLs checked. This documents the inspected sources, not an exhaustive inventory of every publication.

Open evidence questions and research notes (original wording)

Not found in the inspected sources

parameters-billions. Google does not publish a parameter count on the Gemini API model page.

Not found in the inspected sources

active-parameters-billions. Google does not publish active parameter counts for Gemini API models.

Model metadataSource
Context window data (retrieved September 8, 2026)Source
API pricingSource
Scale AI (retrieved August 26, 2026)Source
Vals AI (retrieved August 11, 2026; September 4, 2026)Source
Vals AI (retrieved September 4, 2026)Source
Vals AI (retrieved August 11, 2026; September 4, 2026)Source
Vals AI (retrieved August 11, 2026; September 4, 2026)Source
Vals AI (retrieved August 11, 2026; September 4, 2026)Source
Vals AI (retrieved August 11, 2026; September 4, 2026)Source
Vals AI (retrieved August 11, 2026; September 4, 2026)Source
Vals AI (retrieved August 11, 2026; September 4, 2026)Source
Vals AI (retrieved September 4, 2026)Source
Vals AI (retrieved August 11, 2026; September 4, 2026)Source
Vals AI (retrieved September 4, 2026)Source
Vals AI (retrieved September 4, 2026)Source
Vals AI (retrieved September 4, 2026)Source
Vals AI (retrieved August 11, 2026; September 4, 2026)Source
Vals AI (retrieved September 4, 2026)Source
Vals AI (retrieved August 11, 2026; September 4, 2026)Source
Vals AI (retrieved August 11, 2026; September 4, 2026)Source
Vals AI (retrieved August 11, 2026; September 4, 2026)Source
Vals AI (retrieved August 11, 2026; September 4, 2026)Source
Vals AI (retrieved August 11, 2026; September 4, 2026)Source
Vals AI (retrieved August 11, 2026; September 4, 2026)Source
Vals AI (retrieved August 11, 2026; September 4, 2026)Source
Vals AI (retrieved August 11, 2026; September 4, 2026)Source
Vals AI (retrieved August 11, 2026; September 4, 2026)Source
Vals AI (retrieved September 4, 2026)Source
Google DeepMind (retrieved September 8, 2026)Source
Artificial Analysis (retrieved September 8, 2026)Source
Model metadata (retrieved September 8, 2026)Source
Speed measurement methodologySource

Gemini 3.1 Flash-Lite

Published benchmarks

TutorBench

Coding

Code Migration

Code Migration

Code Migration

Code Migration

Finance

CorpFin v2

CorpFin v2

CorpFin v2

CorpFin v2

EMB

EMB

EMB

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