Gemini 2.5 Flash-Lite
Not tested yet
Language modelActive
Gemini 2.5 Flash-Lite
- Released
- May 2025
- Data date
- September 8, 2026
- Intelligence
- Overall score
- Speed
- 325.9 tokens/sOutput throughput
- Price
- 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 26. Page 1 of 3.
Published benchmarks
Each chart compares models in the same documented test and highlights the current model.
Health
2 measurementsMedCode
Overall
Higher is better40 modelsGemini 2.5 Flash-Lite: Rank 40 of 40Data date: September 4, 2026
Scale: 0% - 100%
Methodology and context
- Comparison cohort
- vals-medcode:1:overall
- Metric
- accuracy
- Scale
- 0-100
- Participants
- 40
- Methodology and context
- Source model ID: google/gemini-2.5-flash-lite. Source model name: Gemini 2.5 Flash-Lite. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-09-03. Latency in seconds: 5.746. Cost per task in USD: 0.001342. Source ID: vals-ai. Evidence capture ID: vals-medcode-2026-09-04-c44942e3604f. Source payload hash: c44942e3604fa8eca13f660a1551cfa5ea9bbf9c67af141f41601402afceb569. Parser version: vals-astro-v2. Imported at: 2026-09-04
MedScribe
Overall
Higher is better41 modelsGemini 2.5 Flash-Lite: Rank 34 of 41Data date: September 4, 2026
Scale: 0% - 100%
Methodology and context
- Comparison cohort
- vals-medscribe:1:overall
- Metric
- accuracy
- Scale
- 0-100
- Participants
- 41
- Methodology and context
- Source model ID: google/gemini-2.5-flash-lite. Source model name: Gemini 2.5 Flash-Lite. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-09-03. Latency in seconds: 4.847. Cost per task in USD: 0.001211. Source ID: vals-ai. Evidence capture ID: vals-medscribe-2026-09-04-c86df6ced023. Source payload hash: c86df6ced023af4a251d97cf5f91df5f06151cd899b2529a2256d12e0656995a. Parser version: vals-astro-v2. Imported at: 2026-09-04
Education
5 measurementsSAGE
Automata
Higher is better4 modelsGemini 2.5 Flash-Lite: Rank 3 of 4Data date: August 11, 2026
Scale: 0% - 100%
Methodology and context
- Comparison cohort
- vals-sage:1:automata
- Metric
- accuracy
- Scale
- 0-100
- Participants
- 4
- Methodology and context
- Source model ID: google/gemini-2.5-flash-lite. Source model name: Gemini 2.5 Flash-Lite. Provider reported by source: Google. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-08-09. Temperature: 1. Maximum output tokens: 30000. Latency in seconds: 10.448. Standard error: 6.023. Cost per task in USD: 0.000876. Source ID: vals-ai. Evidence capture ID: vals-sage-2026-08-11-f1f79f6d8af3. Source payload hash: f1f79f6d8af3af8a952baa6793df3cdbd11ccfc53c0b95683b89817df366a496. Parser version: vals-astro-v2. Imported at: 2026-08-11
SAGE
Calculus
Higher is better4 modelsGemini 2.5 Flash-Lite: Rank 4 of 4Data date: August 11, 2026
Scale: 0% - 100%
Methodology and context
- Comparison cohort
- vals-sage:1:calculus
- Metric
- accuracy
- Scale
- 0-100
- Participants
- 4
- Methodology and context
- Source model ID: google/gemini-2.5-flash-lite. Source model name: Gemini 2.5 Flash-Lite. Provider reported by source: Google. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-08-09. Temperature: 1. Maximum output tokens: 30000. Latency in seconds: 13.337. Standard error: 4.298. Cost per task in USD: 0.001699. Source ID: vals-ai. Evidence capture ID: vals-sage-2026-08-11-f1f79f6d8af3. Source payload hash: f1f79f6d8af3af8a952baa6793df3cdbd11ccfc53c0b95683b89817df366a496. Parser version: vals-astro-v2. Imported at: 2026-08-11
SAGE
Linear Algebra
Higher is better4 modelsGemini 2.5 Flash-Lite: Rank 4 of 4Data date: August 11, 2026
Scale: 0% - 100%
Methodology and context
- Comparison cohort
- vals-sage:1:linear_algebra
- Metric
- accuracy
- Scale
- 0-100
- Participants
- 4
- Methodology and context
- Source model ID: google/gemini-2.5-flash-lite. Source model name: Gemini 2.5 Flash-Lite. Provider reported by source: Google. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-08-09. Temperature: 1. Maximum output tokens: 30000. Latency in seconds: 18.12. Standard error: 5.077. Cost per task in USD: 0.000791. Source ID: vals-ai. Evidence capture ID: vals-sage-2026-08-11-f1f79f6d8af3. Source payload hash: f1f79f6d8af3af8a952baa6793df3cdbd11ccfc53c0b95683b89817df366a496. Parser version: vals-astro-v2. Imported at: 2026-08-11
SAGE
Overall
Higher is better35 modelsGemini 2.5 Flash-Lite: Rank 34 of 35Data date: September 4, 2026
Scale: 0% - 100%
Methodology and context
- Comparison cohort
- vals-sage:1:overall
- Metric
- accuracy
- Scale
- 0-100
- Participants
- 35
- Methodology and context
- Source model ID: google/gemini-2.5-flash-lite. Source model name: Gemini 2.5 Flash-Lite. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-09-03. Latency in seconds: 13.781. Cost per task in USD: 0.000929. Source ID: vals-ai. Evidence capture ID: vals-sage-2026-09-04-81cb7ed97d9a. Source payload hash: 81cb7ed97d9aac52ebad6b8f42e41fe7277575eca512c3a2ac626de8f96970bd. Parser version: vals-astro-v2. Imported at: 2026-09-04
SAGE
Partial Differential Equations
Higher is better4 modelsGemini 2.5 Flash-Lite: Rank 4 of 4Data date: August 11, 2026
Scale: 0% - 100%
Methodology and context
- Comparison cohort
- vals-sage:1:PDEs
- Metric
- accuracy
- Scale
- 0-100
- Participants
- 4
- Methodology and context
- Source model ID: google/gemini-2.5-flash-lite. Source model name: Gemini 2.5 Flash-Lite. Provider reported by source: Google. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-08-09. Temperature: 1. Maximum output tokens: 30000. Latency in seconds: 12.776. Standard error: 5.078. Cost per task in USD: 0.001121. Source ID: vals-ai. Evidence capture ID: vals-sage-2026-08-11-f1f79f6d8af3. Source payload hash: f1f79f6d8af3af8a952baa6793df3cdbd11ccfc53c0b95683b89817df366a496. Parser version: vals-astro-v2. Imported at: 2026-08-11
Measurements without matching peer values
These measurements have no matching peer values under the same test conditions. Their original values and sources remain available here.
GPQA (Show measurement, test conditions, and source)
- Source value
- 66.7
- Score
- 66.7
- Metric
- percent
- Unit
- %
- Category
- vendor-evaluation
- Direction
- Higher is better
- Comparison cohort
- research:gemini-2.5-flash-lite:0
- Source type
- vendor-reported
- Evaluator
- Google DeepMind
- Status
- active
- Retrieved at
- 2026-09-08
- Methodology
- Vendor-reported result. Thinking configuration
AIME (Show measurement, test conditions, and source)
- Source value
- 63.1
- Score
- 63.1
- Metric
- percent
- Unit
- %
- Category
- vendor-evaluation
- Direction
- Higher is better
- Comparison cohort
- research:gemini-2.5-flash-lite:1
- Source type
- vendor-reported
- Evaluator
- Google DeepMind
- Status
- active
- Retrieved at
- 2026-09-08
- Methodology
- Vendor-reported result. Thinking configuration
LiveCodeBench (Show measurement, test conditions, and source)
- Source value
- 34.3
- Score
- 34.3
- Metric
- percent
- Unit
- %
- Category
- vendor-evaluation
- Direction
- Higher is better
- Comparison cohort
- research:gemini-2.5-flash-lite:2
- Source type
- vendor-reported
- Evaluator
- Google DeepMind
- Status
- active
- Retrieved at
- 2026-09-08
- Methodology
- Vendor-reported result. Thinking configuration
SWE-bench Verified (single) (Show measurement, test conditions, and source)
- Source value
- 27.6
- Score
- 27.6
- Metric
- percent
- Unit
- %
- Category
- vendor-evaluation
- Direction
- Higher is better
- Comparison cohort
- research:gemini-2.5-flash-lite:3
- Source type
- vendor-reported
- Evaluator
- Google DeepMind
- Status
- active
- Retrieved at
- 2026-09-08
- Methodology
- Vendor-reported result. Thinking configuration; single-agent
SWE-bench Verified (multi) (Show measurement, test conditions, and source)
- Source value
- 44.9
- Score
- 44.9
- Metric
- percent
- Unit
- %
- Category
- vendor-evaluation
- Direction
- Higher is better
- Comparison cohort
- research:gemini-2.5-flash-lite:4
- Source type
- vendor-reported
- Evaluator
- Google DeepMind
- Status
- active
- Retrieved at
- 2026-09-08
- Methodology
- Vendor-reported result. Thinking configuration; multi-agent
Recorded measurement details
Every observation retains its source value and published test conditions.
MedCode: Overall (Show measurement, test conditions, and source)
- Source value
- 27.115
- Score
- 27.115
- Metric
- accuracy
- Unit
- %
- Benchmark version
- 1
- Category
- health
- Task
- overall
- Task label
- Overall
- Direction
- Higher is better
- Comparison cohort
- vals-medcode:1:overall
- Source type
- independent-evaluator
- Evaluator
- Vals AI
- Status
- active
- Retrieved at
- 2026-09-04
- Methodology
- Source model ID: google/gemini-2.5-flash-lite. Source model name: Gemini 2.5 Flash-Lite. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-09-03. Latency in seconds: 5.746. Cost per task in USD: 0.001342. Source ID: vals-ai. Evidence capture ID: vals-medcode-2026-09-04-c44942e3604f. Source payload hash: c44942e3604fa8eca13f660a1551cfa5ea9bbf9c67af141f41601402afceb569. Parser version: vals-astro-v2. Imported at: 2026-09-04
MedScribe: Overall (Show measurement, test conditions, and source)
- Source value
- 72.832
- Score
- 72.832
- Metric
- accuracy
- Unit
- %
- Benchmark version
- 1
- Category
- health
- Task
- overall
- Task label
- Overall
- Direction
- Higher is better
- Comparison cohort
- vals-medscribe:1:overall
- Source type
- independent-evaluator
- Evaluator
- Vals AI
- Status
- active
- Retrieved at
- 2026-09-04
- Methodology
- Source model ID: google/gemini-2.5-flash-lite. Source model name: Gemini 2.5 Flash-Lite. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-09-03. Latency in seconds: 4.847. Cost per task in USD: 0.001211. Source ID: vals-ai. Evidence capture ID: vals-medscribe-2026-09-04-c86df6ced023. Source payload hash: c86df6ced023af4a251d97cf5f91df5f06151cd899b2529a2256d12e0656995a. Parser version: vals-astro-v2. Imported at: 2026-09-04
SAGE: Automata (Show measurement, test conditions, and source)
- Source value
- 33.334
- Score
- 33.334
- Metric
- accuracy
- Unit
- %
- Benchmark version
- 1
- Category
- education
- Task
- automata
- Task label
- Automata
- Direction
- Higher is better
- Comparison cohort
- vals-sage:1:automata
- Source type
- independent-evaluator
- Evaluator
- Vals AI
- Status
- active
- Retrieved at
- 2026-08-11
- Methodology
- Source model ID: google/gemini-2.5-flash-lite. Source model name: Gemini 2.5 Flash-Lite. Provider reported by source: Google. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-08-09. Temperature: 1. Maximum output tokens: 30000. Latency in seconds: 10.448. Standard error: 6.023. Cost per task in USD: 0.000876. Source ID: vals-ai. Evidence capture ID: vals-sage-2026-08-11-f1f79f6d8af3. Source payload hash: f1f79f6d8af3af8a952baa6793df3cdbd11ccfc53c0b95683b89817df366a496. Parser version: vals-astro-v2. Imported at: 2026-08-11
- Comparison methodology
- Temperature: 1. Maximum output tokens: 30000
SAGE: Calculus (Show measurement, test conditions, and source)
- Source value
- 13.889
- Score
- 13.889
- Metric
- accuracy
- Unit
- %
- Benchmark version
- 1
- Category
- education
- Task
- calculus
- Task label
- Calculus
- Direction
- Higher is better
- Comparison cohort
- vals-sage:1:calculus
- Source type
- independent-evaluator
- Evaluator
- Vals AI
- Status
- active
- Retrieved at
- 2026-08-11
- Methodology
- Source model ID: google/gemini-2.5-flash-lite. Source model name: Gemini 2.5 Flash-Lite. Provider reported by source: Google. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-08-09. Temperature: 1. Maximum output tokens: 30000. Latency in seconds: 13.337. Standard error: 4.298. Cost per task in USD: 0.001699. Source ID: vals-ai. Evidence capture ID: vals-sage-2026-08-11-f1f79f6d8af3. Source payload hash: f1f79f6d8af3af8a952baa6793df3cdbd11ccfc53c0b95683b89817df366a496. Parser version: vals-astro-v2. Imported at: 2026-08-11
- Comparison methodology
- Temperature: 1. Maximum output tokens: 30000
SAGE: Linear Algebra (Show measurement, test conditions, and source)
- Source value
- 28.629
- Score
- 28.629
- Metric
- accuracy
- Unit
- %
- Benchmark version
- 1
- Category
- education
- Task
- linear_algebra
- Task label
- Linear Algebra
- Direction
- Higher is better
- Comparison cohort
- vals-sage:1:linear_algebra
- Source type
- independent-evaluator
- Evaluator
- Vals AI
- Status
- active
- Retrieved at
- 2026-08-11
- Methodology
- Source model ID: google/gemini-2.5-flash-lite. Source model name: Gemini 2.5 Flash-Lite. Provider reported by source: Google. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-08-09. Temperature: 1. Maximum output tokens: 30000. Latency in seconds: 18.12. Standard error: 5.077. Cost per task in USD: 0.000791. Source ID: vals-ai. Evidence capture ID: vals-sage-2026-08-11-f1f79f6d8af3. Source payload hash: f1f79f6d8af3af8a952baa6793df3cdbd11ccfc53c0b95683b89817df366a496. Parser version: vals-astro-v2. Imported at: 2026-08-11
- Comparison methodology
- Temperature: 1. Maximum output tokens: 30000
SAGE: Overall (Show measurement, test conditions, and source)
- Source value
- 27.533
- Score
- 27.533
- Metric
- accuracy
- Unit
- %
- Benchmark version
- 1
- Category
- education
- Task
- overall
- Task label
- Overall
- Direction
- Higher is better
- Comparison cohort
- vals-sage:1:overall
- Source type
- independent-evaluator
- Evaluator
- Vals AI
- Status
- active
- Retrieved at
- 2026-09-04
- Methodology
- Source model ID: google/gemini-2.5-flash-lite. Source model name: Gemini 2.5 Flash-Lite. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-09-03. Latency in seconds: 13.781. Cost per task in USD: 0.000929. Source ID: vals-ai. Evidence capture ID: vals-sage-2026-09-04-81cb7ed97d9a. Source payload hash: 81cb7ed97d9aac52ebad6b8f42e41fe7277575eca512c3a2ac626de8f96970bd. Parser version: vals-astro-v2. Imported at: 2026-09-04
SAGE: Partial Differential Equations (Show measurement, test conditions, and source)
- Source value
- 20.635
- Score
- 20.635
- Metric
- accuracy
- Unit
- %
- Benchmark version
- 1
- Category
- education
- Task
- PDEs
- Task label
- Partial Differential Equations
- Direction
- Higher is better
- Comparison cohort
- vals-sage:1:PDEs
- Source type
- independent-evaluator
- Evaluator
- Vals AI
- Status
- active
- Retrieved at
- 2026-08-11
- Methodology
- Source model ID: google/gemini-2.5-flash-lite. Source model name: Gemini 2.5 Flash-Lite. Provider reported by source: Google. Evaluator: Vals AI. Dataset type: private. Leaderboard date: 2026-08-09. Temperature: 1. Maximum output tokens: 30000. Latency in seconds: 12.776. Standard error: 5.078. Cost per task in USD: 0.001121. Source ID: vals-ai. Evidence capture ID: vals-sage-2026-08-11-f1f79f6d8af3. Source payload hash: f1f79f6d8af3af8a952baa6793df3cdbd11ccfc53c0b95683b89817df366a496. Parser version: vals-astro-v2. Imported at: 2026-08-11
- Comparison methodology
- Temperature: 1. Maximum output tokens: 30000
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.
Prompt and test conditions
Generate an SVG of a pelican riding a bicycle
Token limit including reasoning: 8,192 tokens
Task origin (Simon Willison)Profile
Specifications and access
Published information about this model. Existing estimates are explicitly labeled.
Additional source observations
Dated documentation and model-card observations. Provider limits, native context and extended context can differ. Configuration notes retain the source wording.
- API model ID
- gemini-2.5-flash-liteSource
- Source status
- stableSource
- Maximum output
- 65,536 tokensSource
- Input
- Text, Image, Video, Audio, pdfSource
- Output
- TextSource
- Reasoning mode
- low, medium, highSource
- Tool calling
- YesSource
- Structured output
- YesSource
- Release
- 2025-07-22Source
- Knowledge cutoff
- 2025-01Source
- Capabilities
- function calling, structured outputs, search grounding, Google Maps grounding, URL context, code execution, file searchSource
- General availability
- 2025-07-22 (General availability (GA).)Source
Pricing
Published prices
Prices apply to the stated unit. Resolution, output length, and provider can change the cost.
Cost example
100 API requests
$0.03
100 requests with 1,000 input and 500 output tokens each calculate to $0.03. Input accounts for $0.01; output accounts for $0.02.
- Input price
- $0.1 / 1M tokensBase tier for each request
- Output price
- $0.4 / 1M tokensBase tier for each request
The calculation uses documented token prices and no cache discount. It excludes extra tools, tax, reasoning tokens, and further hidden output tokens.
Open sourceHead-to-head comparisons
Compare this model
Each matchup compares this model with exactly one other model from the same category.
There are no published direct comparisons for this model yet.
Evidence
Sources and data date
Every statement links to its underlying documentation or leaderboard.
- Speed
Google, Non-reasoning. 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.
- Price
Base API prices without caching or batch discounts. Higher context tiers and other rates are listed under Costs.
- Input
Documented modalities. Retrieved September 8, 2026.
- Output
Documented modalities. Retrieved September 8, 2026.
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
- Knowledge cutoff dataSource
- API pricingSource
- Vals AI (retrieved September 4, 2026)Source
- Vals AI (retrieved September 4, 2026)Source
- Vals AI (retrieved August 11, 2026; 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