Google, proprietary

# Gemini 2.5 Flash-Lite

> Gemini 2.5 Flash-Lite by Google, released June 2025. Ranked #211 of 354 with a Noometry Index of 37.0. API: $0.10 in / $0.40 out per M tokens. 1.05M context. Scores, sources and comparisons.
- Canonical page: https://noometry.com/models/gemini-2-5-flash-lite
- Last updated: 2026-10-10
- Title: Gemini 2.5 Flash-Lite Benchmarks, Price & Rank (October 2026)

Gemini 2.5 Flash-Lite by Google ranks 211th of 354 ranked models on the Noometry Index as of October 2026, with a score of 37.0. Its strongest category is agentic & tool use, where it ranks 96th. API pricing starts at $0.10 per million input tokens and $0.40 per million output tokens, with a 1.05M-token context window.

Last verified October 10, 2026

## Specifications

- **Noometry rank:** #211 of 354
- **Index score:** 37.0
- **Evidence:** Confirmed 33 results
- **Provider:** [![](/logos/google.svg) Google](https://noometry.com/providers/google)
- **Released:** June 17, 2025
- **Weights:** Proprietary
- **Reasoning:** Yes
- **Context window:** 1.05M
- **Max output:** 66K
- **Input price:** $0.10 / M
- **Output price:** $0.40 / M
- **Blended price:** $0.18 / M
- **Output speed:** 172 tokens/s [Kagi](https://help.kagi.com/kagi/ai/llm-benchmark.html)
- **Value:** #40 of 219
- **Knowledge cutoff:** January 2025
- **Input:** text, image, audio, video, pdf

## Category scores

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

Gemini 2.5 Flash-Lite category scores

1.  Coding 38.5
2.  Agentic & Tool Use 28.0
3.  Reasoning 22.2
4.  Math 38.0
5.  Knowledge 32.5
6.  Multimodal 29.1
7.  Multilingual 49.3
8.  Instruction Following 70.0
9.  Long Context 33.3
10.  Writing & Preference 56.8
11.  020406080

Gemini 2.5 Flash-Lite category ranks
| Category | Score | Rank | Results |
| --- | --- | --- | --- |
| [Coding](https://noometry.com/best/coding) | 38.5 | #173 | 2 |
| [Agentic & Tool Use](https://noometry.com/best/agentic) | 28.0 | #96 | 1 |
| [Reasoning](https://noometry.com/best/reasoning) | 22.2 | #205 | 4 |
| [Math](https://noometry.com/best/math) | 38.0 | #144 | 2 |
| [Knowledge](https://noometry.com/best/knowledge) | 32.5 | #210 | 4 |
| [Multimodal](https://noometry.com/best/multimodal) | 29.1 | #114 | 2 |
| [Multilingual](https://noometry.com/best/multilingual) | 49.3 | #134 | 1 |
| [Instruction Following](https://noometry.com/best/instruction-following) | 70.0 | #168 | 2 |
| [Long Context](https://noometry.com/best/long-context) | 33.3 | #262 | 2 |
| [Writing & Preference](https://noometry.com/best/writing) | 56.8 | #135 | 4 |

## Strengths and weaknesses

Categories where Gemini 2.5 Flash-Lite places highest and lowest among the models ranked in each, with its score against that category's median.

### Strongest categories

Gemini 2.5 Flash-Lite: strongest categories
| Category | Score | vs median | Rank |
| --- | --- | --- | --- |
| [Writing & Preference](https://noometry.com/best/writing) | 56.8 | +3.1 | #135 of 312, top 44% |
| [Math](https://noometry.com/best/math) | 38.0 | +1.4 | #144 of 327, top 45% |
| [Multilingual](https://noometry.com/best/multilingual) | 49.3 | +1.9 | #134 of 297, top 46% |

### Weakest categories

Gemini 2.5 Flash-Lite: weakest categories
| Category | Score | vs median | Rank |
| --- | --- | --- | --- |
| [Multimodal](https://noometry.com/best/multimodal) | 29.1 | −9.4 | #114 of 128, top 90% |
| [Long Context](https://noometry.com/best/long-context) | 33.3 | −7.6 | #262 of 296, top 89% |
| [Knowledge](https://noometry.com/best/knowledge) | 32.5 | −4.8 | #210 of 314, top 67% |

## Closest competitors

The models ranked just above and below Gemini 2.5 Flash-Lite. When scores are this close, price and speed are often the better way to choose.

Models ranked closest to Gemini 2.5 Flash-Lite
| Model | Rank | Score | Blended $/M | Speed |  |
| --- | --- | --- | --- | --- | --- |
| [Step 3.7 Flash](https://noometry.com/models/step-3-7-flash) | #207 | 37.3 | $0.42 | — | [Compare](https://noometry.com/compare/gemini-2-5-flash-lite-vs-step-3-7-flash) |
| [GPT-4.5](https://noometry.com/models/gpt-4-5) | #208 | 37.2 | — | — | [Compare](https://noometry.com/compare/gemini-2-5-flash-lite-vs-gpt-4-5) |
| [Yi-Lightning](https://noometry.com/models/yi-lightning) | #209 | 37.1 | — | — | [Compare](https://noometry.com/compare/gemini-2-5-flash-lite-vs-yi-lightning) |
| [Qwen Plus](https://noometry.com/models/qwen-plus) | #210 | 37.1 | $0.60 | 37 | [Compare](https://noometry.com/compare/gemini-2-5-flash-lite-vs-qwen-plus) |
| [o3-mini](https://noometry.com/models/o3-mini) | #212 | 36.7 | $1.93 | — | [Compare](https://noometry.com/compare/gemini-2-5-flash-lite-vs-o3-mini) |
| [Llama 3.1 Nemotron Ultra 253b v1](https://noometry.com/models/llama-3-1-nemotron-ultra-253b-v1) | #213 | 36.7 | — | — | [Compare](https://noometry.com/compare/gemini-2-5-flash-lite-vs-llama-3-1-nemotron-ultra-253b-v1) |
| [Granite 4.0 H Small](https://noometry.com/models/ibm-granite-h-small) | #214 | 36.5 | — | — | [Compare](https://noometry.com/compare/gemini-2-5-flash-lite-vs-ibm-granite-h-small) |
| [Command A](https://noometry.com/models/command-a) | #215 | 36.5 | $4.38 | 28 | [Compare](https://noometry.com/compare/command-a-vs-gemini-2-5-flash-lite) |

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

Gemini 2.5 Flash-Lite Coding benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [WeirdML](https://noometry.com/benchmarks/weirdml) | 35.2% |  |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [WeirdML](https://noometry.com/benchmarks/weirdml) | 35.2% | #91 of 119, top 77% | 16K | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LMArena Coding](https://noometry.com/benchmarks/arena-coding) | 1372 |  | no-thinking | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Coding](https://noometry.com/benchmarks/arena-coding) | 1373 | #155 of 294, top 53% | thinking | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [ALE-Bench](https://noometry.com/benchmarks/ale-bench) | 325.9 | #97 of 105, top 93% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |

### Agentic & Tool Use

Gemini 2.5 Flash-Lite Agentic & Tool Use benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [Berkeley Function Calling Leaderboard](https://noometry.com/benchmarks/bfcl) | 36.9% | #28 of 49, top 58% | fc | [Berkeley Function Calling Leaderboard](https://gorilla.cs.berkeley.edu/leaderboard.html) |  |

### Reasoning

Gemini 2.5 Flash-Lite Reasoning benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [Kagi LLM Benchmark](https://noometry.com/benchmarks/kagi-reasoning) | 40.5% | #76 of 99, top 77% |  | [Kagi LLM Benchmark](https://help.kagi.com/kagi/ai/llm-benchmark.html) |  |
| [LMArena Hard Prompts](https://noometry.com/benchmarks/arena-hard-prompts) | 1377 | #140 of 297, top 48% | no-thinking | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Hard Prompts](https://noometry.com/benchmarks/arena-hard-prompts) | 1374 |  | thinking | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [DTBench](https://noometry.com/benchmarks/dtbench) | 62.8% | #107 of 151, top 71% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LMCA](https://noometry.com/benchmarks/lmca) | 18.1% | #96 of 125, top 77% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [Epoch Capabilities Index](https://noometry.com/benchmarks/epoch-capabilities-index) | 133.94 | #129 of 213, top 61% |  | [Epoch AI](https://epoch.ai/eci) | 2025-06-17 |

### Math

Gemini 2.5 Flash-Lite Math benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [Omni-MATH](https://noometry.com/benchmarks/omni-math) | 48% | #17 of 57, top 30% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| [LMArena Math](https://noometry.com/benchmarks/arena-math) | 1373 | #147 of 285, top 52% | no-thinking | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Math](https://noometry.com/benchmarks/arena-math) | 1363 |  | thinking | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Knowledge

Gemini 2.5 Flash-Lite Knowledge benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [MMLU-Pro](https://noometry.com/benchmarks/mmlu-pro) | 53.7% | #50 of 58, top 87% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| [Vectara Hallucination Rate](https://noometry.com/benchmarks/vectara-hallucination) (lower is better) | 3.3% | #2 of 96, top 3% |  | [Vectara Hallucination Leaderboard](https://github.com/vectara/hallucination-leaderboard) |  |
| [GPQA (HELM)](https://noometry.com/benchmarks/helm-gpqa) | 30.9% | #52 of 57, top 92% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| [LMArena Expert](https://noometry.com/benchmarks/arena-expert) | 1373 | #139 of 273, top 51% | no-thinking | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Expert](https://noometry.com/benchmarks/arena-expert) | 1366 |  | thinking | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Multimodal

Gemini 2.5 Flash-Lite Multimodal benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Vision](https://noometry.com/benchmarks/arena-vision) | 1198 | #79 of 122, top 65% | no-thinking | [LMArena](https://lmarena.ai/leaderboard/vision) | 2026-10-09 |
| [LMArena Vision](https://noometry.com/benchmarks/arena-vision) | 1187 |  | thinking | [LMArena](https://lmarena.ai/leaderboard/vision) | 2026-10-09 |
| [VPCT](https://noometry.com/benchmarks/vpct) | 30% | #24 of 24, top 100% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |

### Multilingual

Gemini 2.5 Flash-Lite Multilingual benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Non-English](https://noometry.com/benchmarks/arena-non-english) | 1369 | #134 of 297, top 46% | no-thinking | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Non-English](https://noometry.com/benchmarks/arena-non-english) | 1360 |  | thinking | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Chinese](https://noometry.com/benchmarks/arena-chinese) | 1404 | #137 of 285, top 49% | no-thinking | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Chinese](https://noometry.com/benchmarks/arena-chinese) | 1400 |  | thinking | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena French](https://noometry.com/benchmarks/arena-french) | 1388 | #127 of 223, top 57% | no-thinking | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena French](https://noometry.com/benchmarks/arena-french) | 1387 |  | thinking | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena German](https://noometry.com/benchmarks/arena-german) | 1389 | #105 of 231, top 46% | no-thinking | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena German](https://noometry.com/benchmarks/arena-german) | 1373 |  | thinking | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Japanese](https://noometry.com/benchmarks/arena-japanese) | 1359 | #92 of 211, top 44% | no-thinking | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Japanese](https://noometry.com/benchmarks/arena-japanese) | 1350 |  | thinking | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Korean](https://noometry.com/benchmarks/arena-korean) | 1350 |  | no-thinking | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Korean](https://noometry.com/benchmarks/arena-korean) | 1360 | #95 of 213, top 45% | thinking | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Russian](https://noometry.com/benchmarks/arena-russian) | 1373 | #132 of 283, top 47% | no-thinking | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Russian](https://noometry.com/benchmarks/arena-russian) | 1364 |  | thinking | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Spanish](https://noometry.com/benchmarks/arena-spanish) | 1396 | #115 of 226, top 51% | no-thinking | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Spanish](https://noometry.com/benchmarks/arena-spanish) | 1365 |  | thinking | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Instruction Following

Gemini 2.5 Flash-Lite Instruction Following benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [IFEval](https://noometry.com/benchmarks/ifeval) | 81% | #39 of 57, top 69% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| [LMArena Instruction Following](https://noometry.com/benchmarks/arena-instruction-following) | 1355 |  | no-thinking | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Instruction Following](https://noometry.com/benchmarks/arena-instruction-following) | 1367 | #134 of 298, top 45% | thinking | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Long Context

Gemini 2.5 Flash-Lite Long Context benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [Fiction.LiveBench](https://noometry.com/benchmarks/fiction-livebench) | 47.2% | #36 of 47, top 77% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LMArena Longer Query](https://noometry.com/benchmarks/arena-longer-query) | 1373 |  | no-thinking | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Longer Query](https://noometry.com/benchmarks/arena-longer-query) | 1373 | #136 of 291, top 47% | thinking | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Writing & Preference

Gemini 2.5 Flash-Lite Writing & Preference benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Text](https://noometry.com/benchmarks/arena-text) | 1379 | #136 of 297, top 46% | no-thinking | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Text](https://noometry.com/benchmarks/arena-text) | 1369 |  | thinking | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Creative Writing](https://noometry.com/benchmarks/arena-creative-writing) | 1358 |  | no-thinking | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Creative Writing](https://noometry.com/benchmarks/arena-creative-writing) | 1367 | #113 of 295, top 39% | thinking | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [WildBench](https://noometry.com/benchmarks/wildbench) | 81.8% | #21 of 57, top 37% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| [LMArena Multi-Turn](https://noometry.com/benchmarks/arena-multi-turn) | 1366 | #142 of 295, top 49% | no-thinking | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Multi-Turn](https://noometry.com/benchmarks/arena-multi-turn) | 1360 |  | thinking | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

## API pricing by provider

Gemini 2.5 Flash-Lite API prices
| Route | Input $/M | Output $/M | Cached input $/M | Checked |
| --- | --- | --- | --- | --- |
| [google](https://ai.google.dev/gemini-api/docs/models) | $0.10 | $0.40 | $0.01 | 2026-10-10 |
| [openrouter](https://openrouter.ai/google/gemini-2.5-flash-lite) | $0.10 | $0.40 | $0.01 | 2026-10-10 |
| [vertex](https://cloud.google.com/vertex-ai/generative-ai/docs/models) | $0.10 | $0.40 | $0.01 | 2026-10-10 |

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

## Compare Gemini 2.5 Flash-Lite

-   [Gemini 2.5 Flash-Lite vs Gemini 2.0 Flash-Lite](https://noometry.com/compare/gemini-2-0-flash-lite-vs-gemini-2-5-flash-lite)
-   [Gemini 2.5 Flash-Lite vs Qwen Plus](https://noometry.com/compare/gemini-2-5-flash-lite-vs-qwen-plus)
-   [Gemini 2.5 Flash-Lite vs o3-mini](https://noometry.com/compare/gemini-2-5-flash-lite-vs-o3-mini)
-   [Gemini 2.5 Flash-Lite vs Yi-Lightning](https://noometry.com/compare/gemini-2-5-flash-lite-vs-yi-lightning)
-   [Gemini 2.5 Flash-Lite vs Llama 3.1 Nemotron Ultra 253b v1](https://noometry.com/compare/gemini-2-5-flash-lite-vs-llama-3-1-nemotron-ultra-253b-v1)
-   [Gemini 2.5 Flash-Lite vs GPT-4.5](https://noometry.com/compare/gemini-2-5-flash-lite-vs-gpt-4-5)
-   [Gemini 2.5 Flash-Lite vs Granite 4.0 H Small](https://noometry.com/compare/gemini-2-5-flash-lite-vs-ibm-granite-h-small)
-   [Gemini 2.5 Flash-Lite vs GPT-6 Astra](https://noometry.com/compare/gemini-2-5-flash-lite-vs-gpt-6-astra)
-   [Gemini 2.5 Flash-Lite vs Claude Fable 5.1](https://noometry.com/compare/claude-fable-5-1-vs-gemini-2-5-flash-lite)
-   [Gemini 2.5 Flash-Lite vs Kimi K3](https://noometry.com/compare/gemini-2-5-flash-lite-vs-kimi-k3)
-   [Gemini 2.5 Flash-Lite vs Grok 4.6](https://noometry.com/compare/gemini-2-5-flash-lite-vs-grok-4-6)
-   [Gemini 2.5 Flash-Lite vs Qwen3.8 Max](https://noometry.com/compare/gemini-2-5-flash-lite-vs-qwen3-8-max)
-   [Gemini 2.5 Flash-Lite vs GLM-5.3](https://noometry.com/compare/gemini-2-5-flash-lite-vs-glm-5-3)
-   [Gemini 2.5 Flash-Lite vs Muse Spark 1.3](https://noometry.com/compare/gemini-2-5-flash-lite-vs-muse-spark-1-3)

## Other Google models

-   [Gemini 3.8 Flash](https://noometry.com/models/gemini-3-8-flash)61.8
-   [Gemini 3.7 Flash](https://noometry.com/models/gemini-3-7-flash)59.8
-   [Gemini 3.1 Pro Preview](https://noometry.com/models/gemini-3-1-pro-preview)56.7
-   [Gemini 4 Argon](https://noometry.com/models/gemini-4-argon)56.5
-   [Gemini 3 Pro](https://noometry.com/models/gemini-3-pro)54.8
-   [Gemini 3.5 Flash](https://noometry.com/models/gemini-3-5-flash)54.2
-   [Gemini 3.6 Flash](https://noometry.com/models/gemini-3-6-flash)54.1
-   [Gemini 3 Flash Preview](https://noometry.com/models/gemini-3-flash-preview)52.3

## Frequently asked questions

### How good is Gemini 2.5 Flash-Lite?

Gemini 2.5 Flash-Lite by Google ranks 211th of 354 ranked models on the Noometry Index as of October 2026, with a score of 37.0. Its strongest category is agentic & tool use, where it ranks 96th. API pricing starts at $0.10 per million input tokens and $0.40 per million output tokens, with a 1.05M-token context window.

### How much does Gemini 2.5 Flash-Lite cost?

Gemini 2.5 Flash-Lite costs $0.10 per million input tokens and $0.40 per million output tokens on Google's own API, with cached input at $0.01.

### What is Gemini 2.5 Flash-Lite's context window?

Gemini 2.5 Flash-Lite accepts up to 1.05M tokens of input and can write up to 66K tokens in one response.

### Is Gemini 2.5 Flash-Lite open source?

No. Gemini 2.5 Flash-Lite is proprietary and available only through Google's API and partner platforms.

### How fast is Gemini 2.5 Flash-Lite?

Gemini 2.5 Flash-Lite generated about 172 output tokens per second in the Kagi LLM Benchmark's timed runs. Speed varies by provider, load and reasoning effort.

### What are Gemini 2.5 Flash-Lite's strengths and weaknesses?

Relative to other ranked models, Gemini 2.5 Flash-Lite places best in writing & preference, math, multilingual and lowest in multimodal, long context, knowledge.

### What is Gemini 2.5 Flash-Lite best at?

Its best category is agentic & tool use, where it ranks 96th on Noometry.

### Cite this page

Noometry. (2026). Gemini 2.5 Flash-Lite benchmarks and pricing. Retrieved October 10, 2026, from https://noometry.com/models/gemini-2-5-flash-lite

Quote Noometry with a link back to this page. It is also available in [Markdown](https://noometry.com/md/models/gemini-2-5-flash-lite.md).