Google, proprietary

# Gemini 3.5 Flash

> Gemini 3.5 Flash by Google, released May 2026. Ranked #32 of 354 with a Noometry Index of 54.2. API: $1.50 in / $9 out per M tokens. 1.05M context. Scores, sources and comparisons.
- Canonical page: https://noometry.com/models/gemini-3-5-flash
- Last updated: 2026-10-10
- Title: Gemini 3.5 Flash Benchmarks, Price & Rank (October 2026)

Gemini 3.5 Flash by Google ranks 32nd of 354 ranked models on the Noometry Index as of October 2026, with a score of 54.2. Its strongest category is knowledge, where it ranks 11th. API pricing starts at $1.50 per million input tokens and $9 per million output tokens, with a 1.05M-token context window.

Last verified October 10, 2026

## Specifications

- **Noometry rank:** #32 of 354
- **Index score:** 54.2
- **Evidence:** Confirmed 54 results
- **Provider:** [![](/logos/google.svg) Google](https://noometry.com/providers/google)
- **Released:** May 19, 2026
- **Weights:** Proprietary
- **Reasoning:** Yes
- **Context window:** 1.05M
- **Max output:** 66K
- **Input price:** $1.50 / M
- **Output price:** $9 / M
- **Blended price:** $3.38 / M
- **Output speed:** Not measured
- **Value:** #161 of 219
- **Knowledge cutoff:** January 2025
- **Input:** text, image, video, audio, pdf

## Category scores

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

Gemini 3.5 Flash category scores

1.  Coding 49.4
2.  Agentic & Tool Use 24.7
3.  Reasoning 62.8
4.  Math 60.7
5.  Knowledge 66.3
6.  Multimodal 45.7
7.  Multilingual 57.0
8.  Instruction Following 77.0
9.  Long Context 45.4
10.  Writing & Preference 65.5
11.  020406080

Gemini 3.5 Flash category ranks
| Category | Score | Rank | Results |
| --- | --- | --- | --- |
| [Coding](https://noometry.com/best/coding) | 49.4 | #49 | 6 |
| [Agentic & Tool Use](https://noometry.com/best/agentic) | 24.7 | #114 | 3 |
| [Reasoning](https://noometry.com/best/reasoning) | 62.8 | #18 | 13 |
| [Math](https://noometry.com/best/math) | 60.7 | #36 | 6 |
| [Knowledge](https://noometry.com/best/knowledge) | 66.3 | #11 | 3 |
| [Multimodal](https://noometry.com/best/multimodal) | 45.7 | #15 | 2 |
| [Multilingual](https://noometry.com/best/multilingual) | 57.0 | #13 | 1 |
| [Instruction Following](https://noometry.com/best/instruction-following) | 77.0 | #30 | 1 |
| [Long Context](https://noometry.com/best/long-context) | 45.4 | #38 | 1 |
| [Writing & Preference](https://noometry.com/best/writing) | 65.5 | #47 | 4 |

## Strengths and weaknesses

Categories where Gemini 3.5 Flash places highest and lowest among the models ranked in each, with its score against that category's median.

### Strongest categories

Gemini 3.5 Flash: strongest categories
| Category | Score | vs median | Rank |
| --- | --- | --- | --- |
| [Knowledge](https://noometry.com/best/knowledge) | 66.3 | +29.0 | #11 of 314, top 4% |
| [Multilingual](https://noometry.com/best/multilingual) | 57.0 | +9.6 | #13 of 297, top 5% |
| [Reasoning](https://noometry.com/best/reasoning) | 62.8 | +39.2 | #18 of 350, top 6% |

### Weakest categories

Gemini 3.5 Flash: weakest categories
| Category | Score | vs median | Rank |
| --- | --- | --- | --- |
| [Agentic & Tool Use](https://noometry.com/best/agentic) | 24.7 | −5.6 | #114 of 154, top 75% |
| [Writing & Preference](https://noometry.com/best/writing) | 65.5 | +11.7 | #47 of 312, top 16% |
| [Coding](https://noometry.com/best/coding) | 49.4 | +10.7 | #49 of 340, top 15% |

## Closest competitors

The models ranked just above and below Gemini 3.5 Flash. When scores are this close, price and speed are often the better way to choose.

Models ranked closest to Gemini 3.5 Flash
| Model | Rank | Score | Blended $/M | Speed |  |
| --- | --- | --- | --- | --- | --- |
| [Gemini 3 Pro](https://noometry.com/models/gemini-3-pro) | #28 | 54.8 | — | 1 | [Compare](https://noometry.com/compare/gemini-3-5-flash-vs-gemini-3-pro) |
| [Claude Sonnet 5](https://noometry.com/models/claude-sonnet-5) | #29 | 54.6 | $4 | — | [Compare](https://noometry.com/compare/claude-sonnet-5-vs-gemini-3-5-flash) |
| [GPT-5.6 Luna](https://noometry.com/models/gpt-5-6-luna) | #30 | 54.6 | $0.45 | 12 | [Compare](https://noometry.com/compare/gemini-3-5-flash-vs-gpt-5-6-luna) |
| [DeepSeek V4 Pro](https://noometry.com/models/deepseek-v4-pro) | #31 | 54.3 | $0.99 | 16 | [Compare](https://noometry.com/compare/deepseek-v4-pro-vs-gemini-3-5-flash) |
| [Gemini 3.6 Flash](https://noometry.com/models/gemini-3-6-flash) | #33 | 54.1 | $1.50 | — | [Compare](https://noometry.com/compare/gemini-3-5-flash-vs-gemini-3-6-flash) |
| [GPT-5.2](https://noometry.com/models/gpt-5-2) | #34 | 54.1 | $4.81 | 15 | [Compare](https://noometry.com/compare/gemini-3-5-flash-vs-gpt-5-2) |
| [DeepSeek V4 Flash](https://noometry.com/models/deepseek-v4-flash) | #35 | 53.6 | $0.26 | 6 | [Compare](https://noometry.com/compare/deepseek-v4-flash-vs-gemini-3-5-flash) |
| [GPT-6 Luna](https://noometry.com/models/gpt-6-luna) | #36 | 53.3 | $0.20 | — | [Compare](https://noometry.com/compare/gemini-3-5-flash-vs-gpt-6-luna) |

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 3.5 Flash Coding benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [SWE-bench Verified](https://noometry.com/benchmarks/swe-bench-verified) | 79.3% | #3 of 32, top 10% | high | [Epoch AI](https://epoch.ai/benchmarks) | 2026-06-01 |
| [DeepSWE](https://noometry.com/benchmarks/deepswe) | 36.1% |  | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [DeepSWE](https://noometry.com/benchmarks/deepswe) | 37.4% | #26 of 29, top 90% | medium | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LMArena WebDev](https://noometry.com/benchmarks/arena-webdev) | 1499 | #48 of 113, top 43% | high | [LMArena](https://lmarena.ai/leaderboard/webdev) | 2026-10-08 |
| [SciCode](https://noometry.com/benchmarks/scicode) | 53.1% | #34 of 121, top 29% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [WeirdML](https://noometry.com/benchmarks/weirdml) | 62.6% | #26 of 119, top 22% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LMArena Coding](https://noometry.com/benchmarks/arena-coding) | 1492 | #28 of 294, top 10% | high | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [ALE-Bench](https://noometry.com/benchmarks/ale-bench) | 911.02 | #49 of 105, top 47% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |

### Agentic & Tool Use

Gemini 3.5 Flash Agentic & Tool Use benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [APEX-Agents](https://noometry.com/benchmarks/apex-agents) | 27.5% | #45 of 49, top 92% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [GBAEval](https://noometry.com/benchmarks/gbaeval) | 6.7% | #14 of 23, top 61% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [GDP.pdf](https://noometry.com/benchmarks/gdp-pdf) | 14% | #28 of 36, top 78% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [GDP.pdf](https://noometry.com/benchmarks/gdp-pdf) | 14% |  | medium | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [Vending-Bench 2](https://noometry.com/benchmarks/vending-bench-2) | 5,396 | #26 of 60, top 44% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |

### Reasoning

Gemini 3.5 Flash Reasoning benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [ARC-AGI-2](https://noometry.com/benchmarks/arc-agi-2) | 72.1% | #20 of 83, top 25% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [ARC-AGI-2](https://noometry.com/benchmarks/arc-agi-2) | 8.9% |  | minimal | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [SimpleBench](https://noometry.com/benchmarks/simplebench) | 76.7% | #5 of 77, top 7% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [NYT Connections (extended)](https://noometry.com/benchmarks/nyt-connections) | 92.6% | #12 of 91, top 14% |  | [Lech Mazur benchmarks](https://github.com/lechmazur/nyt-connections) |  |
| [ARC-AGI-1](https://noometry.com/benchmarks/arc-agi-1) | 92.5% | #22 of 83, top 27% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [ARC-AGI-1](https://noometry.com/benchmarks/arc-agi-1) | 48.8% |  | minimal | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [CritPt](https://noometry.com/benchmarks/critpt) | 13.1% | #41 of 134, top 31% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [Chess Puzzles](https://noometry.com/benchmarks/chess-puzzles) | 50% | #10 of 129, top 8% | high | [Epoch AI](https://epoch.ai/benchmarks) | 2026-05-28 |
| [Chess Puzzles](https://noometry.com/benchmarks/chess-puzzles) | 45% |  | low | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-06 |
| [Chess Puzzles](https://noometry.com/benchmarks/chess-puzzles) | 43% |  | minimal | [Epoch AI](https://epoch.ai/benchmarks) | 2026-07-15 |
| [EnigmaEval](https://noometry.com/benchmarks/enigmaeval) | 25.4% | #4 of 38, top 11% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [EBR-Bench](https://noometry.com/benchmarks/ebr-bench) | 4.8% | #22 of 24, top 92% | high | [Epoch AI](https://epoch.ai/benchmarks) | 2026-06-25 |
| [LMArena Hard Prompts](https://noometry.com/benchmarks/arena-hard-prompts) | 1488 | #18 of 297, top 7% | high | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [Mystery Game Puzzles](https://noometry.com/benchmarks/mystery-game-puzzles) | 32% | #24 of 74, top 33% | high | [Epoch AI](https://epoch.ai/benchmarks) | 2026-07-27 |
| [Mystery Game Puzzles](https://noometry.com/benchmarks/mystery-game-puzzles) | 28% |  | low | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-05 |
| [DTBench](https://noometry.com/benchmarks/dtbench) | 94.7% | #19 of 151, top 13% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LMCA](https://noometry.com/benchmarks/lmca) | 47.1% | #27 of 125, top 22% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [Surface Evolver Bench](https://noometry.com/benchmarks/surface-evolver-bench) | 58.1% | #11 of 25, top 44% | medium | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [Epoch Capabilities Index](https://noometry.com/benchmarks/epoch-capabilities-index) | 154.46 | #35 of 213, top 17% |  | [Epoch AI](https://epoch.ai/eci) | 2026-05-19 |
| [ForecastBench](https://noometry.com/benchmarks/forecastbench) | 59 | #44 of 72, top 62% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |

### Math

Gemini 3.5 Flash Math benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [FrontierMath (Tiers 1-3)](https://noometry.com/benchmarks/frontiermath) | 62.8% | #34 of 81, top 42% | high | [Epoch AI](https://epoch.ai/benchmarks) | 2026-06-10 |
| [FrontierMath Tier 4](https://noometry.com/benchmarks/frontiermath-tier-4) | 26.8% | #36 of 63, top 58% | high | [Epoch AI](https://epoch.ai/benchmarks) | 2026-06-10 |
| [MathArena Final-Answer Competitions](https://noometry.com/benchmarks/matharena) | 76.3% | #9 of 29, top 32% |  | [MathArena](https://matharena.ai/) |  |
| [OTIS Mock AIME 2024-2025](https://noometry.com/benchmarks/otis-mock-aime) | 95.6% | #32 of 173, top 19% | high | [Epoch AI](https://epoch.ai/benchmarks) | 2026-05-25 |
| [OTIS Mock AIME 2024-2025](https://noometry.com/benchmarks/otis-mock-aime) | 88.9% |  | low | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-06 |
| [OTIS Mock AIME 2024-2025](https://noometry.com/benchmarks/otis-mock-aime) | 80% |  | minimal | [Epoch AI](https://epoch.ai/benchmarks) | 2026-07-15 |
| [ProofBench](https://noometry.com/benchmarks/proofbench) | 31% | #41 of 77, top 54% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LMArena Math](https://noometry.com/benchmarks/arena-math) | 1504 | #11 of 285, top 4% | high | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [FrontierMath (Feb 2025 set)](https://noometry.com/benchmarks/frontiermath-2025-02) | 39% | #10 of 68, top 15% | high | [Epoch AI](https://epoch.ai/benchmarks) | 2026-05-22 |
| [FrontierMath Tier 4 (v1)](https://noometry.com/benchmarks/frontiermath-tier-4-v1) | 14.6% | #15 of 55, top 28% | high | [Epoch AI](https://epoch.ai/benchmarks) | 2026-05-25 |

### Knowledge

Gemini 3.5 Flash Knowledge benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [GPQA Diamond](https://noometry.com/benchmarks/gpqa-diamond) | 92.8% | #19 of 186, top 11% | high | [Epoch AI](https://epoch.ai/benchmarks) | 2026-05-22 |
| [GPQA Diamond](https://noometry.com/benchmarks/gpqa-diamond) | 88.9% |  | low | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-06 |
| [GPQA Diamond](https://noometry.com/benchmarks/gpqa-diamond) | 86.4% |  | minimal | [Epoch AI](https://epoch.ai/benchmarks) | 2026-07-15 |
| [SimpleQA Verified](https://noometry.com/benchmarks/simpleqa-verified) | 66.2% | #11 of 77, top 15% | high | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-27 |
| [LMArena Expert](https://noometry.com/benchmarks/arena-expert) | 1495 | #27 of 273, top 10% | high | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Multimodal

Gemini 3.5 Flash Multimodal benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Vision](https://noometry.com/benchmarks/arena-vision) | 1310 | #10 of 122, top 9% | high | [LMArena](https://lmarena.ai/leaderboard/vision) | 2026-10-09 |
| [Blueprint-Bench 2](https://noometry.com/benchmarks/blueprint-bench-2) | 33.6% | #9 of 31, top 30% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LMArena Document](https://noometry.com/benchmarks/arena-document) | 1463 | #16 of 38, top 43% | medium | [LMArena](https://lmarena.ai/leaderboard/document) | 2026-09-13 |

### Multilingual

Gemini 3.5 Flash Multilingual benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Non-English](https://noometry.com/benchmarks/arena-non-english) | 1476 | #13 of 297, top 5% | high | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Chinese](https://noometry.com/benchmarks/arena-chinese) | 1526 | #22 of 285, top 8% | medium | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena French](https://noometry.com/benchmarks/arena-french) | 1490 | #20 of 223, top 9% | high | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena German](https://noometry.com/benchmarks/arena-german) | 1492 | #12 of 231, top 6% | medium | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Japanese](https://noometry.com/benchmarks/arena-japanese) | 1486 | #12 of 211, top 6% | high | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Korean](https://noometry.com/benchmarks/arena-korean) | 1451 | #17 of 213, top 8% | medium | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Russian](https://noometry.com/benchmarks/arena-russian) | 1493 | #11 of 283, top 4% | high | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Spanish](https://noometry.com/benchmarks/arena-spanish) | 1480 | #13 of 226, top 6% | high | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Instruction Following

Gemini 3.5 Flash Instruction Following benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Instruction Following](https://noometry.com/benchmarks/arena-instruction-following) | 1467 | #26 of 298, top 9% | high | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Long Context

Gemini 3.5 Flash Long Context benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Longer Query](https://noometry.com/benchmarks/arena-longer-query) | 1482 | #20 of 291, top 7% | high | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Writing & Preference

Gemini 3.5 Flash Writing & Preference benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Text](https://noometry.com/benchmarks/arena-text) | 1482 | #14 of 297, top 5% | high | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Creative Writing](https://noometry.com/benchmarks/arena-creative-writing) | 1470 | #13 of 295, top 5% | medium | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [EQ-Bench 4](https://noometry.com/benchmarks/eqbench-4) | 1087 | #24 of 28, top 86% |  | [EQ-Bench](https://eqbench.com/) |  |
| [LMArena Multi-Turn](https://noometry.com/benchmarks/arena-multi-turn) | 1481 | #19 of 295, top 7% | high | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

## API pricing by provider

Gemini 3.5 Flash API prices
| Route | Input $/M | Output $/M | Cached input $/M | Checked |
| --- | --- | --- | --- | --- |
| [google](https://ai.google.dev/gemini-api/docs/models) | $1.50 | $9 | $0.15 | 2026-10-10 |
| [openrouter](https://openrouter.ai/google/gemini-3.5-flash) | $1.50 | $9 | $0.15 | 2026-10-10 |
| [vertex](https://cloud.google.com/vertex-ai/generative-ai/docs/models) | $1.50 | $9 | $0.15 | 2026-10-10 |

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

## Compare Gemini 3.5 Flash

-   [Gemini 3.5 Flash vs Gemini 2.5 Flash](https://noometry.com/compare/gemini-2-5-flash-vs-gemini-3-5-flash)
-   [Gemini 3.5 Flash vs DeepSeek V4 Pro](https://noometry.com/compare/deepseek-v4-pro-vs-gemini-3-5-flash)
-   [Gemini 3.5 Flash vs Gemini 3.6 Flash](https://noometry.com/compare/gemini-3-5-flash-vs-gemini-3-6-flash)
-   [Gemini 3.5 Flash vs GPT-5.6 Luna](https://noometry.com/compare/gemini-3-5-flash-vs-gpt-5-6-luna)
-   [Gemini 3.5 Flash vs GPT-5.2](https://noometry.com/compare/gemini-3-5-flash-vs-gpt-5-2)
-   [Gemini 3.5 Flash vs Claude Sonnet 5](https://noometry.com/compare/claude-sonnet-5-vs-gemini-3-5-flash)
-   [Gemini 3.5 Flash vs DeepSeek V4 Flash](https://noometry.com/compare/deepseek-v4-flash-vs-gemini-3-5-flash)
-   [Gemini 3.5 Flash vs GPT-6 Astra](https://noometry.com/compare/gemini-3-5-flash-vs-gpt-6-astra)
-   [Gemini 3.5 Flash vs Claude Fable 5.1](https://noometry.com/compare/claude-fable-5-1-vs-gemini-3-5-flash)
-   [Gemini 3.5 Flash vs Kimi K3](https://noometry.com/compare/gemini-3-5-flash-vs-kimi-k3)
-   [Gemini 3.5 Flash vs Grok 4.6](https://noometry.com/compare/gemini-3-5-flash-vs-grok-4-6)
-   [Gemini 3.5 Flash vs Qwen3.8 Max](https://noometry.com/compare/gemini-3-5-flash-vs-qwen3-8-max)
-   [Gemini 3.5 Flash vs GLM-5.3](https://noometry.com/compare/gemini-3-5-flash-vs-glm-5-3)
-   [Gemini 3.5 Flash vs Muse Spark 1.3](https://noometry.com/compare/gemini-3-5-flash-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 3.6 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
-   [Gemini 2.5 Pro](https://noometry.com/models/gemini-2-5-pro)45.0

## Frequently asked questions

### How good is Gemini 3.5 Flash?

Gemini 3.5 Flash by Google ranks 32nd of 354 ranked models on the Noometry Index as of October 2026, with a score of 54.2. Its strongest category is knowledge, where it ranks 11th. API pricing starts at $1.50 per million input tokens and $9 per million output tokens, with a 1.05M-token context window.

### How much does Gemini 3.5 Flash cost?

Gemini 3.5 Flash costs $1.50 per million input tokens and $9 per million output tokens on Google's own API, with cached input at $0.15.

### What is Gemini 3.5 Flash's context window?

Gemini 3.5 Flash accepts up to 1.05M tokens of input and can write up to 66K tokens in one response.

### Is Gemini 3.5 Flash open source?

No. Gemini 3.5 Flash is proprietary and available only through Google's API and partner platforms.

### What are Gemini 3.5 Flash's strengths and weaknesses?

Relative to other ranked models, Gemini 3.5 Flash places best in knowledge, multilingual, reasoning and lowest in agentic & tool use, writing & preference, coding.

### What is Gemini 3.5 Flash best at?

Its best category is knowledge, where it ranks 11th on Noometry.

### Cite this page

Noometry. (2026). Gemini 3.5 Flash benchmarks and pricing. Retrieved October 10, 2026, from https://noometry.com/models/gemini-3-5-flash

Quote Noometry with a link back to this page. It is also available in [Markdown](https://noometry.com/md/models/gemini-3-5-flash.md).