Gemini 2.5 Flash
API request failed. The model was not evaluated.
What is new in Gemini 2.5 Flash is hybrid reasoning. Google lets developers turn thinking on or off and control it through a budget. The stable GA model remains served, but API access is now limited to users with prior 2.5 usage. Gemini 3 Flash Preview is the later model in the documented line.
The model card lists limitations in causal understanding, complex logical deduction, and counterfactual reasoning.
| Specification | Value and source |
|---|---|
| Weights | ProprietarySource |
| Access | APISource |
| Context window | 1,048,576 tokensSource |
| Knowledge cutoff | January 2025Source |
| Notes | 1M context, parameter count not disclosedSource |
| API model ID | gemini-2.5-flashSource |
| 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 | 2025-06-17Source |
| Knowledge cutoff | 2025-01Source |
| Capabilities | function calling, structured outputs, search grounding, Google Maps grounding, URL context, code execution, file searchSource |
| General availability | 2025-06-17 (General availability (GA).)Source |
Benchmark meta-analysis
These Gradually indexes place selected published measurements on a 0 to 100 scale. They are not accuracy percentages and do not guarantee results in your application.
Retrieval dates of the sources used 2026-08-05 - 2026-08-26
Not enough independent results for a score yet
An overall score needs at least eight test series.
provisional
Published configurations differ within this comparison cohort. Treat the index as provisional.
Index below 1 / 100
provisional
Index below 1 / 100
provisional
Published configurations differ within this comparison cohort. Treat the index as provisional.
Index below 1 / 100
provisional
Published configurations differ within this comparison cohort. Treat the index as provisional.
Index below 1 / 100
provisional
Published configurations differ within this comparison cohort. Treat the index as provisional.
Method version: benchmark-meta-score-v3
The index includes active measurements from reviewed primary sources when at least five models are compared in the same documented comparison slice across dataset, harness, agent, tools, and trial count. Each benchmark series and evaluator contributes one shared setup slice from the newest capture. When one source and series include several explicitly documented reasoning tiers, the highest documented tier (none through max) is selected, never the best result value. The explicit source label “Non-reasoning” is treated as none. Unknown or ambiguous tiers exclude the model from that series. Within each series, percentages and rates are logit-transformed, other units stay unchanged, and all values are then standardized. A one-factor model then estimates one shared strength per model and, per series, how sharply it separates the models. Area scores move away from that strength only as far as the model's own results in the area support. The overall score weights the core areas at 75% and finance, law and health at 25%. It requires at least eight test series from two sources and three areas. The 0 to 100 scale refers to a fixed reference group of 29 language models whose average sits at 50.
Published model-specific parameters can differ. This is not a controlled experiment; comparisons with such differences are marked provisional.
Unmeasured series are not entered as zero. Where a model has no own results in a core area, its overall strength stands in, and the note “estimated without own results in …” names the area. Fewer test series lead to a larger standard error.
The 95% interval follows from the standard error of 200 recalculations with randomly redrawn test families. It describes how precisely the recorded test series determine the value. It is no prediction for future tasks or for later recalculations with other participants.
The source count is not a count of independent experiments.
OECD handbook on composite indicatorsAll 5 test families and 5 of 5 raw measurements are listed here. The complete calculation for every model is available in the JSON export.
Family weight in the fixed test panel (informative): 0.89 % · Coverage of this test family: 100 %
Family weight in the fixed test panel (informative): 0.89 % · Coverage of this test family: 100 %
Family weight in the fixed test panel (informative): 1.19 % · Coverage of this test family: 100 %
Published configurations differ within this cohort.
Family weight in the fixed test panel (informative): 2.08 % · Coverage of this test family: 100 %
Published configurations differ within this cohort.
Family weight in the fixed test panel (informative): 2.68 % · Coverage of this test family: 100 %
Published configurations differ within this cohort.
Each evaluator measures different capabilities under its own conditions. Test series, composite indices and their components stay separate. The detailed results below retain their scales, configurations and source dates.
| Evaluator | Test series | Composite indices | Recorded active measurements |
|---|---|---|---|
| Artificial Analysis | 3 | 1 | 16 |
| Vals AI | 3 | 0 | 14 |
| Princeton HAL | 2 | 0 | 12 |
| Scale AI Evals | 3 | 0 | 3 |
Coverage is not a quality ranking. Overlapping tests and multiple settings do not count as independent experiments. Vendor claims, historical and disputed results are excluded from this overview and remain labelled in the detailed evidence.
6 measurements from these sources still lack a verified test-family identity and do not increase the test-series count.
Page 1 of 6
Reliability evaluation on 165 GAIA tasks with repetitions and perturbations. Accuracy, reliability, consistency, predictability, robustness, and safety are separate metrics.
| Sub-task | Gemini 2.5 Flash (This model) | Claude Opus 4.5 | Claude Opus 4.7 | Gemini 3.1 Pro Preview | Gemini 3.5 Flash | GPT-4o mini | Gemini 2.5 Pro | o1 | GPT-5.5 |
|---|---|---|---|---|---|---|---|---|---|
| Consistency | 0.7 | 0.81 (best value in this row) | 0.81 (best value in this row) | 0.76 | 0.75 | 0.73 | 0.72 | 0.68 | 0.61 |
| Predictability | 0.64 | 0.84 (best value in this row) | 0.73 | 0.78 | 0.8 | 0.58 | 0.71 | 0.68 | 0.8 |
| Reliability | 0.74 | 0.85 (best value in this row) | 0.84 | 0.82 | 0.84 | 0.76 | 0.78 | 0.79 | 0.79 |
| Robustness | 0.87 | 0.91 | 0.99 | 0.94 | 0.96 | 0.97 | 0.91 | 1 (best value in this row) | 0.95 |
| Safety | 1 (best value in this row) | 1 (best value in this row) | 1 (best value in this row) | 1 (best value in this row) | 1 (best value in this row) | 1 (best value in this row) | 1 (best value in this row) | 1 (best value in this row) | 1 (best value in this row) |
Unit: ratinghigher is betterAs of August 6, 2026Source: Princeton HALbars scaled within each row, not across rows
Accuracy
Reliability evaluation on 165 GAIA tasks with repetitions and perturbations. Accuracy, reliability, consistency, predictability, robustness, and safety are separate metrics.
higher is betterAs of August 6, 2026Scale: 0% - 100%
26 cleaned customer-service tasks involving dialogue, policy compliance, and mutating backend tools. The cleaned subset removes 24 broken or ambiguous tasks. Accuracy and reliability dimensions measure different properties.
| Sub-task | Gemini 2.5 Flash (This model) | Claude Opus 4.7 | Claude Opus 4.5 | GPT-5.5 | Gemini 3.1 Pro Preview | Gemini 3.5 Flash | Gemini 2.5 Pro | GPT-4o mini | o1 |
|---|---|---|---|---|---|---|---|---|---|
| Consistency | 0.75 | 0.88 (best value in this row) | 0.84 | 0.84 | 0.81 | 0.78 | 0.74 | 0.74 | 0.71 |
| Predictability | 0.6 | 0.87 (best value in this row) | 0.85 | 0.84 | 0.83 | 0.82 | 0.78 | 0.35 | 0.74 |
| Reliability | 0.72 | 0.89 (best value in this row) | 0.88 | 0.89 (best value in this row) | 0.86 | 0.86 | 0.81 | 0.67 | 0.81 |
| Robustness | 0.82 | 0.91 | 0.97 | 0.97 | 0.94 | 0.97 | 0.93 | 0.93 | 0.98 (best value in this row) |
| Safety | 0.9 | 0.94 | 0.98 | 0.96 | 0.97 | 0.99 (best value in this row) | 0.92 | 0.85 | 0.91 |
Unit: ratinghigher is betterAs of August 5, 2026Source: Princeton HALbars scaled within each row, not across rows
Accuracy
26 cleaned customer-service tasks involving dialogue, policy compliance, and mutating backend tools. The cleaned subset removes 24 broken or ambiguous tasks. Accuracy and reliability dimensions measure different properties.
higher is betterAs of August 5, 2026Scale: 0% - 100%
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One SVG prompt and fixed output settings. Captures are shown only with 0 reported reasoning tokens or documented lack of reasoning controls. Identical test conditions do not make the models' internal compute identical.
API request failed. The model was not evaluated.
A community classic for free-form SVG drawing.
Gemini 2.5 Flash
The response reached the token limit. No complete recording is available.
Reasoning (requested): high
Not yet visually reviewed. A successful recording does not confirm correct physics or full compliance with the prompt.
Generate an SVG of a pelican riding a bicycle
Token limit including reasoning: 8,192 tokens
Task origin (Simon Willison)55.7 / 100
Next generation in the directory
Google states that Gemini 3 Flash becomes the default Gemini model in the app, replacing Gemini 2.5 Flash there. Gemini 2.5 Flash remains a GA API model, so this is a nearest-profile app transition rather than an API retirement or direct replacement.
Google, "Gemini 3 Flash" (2026-09-22)| Type | Evidence and data date |
|---|---|
| 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 status | Research date September 8, 2026. 4 source URLs checked. This documents the inspected sources, not an exhaustive inventory of every publication. |
| Not found in the inspected sources | parameters-billions Original wording Google does not publish a parameter count on the Gemini API model page. |
| Not found in the inspected sources | active-parameters-billions Original wording Google does not publish active parameter counts for Gemini API models. |
| Additional source | Model metadata |
| Additional source | Artificial Analysis (retrieved October 19, 2026) |
| Additional source | Artificial Analysis (retrieved October 19, 2026) |
| Additional source | Artificial Analysis (retrieved October 19, 2026) |
| Additional source | Princeton HAL (retrieved August 6, 2026) |
| Additional source | Princeton HAL (retrieved August 5, 2026) |
| Additional source | LongBench (retrieved September 2, 2026) |
| Additional source | Scale AI (retrieved August 26, 2026) |
| Additional source | Scale AI (retrieved August 26, 2026) |
| Additional source | Scale AI (retrieved August 26, 2026) |
| Additional source | Vals AI (retrieved October 15, 2026) |
| Additional source | Vals AI (retrieved October 15, 2026) |
| Additional source | Vals AI (retrieved October 15, 2026) |
| Additional source | Google DeepMind (retrieved September 8, 2026) · Gemini 2.5 Flash model card · Editorial description reviewed October 2, 2026 |
| Additional source | Model metadata (retrieved September 8, 2026) |
| Additional source | OpenRouter: Popularity index (derived), CC BY 4.0 |
| Additional source | Vercel AI Gateway: Popularity index (derived), CC BY 4.0 |
| Additional source | Ollama: cumulative downloads for the popularity index |
| Additional source | Replicate: cumulative runs for the popularity index |
| Additional source | Google Trending Now: limited feed selection for Germany and the US |
| Additional source | Creative Commons Attribution 4.0 |
| Additional source | Google, "Gemini 3 Flash" (2026-09-22) |