Capability
75.4/100
field median 57.7
#9 of 217 ranked models
Superseded.Google has newer models in this line:Gemini 3.7 Flash
Gemini 3.6 Flash
Released Jul 21, 2026 — see all recent releases
Decision reading
Gemini 3.6 Flash scores 75.4 out of 100 and ranks #9 of 217. This profile shows 4 source-displayable benchmark rows; its strongest eligible category is Coding at #15. API pricing is $1.5 input and $7.5 output per million tokens, with cached input at $0.15.
Data as of August 14, 2026 · How the score is built
Strongest published evidence
Coding ranks #15. Particularly well-suited for software development and code generation tasks.
Validate before choosing
4 published rows leave some tracked benchmark slots empty. Agentic is its lowest eligible category at #77.
Decision snapshot
Each value carries a field reference instead of floating alone. Markers compare this model with the current ranked and priced catalog; they are not absolute quality thresholds.
Price
$1.50input / $7.50 output
input median $1
cached $0.15 · batch + cache $0.075 · blended $4.50
Speed
238tok/s
field median 93 tok/s
First token 17.93 s
Context
1Mtokens
field median 200,000
Maximum output length is tracked separately
Capability shape
Each axis shows percentile within that category’s eligible cohort. The comparison outline is the median of the six nearest public-score peers; a collapsed vertex means the category is not rank-eligible.
Gemini 3.6 Flash category percentile values
- Agentic41st percentile
- Coding89th percentile
- ReasoningNot eligible
- KnowledgeNot eligible
- MathNot eligible
- MultilingualNot eligible
- MultimodalNot eligible
- Instruction followingNot eligible
The dashed outline is median of 6 nearest peers.
Eligible category ranks
- Agentic#77/129
- Coding#15/134
- ReasoningNot ranked
- KnowledgeNot ranked
- MathNot ranked
- MultilingualNot ranked
- MultimodalNot ranked
- Inst. FollowingNot ranked
Top decileTop quartileMid-fieldNot eligible
What it costs to get this score
Published API price against the public score. The x-axis uses a log scale; the dashed path marks models that are not beaten by a cheaper, higher-scoring option. Price uses average of published input and output rates.
The chart opens on the current model. Scroll horizontally to inspect the full price axis.
Current modelGemini 3.6 Flash · 75.3 score · $4.50 blended per million tokens
Horizontal: blended price per million tokens, log scale · Vertical: public score
How much of this is verified
Coverage is split by category so a strong number never hides a thin evidence base. Verified means the row is tied to a published source; provisional rows remain visible but separate.
- Agentic1/1 verified
- Coding3/3 verified
- ReasoningNot measured
- KnowledgeNot measured
- MathNot measured
- MultilingualNot measured
- MultimodalNot measured
- Inst. FollowingNot measured
Verified sourceProvisionalNot measured
Spec sheet
Each documented value carries its source. Missing fields stay visible as not sourced or not published, rather than disappearing from the page.
- API model ID
- gemini-3.6-flashGoogle Gemini 3.6 Flash model documentation
- Context window
- 1MGoogle latest Gemini model guide
- Maximum output
- Not sourced yet
- Knowledge cutoff
- Not sourced yet
- Input modalities
- text, image, video, audio, pdfGoogle Gemini 3.6 Flash model documentation
- Output modalities
- textGoogle Gemini 3.6 Flash model documentation
- Parameters
- Not disclosed by the provider
- Availability
- Gemini API · Google AI StudioGoogle latest Gemini model guide
- Cloud regions
- Not tracked yet
- Lifecycle
- activeGoogle Gemini 3.6 Flash model documentation
- API capabilities
- Tool calling, structured outputs, and batch support are not tracked yet
- Prompt caching
- Published at $0.15 per million cached input tokensGoogle Gemini API pricing
- Self-host
- Weights are not published
- Rate limits
- Not tracked yet
Category score record
Scores and ranks appear only where published evidence can be displayed. The table keeps the score, weight, cohort, and evidence state together.
| Category | Score | Rank | Percentile | Weight | Benchmarks | Evidence |
|---|---|---|---|---|---|---|
| AgenticRank #77 of 129Percentile 41stWeight 22%1 benchmarkVerified | 45.9 | #77 of 129 | 41st | 22% | 1 benchmark | Verified |
| CodingRank #15 of 134Percentile 89thWeight 20%3 benchmarksVerified | 64.6 | #15 of 134 | 89th | 20% | 3 benchmarks | Verified |
| ReasoningWeight 17%0 benchmarksNot measured | Not measured | Not ranked | Not available | 17% | 0 benchmarks | Not measured |
| KnowledgeWeight 12%0 benchmarksNot measured | Not measured | Not ranked | Not available | 12% | 0 benchmarks | Not measured |
| MathWeight 5%0 benchmarksNot measured | Not measured | Not ranked | Not available | 5% | 0 benchmarks | Not measured |
| MultilingualWeight 7%0 benchmarksNot measured | Not measured | Not ranked | Not available | 7% | 0 benchmarks | Not measured |
| MultimodalWeight 12%0 benchmarksNot measured | Not measured | Not ranked | Not available | 12% | 0 benchmarks | Not measured |
| Inst. FollowingWeight 5%0 benchmarksNot measured | Not measured | Not ranked | Not available | 5% | 0 benchmarks | Not measured |
Benchmark ledger
Coding opens by default. The marker compares each value with the best source-verified result in the catalog; provisional leaders do not set the reference. Expand the remaining categories for every published row.
Coding3 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| deepSwe | Score49% | Versus best verified row Best verified: GPT-5.6 Sol · 72.7% | Gap23.7 behind | WeightDisplay only | |
| cursorBench32 | Score53.5% | Versus best verified row Best verified: Grok 4.6 · 70.8% | Gap17.3 behind | WeightDisplay only | Benchmark exact |
| EEBenchEEBench V1 core corpus | Score37.4% | Versus best verified row Best verified: Grok 4.6 · 58.3% | Gap20.9 behind | WeightDisplay only | Benchmark exact |
Agentic1 row
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| OSWorld-Verified | Score83% | Versus best verified row Best verified: Qwen3.8 Max · 86.1% | Gap3.1 behind | WeightWeighted 34% |
Lineage
The sequence follows explicit supersedes links. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.
December 2025
Gemini 3 FlashScore 59.6 · $0.5 / $3
May 19, 2026
Gemini 3.5 FlashScore 64.4 · $1.5 / $9
Jul 21, 2026 · you are here
Gemini 3.6 FlashScore 75.3 · $1.5 / $7.5
Aug 13, 2026
Gemini 3.7 FlashNot publicly ranked · $0.75 / $3.75
Base entry
How to read this profile
The visual layer above carries the decisions. These notes preserve the model, ranking, coverage, and family context behind the numbers.
Gemini 3.6 Flash ranks #9 of 217 on the public leaderboard with a score of 75.35/100. Its source-verified position is #9 of 104.
Gemini 3.6 Flash is a proprietary model with a 1M context window. It uses an explicit reasoning mode, which can improve complex problem solving while adding latency and token use.
Available through the Gemini API in Google AI Studio and Android Studio, Google Antigravity, Gemini Enterprise, and the Gemini app.
Its explicit predecessor is Gemini 3.5 Flash. 4 of 431 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.
Its strongest eligible category is Coding at #15, while its lowest eligible position is Agentic at #77. particularly well-suited for software development and code generation tasks.
Radar
Full release historyGemini 3.6 Flash release history
Gemini 3.6 Flash, Gemini 3.5 Flash-Lite, and Gemini 3.5 Flash Cyber released
Google · Model release
Source confirmed
Frequently asked questions
How does Gemini 3.6 Flash perform overall in AI benchmarks?
Gemini 3.6 Flash ranks #9 out of 217 models on the public BenchAlign leaderboard, with a score of 75.35/100. Its evidence status is Supported, and this profile shows 4 source-displayable benchmark rows. The label describes evidence depth, not a provider quality claim; inspect category rows before choosing a workload.
Is Gemini 3.6 Flash good for coding and programming?
Gemini 3.6 Flash ranks #15 out of 134 eligible models for coding and programming, with a public category score of 64.6/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.
Is Gemini 3.6 Flash good for agentic tool use and computer tasks?
Gemini 3.6 Flash ranks #77 out of 129 eligible models for agentic tool use and computer tasks, with a public category score of 45.9/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.
Does Gemini 3.6 Flash have full benchmark coverage on BenchLM?
No. Gemini 3.6 Flash currently has 24 source-displayable rows across 431 tracked benchmark slots. The profile exposes published, non-generated evidence and leaves missing categories blank until an exact evaluation is available. Coverage describes how much was measured; it is not a penalty added to an individual benchmark result.
What is the context window size of Gemini 3.6 Flash?
Gemini 3.6 Flash has a documented context window of 1M. That figure is the maximum combined prompt and retained-conversation space reported for this exact model; it is not the maximum output length. The profile keeps output limits separate because providers often publish those limits independently.
Last updated August 14, 2026. Runtime fields remain blank until a sourced snapshot exists.
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