GoogleGemini 3.6 Flash
Best configuration ranks #79 of 610 on the BenchLeader Index at 60.7 ±5.8. Last measured 21 Jul 2026. Released 21 Jul 2026.
- Blended price
- $1.50/M
- $0.750 in · $3.75 out
- Output speed
- 190 tok/s
- First answer
- 16 s
- first token 1.34 s
- Context
- 1.0M
- Overall index61
- Coding50
- Maths55
- Knowledge75
- Multimodal68
- Long context67
- Composite72
Reasoning-effort configurations
The same model behaves differently depending on how much it is allowed to think. Each row is one setting, scored only on the benchmarks that were run at that setting. “Default” means the publisher did not say which setting was used.
| Effort | Index | Rank | Speed | First answer | Chat reply cost | Categories |
|---|---|---|---|---|---|---|
| minimal | – | – | 190 tok/s | 16 s | $0.0014 | Maths 59 · Reasoning 47 |
| low | – | – | 190 tok/s | 16 s | $0.0014 | Maths 60 · Reasoning 56 |
| medium | – | – | 190 tok/s | 16 s | $0.0014 | Reasoning 58 |
| high | 58.6 | #119 | 190 tok/s | 16 s | $0.0014 | Agents & tools 49 · Coding 62 · Composite 47 · Human preference 68 · Knowledge 64 · Maths 57 · Multimodal 66 · Reasoning 65 |
| defaultbest | 60.7 | #79 | 190 tok/s | 16 s | $0.0014 | Coding 50 · Composite 72 · Knowledge 75 · Long context 67 · Maths 55 · Multimodal 68 |
Benchmark results
One column per reasoning effort. Rank is among every configuration of every model on that benchmark. Hover a score for the run it came from.
Reasoning
| Benchmark | minimal | low | medium | high | default | Source | Trend |
|---|---|---|---|---|---|---|---|
| GPQA Diamond | 85.9%#72 | 86.4%#66 | – | 94.1%#6 | – | Epoch AI Benchmarking Hub | |
| LMArena Hard Prompts | – | – | – | 1500#24 | – | LMArena | |
| LiveBench Reasoningnot in index | – | – | – | 85.2%#29 | – | LiveBench | |
| GPQA Diamond (AA)not in index | – | – | – | – | 92.8%#28 | Artificial Analysis | |
| Humanity's Last Exam (AA)not in index | – | – | – | – | 40.8%#51 | Artificial Analysis | |
| GPQA Diamond (Vals)not in index | – | – | – | 93.4%#7 | – | Vals AI | |
| ARC-AGI-1 | 34.5%#138 | 76.5%#89 | 83.2%#79 | 91.2%#45 | – | ARC Prize | |
| ARC-AGI-2 | 2.6%#137 | 30.4%#88 | 50.4%#73 | 60.4%#56 | – | ARC Prize |
Coding
| Benchmark | minimal | low | medium | high | default | Source | Trend |
|---|---|---|---|---|---|---|---|
| SciCode | – | – | – | 52.7%#47 | – | SciCode | |
| WeirdML | – | – | – | 56.1%#54 | – | WeirdML | |
| FrontierCode | – | – | – | – | 34.4%#17 | Cognition | |
| LMArena Coding | – | – | – | 1518#32 | – | LMArena | |
| LMArena WebDev | – | – | – | 1537#30 | – | LMArena | |
| LiveBench Codingnot in index | – | – | – | 77.9%#25 | – | LiveBench | |
| SciCode (AA)not in index | – | – | – | – | 53.4%#48 | Artificial Analysis | |
| LiveCodeBench | – | – | – | 88.1%#8 | – | Vals AI | |
| SWE-bench (Vals)not in index | – | – | – | 79.6%#25 | – | Vals AI |
Agents & tools
| Benchmark | minimal | low | medium | high | default | Source | Trend |
|---|---|---|---|---|---|---|---|
| LMArena Agent | – | – | – | -5.3#33 | – | LMArena | |
| LiveBench Agentic Codingnot in index | – | – | – | 43.4%#44 | – | LiveBench | |
| Terminal-Bench 2.1 (Vals) | – | – | – | 73.8%#16 | – | Vals AI |
Maths
| Benchmark | minimal | low | medium | high | default | Source | Trend |
|---|---|---|---|---|---|---|---|
| FrontierMath Tiers 1–3 | – | – | – | 59.0%#29 | – | Epoch AI Benchmarking Hub | |
| FrontierMath Tier 4 | – | – | – | 21.9%#38 | – | Epoch AI Benchmarking Hub | |
| OTIS Mock AIME | 80.0%#99 | 82.2%#93 | – | 94.2%#41 | – | Epoch AI Benchmarking Hub | |
| ProofBench | – | – | – | – | 36.0%#25 | Vals AI | |
| LiveBench Mathematicsnot in index | – | – | – | 86.4%#37 | – | LiveBench | |
| AIME 2026 | – | – | – | – | 96.7%#6 | MathArena | |
| HMMT February 2026 | – | – | – | – | 89.4%#14 | MathArena | |
| MathArena Apex | – | – | – | – | 26.0%#12 | MathArena |
Knowledge
| Benchmark | minimal | low | medium | high | default | Source | Trend |
|---|---|---|---|---|---|---|---|
| SimpleQA Verified | – | – | – | 66.2%#9 | – | Epoch AI Benchmarking Hub | |
| LiveBench Data Analysisnot in index | – | – | – | 63.0%#47 | – | LiveBench | |
| AA-Omniscience | – | – | – | – | 22.1#34 | Artificial Analysis | |
| MMLU-Pro | – | – | – | 89.3%#13 | – | Vals AI | |
| LegalBench | – | – | – | 86.7%#10 | – | Vals AI | |
| CorpFin | – | – | – | 63.3%#45 | – | Vals AI | |
| TaxEval | – | – | – | 74.9%#25 | – | Vals AI |
Instruction following
| Benchmark | minimal | low | medium | high | default | Source | Trend |
|---|---|---|---|---|---|---|---|
| LiveBench Languagenot in index | – | – | – | 83.9%#12 | – | LiveBench |
Human preference
| Benchmark | minimal | low | medium | high | default | Source | Trend |
|---|---|---|---|---|---|---|---|
| LMArena Text | – | – | – | 1480#21 | – | LMArena |
Multimodal
| Benchmark | minimal | low | medium | high | default | Source | Trend |
|---|---|---|---|---|---|---|---|
| LMArena Vision | – | – | – | 1302#13 | – | LMArena | |
| MMMU-Pro | – | – | – | – | 83.2%#17 | Artificial Analysis |
Long context
| Benchmark | minimal | low | medium | high | default | Source | Trend |
|---|---|---|---|---|---|---|---|
| AA-LCR | – | – | – | – | 80.0%#51 | Artificial Analysis |
Composite
| Benchmark | minimal | low | medium | high | default | Source | Trend |
|---|---|---|---|---|---|---|---|
| Epoch Capabilities Indexnot in index | – | – | – | – | 154.3#29 | Epoch AI Benchmarking Hub | |
| LiveBench | – | – | – | 73.6%#34 | – | LiveBench | |
| AA Intelligence Index | – | – | – | – | 34.3#58 | Artificial Analysis | |
| Vals Indexnot in index | – | – | – | 55.4#20 | – | Vals AI |
Where to run it
Every provider serving this model through OpenRouter, with throughput and first-token latency measured on live traffic over the last 30 minutes and each provider’s own price. Purple marks the best in each column.
| Provider | Speed | First token | Input $/M | Output $/M | Context | Quantisation |
|---|---|---|---|---|---|---|
| Google AI Studio Priority | 139 tok/s | 1.80 s | $1.35 | $6.75 | 1.0M | – |
| Google Vertex | 122 tok/s | 1.55 s | $0.750 | $3.75 | 1.0M | – |
| Google Vertex Flex | 110 tok/s | 7.62 s | $0.375 | $1.88 | 1.0M | – |
| Google AI Studio Flex | 105 tok/s | 0.89 s | $0.375 | $1.88 | 1.0M | – |
| Google Vertex Priority | 64 tok/s | 0.90 s | $1.35 | $6.75 | 1.0M | – |
| Google AI Studio | 61 tok/s | 1.12 s | $0.750 | $3.75 | 1.0M | – |
Price history
Listed price per 1M tokens over time, as recorded by OpenRouter for the provider with the longest history.
What a task costs
Estimates from list price, output speed and time to first answer for the best configuration. “With caching” assumes three-quarters of the input is served from the prompt cache at $0.075 per 1M. Reasoning tokens are not modelled.
| Workload | Tokens in / out | Cost | With caching | Time |
|---|---|---|---|---|
| Chat reply | 400 / 300 | $0.0014 | $0.0012 | 18.0 s |
| Summarise a 30-page report | 12,000 / 600 | $0.011 | $0.0052 | 19.5 s |
| Code edit | 6,000 / 1,500 | $0.010 | $0.0071 | 24.3 s |
| Agentic coding session | 60,000 / 4,000 | $0.060 | $0.030 | 37.4 s |
| Structured extraction | 2,000 / 200 | $0.0023 | $0.0012 | 17.4 s |
See also
Data as of 9 Sept 2026. Compare these configurations.