DeepMind 的 Gemini 3.6 Flash 模型卡表。 · 来源
DeepMind的Gemini 3.6 Flash模型卡表;Grok 4.5 未报告。 · 来源
DeepMind 的 Gemini 3.6 Flash 模型卡表。 · 来源
| 模型 | 输入$/1M | 产出 $/100 万美元 | SWE-Bench Pro(公共) | 终端工作台2.1 | MLE-工作台 |
|---|---|---|---|---|---|
| 双子座3.6闪存 | $1.50 | $7.50 | 58.7% | 78.0% | 63.9% |
| 双子座3.5闪存 | $1.50 | $9.00 | 55.1% | 76.2% | 49.7% |
| 双子座3.1专业版 | $2.00 | $12.00 | 54.2% | 73.8% | 42.6% |
| GPT-5.6 露娜 | $1.00 | $6.00 | 62.7% | 84.7% | 47.6% |
| 格罗克4.5 | $2.00 | $6.00 | 64.7% | 83.3% | 43.2% |
| 克劳德十四行诗 5 | $3.00 | $15.00 | 63.2% | 80.4% | 66.9% |
如 DeepMind 的模型卡中所列;价格不含缓存。 · 来源
Estimate from the version's published specs, benchmarks and reviews, 0-5; scores are only comparable within one criteria year. Scored as launched (Gemini 3.6 Flash, 21 Jul 2026): Artificial Analysis Intelligence Index 50 (v4.1, high reasoning; same as 3.5 Flash; v4.1 was current at launch, AA's page now shows 34 on v4.3.2 so later re-indexing is not used); 1M-token input window (1,048,576 per Google API docs, 64K output); $1.50 in / $7.50 out per 1M = $3.00 blended at 3:1; 304 output tokens/s measured by Artificial Analysis pre-launch (its current page shows 202 t/s, a later snapshot); inputs text, image, video, audio/PDF. Coding null: AA's index at launch used Terminal-Bench v2.1 (Google reports 78.0% on v2.1), no Terminal-Bench 4.0 figure was published at launch, so the 4.0 anchor is not applied. Reviews are AA's own pre-launch benchmark note, OfficeChai, a comparison blog (emergent.sh) and 9to5Google quoting Google; no hands-on tests found, so 4 sources are mostly benchmark-led. blog.google
Gemini 3.6 Flash scores 50 on the Artificial Analysis Intelligence Index, matching Gemini 3.5 Flash
Gemini 3.6 Flash lands at exactly 50 points on version 4.1 of the index, the identical score its predecessor was already sitting at
Gemini 3.6 Flash is an efficiency upgrade, not an intelligence upgrade.
Gemini 3.6 Flash "delivers higher precision with fewer unwanted code edits and reduced execution loops"
读者上传的照片,与图钉带来源的媒体分开显示。你可以为吃到或看到的内容评分,在餐厅图钉上还能直接在照片上标记菜品。
第一项始终是图钉的来源。总体可信度是各份资料对上方所用开始和结束时间支持程度的加权平均;资料每比最新的一份旧 180 天,权重减半。
9to5Google的发布报道日期为2026年7月21日,称谷歌“今天宣布了Gemini 3.6 Flash和3.5 Flash-Lite”;DeepMind[2]的3.6 Flash模型卡于2026年7月21日发布。
DeepMind's model card, published 21 July 2026, lists the benchmark table and the $1.50 and $7.50 per million token prices.
MarkTechPost's same-day write-up of the three-model Flash tier release.
Neural Newscast's episode "Google Ships Three New Gemini Flash Models [Model Behavior]" (2026-07-21) says: "with enterprise software. [00:48] Thatcher Collins: I'm Thatcher Collins. [00:49] Thatcher Collins: Nina, the timing of these releases is certainly noteworthy. [00:53] Thatcher Collins: Today , Google shipped Gemini 3.6 Flash, 3.5 Flash Lite, and a specialized security-focused version called Flash Cyber. [01:03] Thatcher Collins: This blitz comes immediately after"[1]
有遗漏或错误吗?用你自己的话说明:能佐证此图钉的链接、不同的开始或结束日期及理由,或缺失、有误的信息。AI 会对照此图钉的来源进行核实,搜索更好的来源,并添加任何支持你说法的页面。图钉自身的来源仍然最重要。AI 也会查看图片:显示的是别的东西或显示效果差的图片会被移到后面或替换。
原标题: Gemini 3.6 Flash Released
| 基准测试 | Gemini 3.6 Flash | Gemini 3.5 Flash | Gemini 3.1 Pro | GPT-5.6 Luna | Grok 4.5 | Claude Sonnet 5 |
|---|---|---|---|---|---|---|
| 输入价格(美元/百万token,无缓存) | $1.50 | $1.50 | $2.00 | $1.00 | $2.00 | $3.00 |
| 输出价格(美元/百万token) | $7.50 | $9.00 | $12.00 | $6.00 | $6.00 | $15.00 |
| SWE-Bench Pro (Public)(多样化智能体编程任务) | 58.7% | 55.1% | 54.2% | 62.7% | 64.7% | 63.2% |
| DeepSWE v1.1(长周期软件工程) | 49% | 37% | 12% | 67% | 54% | 54% |
| Terminal-bench 2.1(智能体终端编程,Terminus-2框架) | 78.0% | 76.2% | 73.8% | 84.7% | 83.3% | 80.4% |
| MLE-Bench(机器学习工程) | 63.9% | 49.7% | 42.6% | 47.6% | 43.2% | 66.9% |
| GDPVal-AA v2(知识工作,Elo) | 1421 | 1349 | 965 | 1584 | 1535 | 1607 |
| OSWorld-Verified(智能体计算机操作) | 83.0% | 78.4% | 76.2% | 72.6% | — | 81.2% |
| CharXiv Reasoning(复杂图表的信息综合,不使用工具) | 85.2% | 84.2% | 83.3% | 82.7% | 81.6% | 77.0% |
| CharXiv Reasoning(复杂图表的信息综合,使用工具) | 89.4% | 84.9% | 83.2% | — | — | 88.3% |
| GDM-MRCR v2 (8-needle)(长上下文表现,128k(平均)) | 91.8% | 77.3% | 84.9% | 74.8% | 81.4% | 71.6% |
| GDM-MRCR v2 (8-needle)(长上下文表现,1M(逐点)) | 54.0% | 26.6% | 26.3% | — | — | — |