Gemini 3.5 Flash
gemini-3-5-flashgemini-3.5-flash- 🆕 Google's newest, most intelligent Flash-tier model, GA in 2026.
- 📏 1M-token input context for long documents and agentic tasks.
- 🧠 Built on Gemini 3 Flash foundation with adjustable thinking levels.
- 👁️ Accepts text, image, video, audio, and PDF inputs.
- 🔧 First-party function calling, code execution, structured output.
- ⚡ Targets near-Pro reasoning at Flash-class latency and cost.
- 🌐 Google Search grounding for agentic, tool-using workflows.
- 💬 Designed for multi-turn chat and coding assistance.
Google is an American multinational technology corporation and one of the world's most valuable brands. A subsidiary of parent company Alphabet Inc., Google operates across search, cloud computing, consumer electronics, and artificial intelligence. Its DeepMind and Google…
Explore 17 more models by Google →Gemini 3.5 Flash is Google's speed-optimized frontier model, released in May 2026 and positioned for agentic workflows, multi-turn chat, and coding assistance. It is built directly on the Gemini 3 Flash reasoning foundation, adding explicit thinking levels that let developers trade quality against cost and latency per request. The model accepts text, image, video, audio, and PDF inputs, outputs text, and carries a roughly 1M-token context window.
Compared with its same-family predecessor [[sibling:gemini-3-flash-preview|Gemini 3 Flash Preview]], Gemini 3.5 Flash keeps the same 1M context, tool set, and platform features while improving performance, so code and short agentic tasks run at strong quality with lower latency. Google frames it as its most intelligent and capable Flash model to date.
The model integrates first-party function calling, code execution, structured output, and Google Search grounding, making it suited to tool-using agents rather than only single-turn prompts. Google positions it to deliver near-Pro reasoning while retaining Flash-class latency and cost characteristics.
It is distributed through Google Cloud's Gemini Enterprise Agent Platform and Vertex AI, alongside Google DeepMind's model channels, where the model card and platform documentation detail its capabilities and deployment options.
This About section is AI-generated from public sources via VeniceStats + Venice inference, with no human editing. It may contain inaccuracies.
| Seller | Reputation↓ | Routing | Input $/M | Cached $/M | Output $/M | Categories | API |
|---|---|---|---|---|---|---|---|
| ▲ Apex Ant 0x73b4…e736 | 83 | #2 | $0.6975 | $0.0698 | $4.2525 | chat,fast,premium,vision,multimodal,reasoning,long-context,agents | openai-chat-completions |
| Open Ant 0xe4f6…5bc4 | 74 | #3 | $1.0075 | $0.1008 | $6.1425 | chat,reasoning,vision,multimodal,tools,long-context | openai-chat-completions |
| surplusintelligence.ai 0x0e49…8927 | 68 | #1 | $0.465 | $0.0465 | $2.835 | agents,audio,chat,cheap,fast,frontier,function-calling,multimodal,reasoning,research,tasks,tools,video,vision,web-search | openai-chat-completions |
| NovaRoute AI 0xc50d…ed7b | 60 | gated | $0.4604 | $0.4604 | $2.8067 | chat,coding,code,reasoning,agent,tasks,gemini,google,fast,value,surplus,openai-compatible,low-cost,verified,github,response-auth,base-usdc,monitored | openai-chat-completions |
| Super Seeder 0xd19f…41f3 | 40 | gated | $0.775 | $0.0775 | $4.725 | chat,reasoning,vision,multimodal,tools,long-context | openai-chat-completions |
| Fire Ant 🔥🐜 0xbe05…bc5d | 37 | gated | $1.3512 | $0.1395 | $8.2379 | agent,base-usdc,chat,code,coding,fast,gemini,github,google,json,low-cost,math,monitored,openai-compatible,reasoning,response-auth,surplus,tasks,tools,value,verified | — |
| D5V1N2 0xd5e7…7be0 | 26 | gated | $1.96 | $0.20 | $11.72 | chat,reasoning,coding,research,multimodal,google,frontier,gemini | openai-chat-completions |
| Tokaine · Vertex Gemini 3.5 Flash 0x68cb…0634 | 8 | gated | $0.75 | $0.75 | $4.50 | chat,fast,reasoning,vision,multimodal,tools,json,coding | openai-chat-completions |
| antseed-neon-puma-944e 0x6650…944e | 3 | gated | $0.5286 | $0.155 | $3.2225 | chat,math | openai-chat-completions |
| antseed-opal-badger-2580 0xc85d…2580 | 1 | gated | $0.775 | $0.775 | $4.725 | chat | openai-chat-completions |
| Apex TEE Test 0xe672…7955 | 0 | gated | $1.485 | $1.485 | $8.91 | chat,fast,premium,vision,multimodal,reasoning,long-context,agents | openai-chat-completions |
| Leftermute 0x388b…5389 | 0 | gated | $0.1162 | $0.1162 | $0.5808 | chat,coding,json,tools | openai-chat-completions |
"Best price" and the seller table are live AntSeed catalog data (advertised $/1M tokens — or $ per generated image for unit-billed image models — not settled amounts). Reputation = on-chain trust (0-100). "Routing" = the SDK's default buyer routing (what the VPR desktop app ships with): a trust ≥ 60 gate on the effective reputation, then cheapest-first among routable sellers; live failover state (per-peer cooldowns) is buyer-side runtime and not included. Model knowledge (TLDR, provider, About) via the VeniceStats enrichment layer. Advertised catalog, not the model used in any specific purchase. "Usage on AntSeed" counts only settlements whose buyers share the per-model split on-chain (metadata v2/v3, opt-in), so every usage figure is a lower bound.