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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

Gemini 3.5 Flash-Lite stands out as the quickest model within Google's Gemini 3.5 lineup, specifically engineered for tasks requiring low latency and for enhancing developer workflows that demand high throughput, including agentic search, document processing, coding, and extensive data analysis. It boasts an impressive output capacity of 350 tokens per second and marks a significant enhancement over earlier Flash-Lite iterations in terms of both quality and agentic capabilities. Developers have the flexibility to adjust the model's thinking level to suit the demands of the task at hand: minimal or low thinking allows for rapid processing of large volumes, while elevated thinking levels accommodate more intricate, multi-step workflows involving subagents. Furthermore, the model is equipped with built-in computational skills, enabling it to interact effectively with various digital environments across compatible platforms. Additionally, Gemini 3.5 Flash-Lite excels in coding, comprehending long contexts, and executing real-world tasks, consistently outperforming its predecessor, Gemini 3.1 Flash-Lite, in critical assessments and even exceeding the performance of Gemini 3 Flash on multiple benchmarks related to agentic functions and software engineering. This impressive performance highlights its potential to transform how developers approach complex workflows and data-intensive tasks.

Description

The Pokee-Isaac text-only agentic model features an impressive context window capable of accommodating up to 10 million tokens. This model is engineered to facilitate reasoning, planning, tool invocation, and the execution of extensive tasks, all while being compact enough for deployment within a Virtual Private Cloud (VPC), on customer premises, on a workstation, or directly on devices. According to Pokee, Isaac excels in long-context performance across the RULER benchmarks, effectively handling token ranges from 256K to 10M and outperforming competitors in multi-needle retrieval tests at 256K, 512K, and 1M tokens. Its agentic framework is specifically designed for reliable function calling, maintaining coherence over multiple turns, executing in real-shell environments, and the ability to discover and integrate tools across live Multi-Cloud Platforms (MCP) servers. In controlled assessments by Pokee, Isaac secured the top position on BFCL v4 and τ³-bench, while placing second in the Terminal-Bench 2.1 text-only subset and third in MCP-Atlas. Furthermore, security evaluations using the DTAP method indicated that it achieved the lowest overall attack success rate in the comparative analysis, all while demonstrating robust performance on benign tasks. This combination of features underscores Isaac's capability as a versatile and secure model in various operational environments.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

.NET Yes 
Android Studio Yes 
C# Yes 
Cursor Yes 
Factory Droid Yes 
Gemini 3.7 Flash Yes 
Gemini Enterprise Agent Platform Yes 
Google Antigravity Yes 
Java Yes 
JavaScript Yes 
Kotlin Yes 
Model Context Protocol (MCP) No 
Objective-C Yes 
OpenTag Yes 
Python Yes 
Replit Yes 
Scala Yes 
Swift Yes 
Vercel AI Gateway Yes 
YAML Yes 

Integrations

.NET No 
Android Studio No 
C# No 
Cursor No 
Factory Droid No 
Gemini 3.7 Flash No 
Gemini Enterprise Agent Platform No 
Google Antigravity No 
Java No 
JavaScript No 
Kotlin No 
Model Context Protocol (MCP) Yes 
Objective-C No 
OpenTag No 
Python No 
Replit No 
Scala No 
Swift No 
Vercel AI Gateway No 
YAML No 

Pricing Details

$0.30 per 1M input tokens
$0.30/1M input tokens and $2.50/1M output tokens
Free Trial No 
Free Version No 

Pricing Details

$0.15 per 1M tokens
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Google

Founded

1998

Country

United States

Website

gemini.google.com

Vendor Details

Company Name

Pokee AI

Founded

2024

Country

United States

Website

console.pokee.ai/model

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