Quick Take

This comparison examines the G9v3-3B by AI9Stars and Google's Gemini 3.5 Flash (medium). Released on July 23, 2026, and May 19, 2026, respectively, these models represent different tiers of utility. Gemini 3.5 Flash (medium) establishes itself as a high-performance model with extensive benchmark validation, while G9v3-3B enters the market as a cost-disruptive option.

Benchmark Read

Gemini 3.5 Flash (medium) demonstrates superior performance across all shared metrics. In the GPQA benchmark, Gemini scores 0.921 compared to G9v3-3B’s 0.438. Similarly, Gemini shows higher proficiency in HLE (0.399 vs 0.04), SciCode (0.53 vs 0.177), and LCR (0.71 vs 0.346). Gemini also boasts strong scores in specialized areas like TAU2 (0.956) and IFBench (0.745), whereas G9v3-3B lacks data for these categories. The Intelligence Index further highlights this gap, with Gemini scoring 45.4 against G9v3-3B’s 16.1.

Cost and Speed

Pricing structures differ drastically. G9v3-3B is entirely free, with input and output costs at $0.00/1M tokens. Conversely, Gemini 3.5 Flash (medium) operates on a paid model with a blended cost of $3.38/1M tokens ($1.50 input / $9.00 output). Regarding speed, Gemini provides a documented output speed of 246.743 tok/s with a time to first token of 12.828s. Performance metrics for G9v3-3B remain unknown.

Best Fit

Gemini 3.5 Flash (medium) is best suited for developers and enterprises requiring reliable, high-speed performance and advanced agentic capabilities. G9v3-3B is best suited for hobbyists or developers testing lightweight applications where zero-cost infrastructure is the primary requirement.