Model comparison
nanoMoE vs Gemini 2.5 Pro
Capability radar, value bars, and side-by-side posture.
nanoMoE
Not scored
value score
Gemini 2.5 Pro
93
value score
nanoMoE ctx
—
Gemini 2.5 Pro ctx
1.0M
Capability radar
Value · context · multimodal · openness · speed posture
Value head-to-head
- Gemini 2.5 Pro93
Attribute tape
| Field | nanoMoE | Gemini 2.5 Pro |
|---|---|---|
| Developer | Unknown | Google DeepMind |
| Context | — | 1.0M |
| Modalities | Text, Code, Image, Audio, Video | |
| Openness | — | Proprietary Model |
| Speed | — | — |
| Price | — | $1.25/1M in · $10/1M out |
| Value score | — | 93 |
| Summary | nanoMoE is a small-scale, open-source Mixture-of-Experts (MoE) language model and training codebase forked from nanoGPT, designed to help researchers and developers understand and experiment with sparse MoE transformer architectures on modest hardware. It implements a 6-layer decoder-only transformer with 8 total experts and 2 active experts per token, trained on OpenWebText. | Google frontier multimodal model. |