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Gemma 3n E4B

Google's mobile-first multimodal open model — text, image, audio, and video on-device in ~3GB of RAM.

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About

Gemma 3n E4B is Google's mobile-first multimodal model, generally available June 26, 2025 (previewed at Google I/O, May 20, 2025). "E4B" = effective-4B: the checkpoint totals ~8B parameters but uses the MatFormer (Matryoshka Transformer) nested architecture, so a fully functional 4B submodel runs inside the larger model and memory footprint stays around 3GB (E2B sibling: ~2GB). It natively handles text, image, audio, and video input with a 32K-token context, 140-language text support, and on-device speech-to-text/translation via a Universal Speech Model-based audio encoder (30-second clips) plus a MobileNet-V5 vision encoder (provider-claimed 60 FPS video on Pixel).

Benchmarks are provider-reported (official model card): LMArena >1300 — the first model under 10B parameters to break 1300; MMLU 64.9, MBPP 63.6, HumanEval 75.0, Global-MMLU-Lite 64.5, MMLU-Pro 50.6 (E4B IT). Per-layer embeddings cut parameters ~46% and KV cache sharing doubles prefill speed vs Gemma 3 4B (provider claims).

Licensed under the Gemma Terms of Use (custom, non-OSI; gated download requiring terms acceptance; commercial use allowed with restrictions). No paid official API — available free in Google AI Studio, on Kaggle, and self-hosted via Transformers, llama.cpp, Ollama, MLX, and Google AI Edge. The reference choice for private, offline, on-device multimodal AI.

Specs

Context window

32K tokens (input; output up to 32K minus input)

Pricing

No paid official API from Google — free in Google AI Studio (rate-limited) and free to self-host. Third-party hosts set their own rates. (provider-claimed: no per-token SKU exists)

Free quota

Google AI Studio free tier; Kaggle free GPU/TPU hours; Ollama/llama.cpp local inference unlimited.

API access

Google AI Studio (free tier API); self-host via Transformers, llama.cpp, Ollama, MLX, Google AI Edge; Kaggle. No paid official API SKU.

Weights

Open weights

Released

June 26, 2025

Benchmarks

Provider-reported (official model card / Google): LMArena >1300 (first sub-10B model to break 1300); MMLU 64.9, MBPP 63.6, HumanEval 75.0, Global-MMLU-Lite 64.5, MMLU-Pro 50.6 (E4B IT); 2x prefill latency improvement over Gemma 3 4B.

Independent: Not yet independently replicated at batch time; launch press (Neowin, Campus Technology, Jul 2025) confirmed the LMArena claim as Google's reported figure.

Provider-reported unless a source says otherwise. Benchmarks are marketing-adjacent by nature — treat them as directional.

Use cases

on-device-aimobile-appsoffline-assistantsmultimodal-chatspeech-translationedge-visionprivacy-sensitive-ai

Trust score — 6/10

/10 trustVerified

Scored 6/10 (verified tier, metrics-v1). Evidence: HF: google/gemma-3n-E4B-it; HF downloads 12,053 (peer-normalized); released 474 days ago. Manual review: LMArena >1300 is Google-reported; no paid official API (free via AI Studio/Kaggle/self-host). License: Gemma Terms of Use — custom, non-OSI, gated (describe as 'open weights', never 'open source').

How the trust score is built

Full methodology →
Adoption · stars/downloads, log-scaled vs peers
6.3/10
Maintenance · recency, releases, issue load
5.0/10
Openness · license + docs
5.8/10
Manual review · sanity read + red-flag check
8.0/10
  • · HF: google/gemma-3n-E4B-it
  • · HF downloads 12,053 (peer-normalized)
  • · released 474 days ago
  • · manual review: LMArena >1300 is Google-reported; no paid official API (free via AI Studio/Kaggle/self-host)

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