Is Gemma 4 (Google) Down?

Quickest ways to check the current status of deepmind.google plus recent known issues and working alternatives if it's out.

Last editorial review: 2026-10-06

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Known issues we've tracked

EMBEDDINGGEMMA 2 -- A 740M OPEN MULTIMODAL EMBEDDING MODEL ON THE GEMMA 4 ARCHITECTURE (2026-10-06 blog; Hugging Face repo created 2026-09-14; vendor-primary): Google announced **EmbeddingGemma 2**, 'the most capable model for on-device multimodal embeddings', which maps 'text (incl. code), images, video, and audio inputs -- and combinations thereof -- into a single, unified 768-dimensional vector space'. **Specs (model card):** 740M total parameters = a 270M text model (130M transformer + 140M embedder) plus selectively loadable vision (170M) and audio (300M) encoders; **Apache 2.0** (the card states Apache 2.0 while linking Google's Gemma 4 license page); 100+ languages; **8K token context** ('4x larger than EmbeddingGemma 1', enough for about 5.5 minutes of audio, 29 images or 58 video frames); **Matryoshka Representation Learning** lets you truncate 768-d vectors to 512, 256 or 128 for up to 6x storage reduction; task-steered instruction prefixes. **On-device footprint:** with quantization on a Pixel 11 Pro, about 191 MB of active RAM for text-only weights and about 567 MB for the full multimodal model. **Vendor benchmarks:** MTEB Code 78.68 (from 68.76 for EmbeddingGemma 1, a 9.92-point gain), 'leading scores among sub-1B multimodal embedders' on MTEB Code and MAEB, 'matching or outperforming many larger models'. Because it 'shares its text tokenizer and audio encoder' with Gemma 4, Google pitches a combined on-device RAG stack with a lower total memory footprint. Context: the first EmbeddingGemma passed 20 million downloads. **Timing note:** the Hugging Face repo google/embeddinggemma-2 was created 2026-09-14, three weeks before the blog post -- weights before write-up, the pattern this site has seen with Qwen. Not a Gemma 4 LLM revision; recorded here because this is the Gemma family page and the model is the retrieval half of Google's on-device open stack.
2026-10-06•Google (blog.google/innovation-and-ai/technology/developers-tools/embeddinggemma-2/, root RSS pubDate Tue, 06 Oct 2026, on-page 'Oct 06, 2026'); Hugging Face model card (huggingface.co/google/embeddinggemma-2/raw/main/README.md -- 'license: apache-2.0', 740M, 768-d, 8K; API createdAt 2026-09-14) -- both fetched 2026-10-06 via curl
2026-04-18 BF16 stability refresh -- Google re-released Gemma 4 multimodal checkpoints in BF16 format focused on truthfulness, JSON / tool-call formatting, long-context extraction reliability, and loop resistance. Not a new model version; a quality refresh that fixes specific failure modes developers were hitting in production. If you pulled weights before 2026-04-18, consider re-downloading for the new checkpoints
2026-04•Google DeepMind Gemma page, Hugging Face
Gemma 4 launched April 2, 2026 with improved licensing -- earlier Gemma versions had restrictive use clauses that confused developers
2026-04•The Register, Hugging Face
Function calling support is new -- some users report inconsistent tool-use behavior compared to Llama 3 or Mistral
2026-04•Hugging Face discussions

Issues here are sourced from our editorial sweeps, not real-time telemetry. Newer issues may exist.

What to use if Gemma 4 (Google) is down

Top AIToolTier-ranked alternatives in the same category, ordered by our overall score.

A

Qwen (Alibaba)

8.8

**Qwen-Image-2.1 went open-weight (weights 2026-09-14, blog 2026-09-20)** -- a unified text-to-image and editing model with a 7B visual-generation component, native transparent (RGBA) output, up to 10 reference images and mask-guided local edits -- but under a **research-only licence, not Apache**: commercial use needs a separate licence from Alibaba. Alibaba's open-weights + API family, and August 2026 was its biggest open-release month yet: **Qwen3.8-2.4T-A95B -- the Max-class flagship -- went open-weight on 2026-08-08** (custom Qwen3.8-Max licence), **Qwen3.8-27B** dense landed Apache 2.0 (8/05), and **Qwen3.8-Flash-Next** (8/24 weights, 8/26 blog) previews the Qwen4 architecture: 125B main + 51B n-gram embeddings with only 6B active, served as Qwen3.8-Flash at $0.15/$0.47 per 1M. Qwen 3.7 Max remains the GA API flagship ($2.50/$7.50)

A

MiniMax M3

8.4

**MiniMax-H3's weights are public on Hugging Face (repo 2026-07-28, updated 2026-08-13) under a community licence whose open-weight grant is limited to the US, EU, UK and South Korea**, and **MiniMax Music 3 (2026-08-07)** ships open weights for five-minute full-song generation with a prominent-attribution commercial clause. MiniMax's coding/agent flagship -- M3 (June 1 2026): 1M-token context, MSA sparse attention (>15x decoding speedup at long context), SWE-Bench Pro 59.0%, Terminal-Bench 66.0%. OPEN WEIGHTS LIVE on HuggingFace since June 12 (~428B total / ~23B active, native multimodal, minimax-community license)

A

IBM Granite 4.0

8.2

IBM's enterprise-focused open-weight family -- Granite 4.0 hybrid Mamba-2 + transformer architecture (70-80% memory reduction vs pure transformer), 3B to 32B sizes, Apache 2.0. First open model family to secure ISO 42001 certification. Nano 350M runs on CPU with 8-16GB RAM. 3B Vision variant landed 2026-04-01

A

Kimi K3 (Moonshot)

8.1

Moonshot's 2.8T-parameter Kimi K3 (launched 2026-07-16/17) is the largest open-weight model ever released -- 1M context, multimodal, $3/$15 per 1M via API, ranked best-available on Arena.AI at launch. WEIGHTS SHIPPED ~2026-07-26/27 on Hugging Face (2.8T total / 104B activated, safetensors) under a custom Kimi K3 License, not the Modified MIT of the K2 line

A

gpt-oss (OpenAI)

8.1

OpenAI's FIRST open-weight models -- gpt-oss-120b (single 80GB GPU, near parity with o4-mini on reasoning) and gpt-oss-20b (runs on 16GB edge devices). Apache 2.0. Launched 2025-08-05. gpt-oss-safeguard ships in 2026 as the safety-tuned variant

About Gemma 4 (Google)

Tier A (8.3/10). Google DeepMind's open-weights model family -- multimodal, 256K context, runs on edge devices **EmbeddingGemma 2 (announced 2026-10-06; weights on Hugging Face since 9/14) adds a 740M-parameter Apache 2.0 embedding model built on Gemma 4 that maps text, code, images, video and audio into one 768-dimensional space, with an 8K context, Matryoshka truncation down to 128 dimensions and about 191 MB of RAM for text-only use on a Pixel 11 Pro.**

Read the full Gemma 4 (Google)review →