Compare/DeepSeek V4 vs Google Gemma 4

AI tool comparison

DeepSeek V4 vs Google Gemma 4

Which one should you ship with? Here is the side-by-side panel verdict, pricing read, reviewer split, and community vote comparison.

D

Open Source Models

DeepSeek V4

1.6T open-source MoE that nearly matches frontier — MIT, 1M token context

Ship

75%

Panel ship

Community

Paid

Entry

DeepSeek V4 dropped April 24, 2026 as two production-ready Mixture-of-Experts models: V4-Pro (1.6T parameters, 49B activated) and V4-Flash (284B parameters, 13B activated). Both support 1 million token context and ship under the MIT license — the most permissive option in AI. The architecture innovation is the hybrid attention mechanism combining Compressed Sparse Attention (CSA) and Heavily Compressed Attention (HCA), which slashes long-context inference costs dramatically. At 1M tokens, V4-Pro requires only 27% of the FLOPs and 10% of the KV cache compared to DeepSeek V3.2 — a meaningful efficiency gain that makes million-token context economically viable. Performance-wise, DeepSeek V4-Pro beats all rival open models on math and coding benchmarks, trailing only Google's Gemini 3.1-Pro (closed) on world knowledge. One year after V2 upended the industry, DeepSeek has done it again — a model approaching frontier performance that anyone can run, modify, and ship commercially with zero licensing friction.

G

Open Source Models

Google Gemma 4

Google's open multimodal models — vision, audio, and text under Apache 2.0

Ship

75%

Panel ship

Community

Paid

Entry

Google Gemma 4 is the most capable open model family Google has released, and the first to unify text, vision, and audio in a single architecture — all under the Apache 2.0 license. Available in four sizes (E2B, E4B, 26B MoE, 31B Dense), the lineup runs everywhere from smartphones to high-end GPUs and covers 140+ languages with context windows up to 256K. The headline stat: the 31B Dense model benchmarks above models nearly 20x its size in certain evals, making it the sharpest intelligence-per-parameter model in the open-source ecosystem as of its April 2026 release. The multimodal architecture processes documents with OCR, analyzes charts, transcribes speech, and understands video frames from a single model — no pipeline stitching required. For developers and researchers, the Apache 2.0 licensing is the real unlock. Gemma 4 is fully OSI-approved and commercially usable without restriction, building on a community of 400M+ downloads from prior Gemma versions and 100,000+ variants in the wild.

Decision
DeepSeek V4
Google Gemma 4
Panel verdict
Ship · 3 ship / 1 skip
Ship · 3 ship / 1 skip
Community
No community votes yet
No community votes yet
Pricing
Open Source / MIT
Open Source / Apache 2.0
Best for
1.6T open-source MoE that nearly matches frontier — MIT, 1M token context
Google's open multimodal models — vision, audio, and text under Apache 2.0
Category
Open Source Models
Open Source Models

Reviewer scorecard

Builder
80/100 · ship

MIT license on a 1M context model that beats GPT-5 on coding evals is wild. V4-Flash at 13B active params is particularly practical — you get near-frontier coding performance with inference costs that don't require a mortgage. Ship immediately.

80/100 · ship

Apache 2.0 on a model that beats GPT-class performance at 31B? Ship it immediately. The MoE 26B variant is already running under 16GB VRAM for me with llama.cpp quantization. The unified multimodal arch saves a ton of pipeline complexity.

Skeptic
45/100 · skip

Running 1.6T parameters requires infrastructure most companies don't have, and DeepSeek's API has had reliability issues before. The 'MIT license' is less useful when you're dependent on their API anyway. Wait for quantized local versions to stabilize.

45/100 · skip

Google's benchmark marketing is getting harder to trust — 'beats 600B rivals' is cherry-picked. The audio modality is notably weaker than Gemini 3.1, and fine-tuning the MoE variant requires infrastructure most teams don't have. Real-world performance lags the headline numbers.

Futurist
80/100 · ship

The efficiency breakthrough is the story. If 1M-token context now costs 73% less to serve, that changes the economics of an entire class of applications. DeepSeek is compressing the frontier timeline faster than anyone predicted a year ago.

80/100 · ship

The 100,000-variant Gemmaverse is a real ecosystem flywheel. Every new Gemma release compresses capability curves downward — things that required cloud APIs last year now run on-device. Gemma 4's audio addition makes it the first truly comprehensive local AI.

Creator
80/100 · ship

A million-token context means I can feed an entire brand style guide, all past campaign materials, and a full brief into one call. V4-Flash is fast enough for real-time creative iteration. This is now my go-to for long-context creative workflows.

80/100 · ship

A single model that can read my documents, analyze charts, transcribe my audio notes, and generate code is genuinely transformative for creative production. The Apache license means I can embed it in client deliverables without legal headaches.

Weekly AI Tool Verdicts

Get the next comparison in your inbox

New AI tools ship daily. We compare them before you waste an afternoon.

Bookmarks

Loading bookmarks...

No bookmarks yet

Bookmark tools to save them for later