Google Gemma 4 26B A4B Instruct
gemma-4-26b-a4bgemma-4-26b-a4b-itgoogle-gemma-4-26b-a4b-instructgoogle-gemma-4-26b-a4b-it- 🧠 Mixture-of-Experts: 26B total parameters, only ~4B active per token.
- ⚡ Google reports it runs almost as fast as a 4B dense model.
- 📏 256K-token context window across the larger Gemma 4 models.
- 👁️ Accepts text, image, and video input.
- 🔧 Native function calling among its listed capabilities.
- 🧠 Configurable thinking modes for step-by-step reasoning.
- 🌐 Multilingual support across 140+ languages.
- 🔒 Open-weight, instruction-tuned release under Apache 2.0.
Google is an American multinational technology corporation and one of the world's most valuable brands. A subsidiary of parent company Alphabet Inc., Google operates across search, cloud computing, consumer electronics, and artificial intelligence. Its DeepMind and Google…
Explore 28 more models by Google →Gemma 4 26B A4B Instruct is an open-weight, instruction-tuned model from Google DeepMind, released in April 2026 as part of the Gemma 4 family. Unlike its dense siblings, it uses a Mixture-of-Experts design: of its roughly 26 billion total parameters, only about 4 billion activate per token, so all weights load into memory while inference stays fast. Google describes it as running almost as quickly as a 4B dense model.
Compared to same-family predecessors, this model advances on several fronts. Where the earlier Google Gemma 3 27B Instruct used a dense architecture, Gemma 4 introduces MoE variants alongside dense ones, plus built-in configurable reasoning modes and video input. Its context window reaches 256K tokens, and multilingual coverage spans over 140 languages.
Within Gemma 4 itself, the 26B A4B is positioned as the throughput-optimized counterpart to the dense Google Gemma 4 31B Instruct. Sparse activation reduces compute per token relative to the dense 31B while aiming for comparable quality.
Both target consumer GPUs and workstations. It supports text, image, and video input natively, with audio featured on the smaller family members rather than this size. Its listed capabilities include reasoning, vision, function calling, and web search, offered as an open-weight, multilingual option.
This About section is AI-generated from public sources via VeniceStats + Venice inference, with no human editing. It may contain inaccuracies.
Daily usage · Google Gemma 4 26B A4B Instruct · Organic sellers
Top sellers · Google Gemma 4 26B A4B Instruct · Organic
- OpenCheap73.0%
- Fire Ant 🔥🐜8.3%
- Venice.ai Proxy7.9%
- Unified Rack · DeepSeek 240 tok/s4.0%
- uomi.ai3.6%
- Linkrra Synap1.9%
- Others1.3%
| Seller | Health | Rep↓ | Sales | Tokens | Routing | Input $/M | Cached $/M | Output $/M | Save |
|---|---|---|---|---|---|---|---|---|---|
| Super Seeder 0xd19f…41f3 | healthy | 89.22 | $0.00 | 191.61k | #1 | $0.00 | $0.00 | $0.00 | −100% |
| Venice.ai Proxy 0x1f22…18c9 | healthy | 86.84 | $0.25 | 1.75M | #2 | $0.0715 | $0.0275 | $0.22 | −11% |
| OpenCheap 0x0ee1…6c41 | — | 12.43 | $2.29 | 30.67M | gated | $0.0011 | $0.0007 | $0.0014 | −99% |
| surplus-hive 0x6145…5c58 | — | 0.00 | — | — | gated | $0.316 | $0.316 | $0.9722 | — |
| Fire Ant 🔥🐜 0xbe05…bc5d | — | 0.00 | $0.26 | 2.12M | gated | $0.117 | $0.045 | $0.36 | — |
| uomi.ai 0x87df…48e3 | — | 0.00 | $0.11 | 905.34k | gated | $0.10 | $0.10not advertised | $0.389 | — |
| Swift Ant 0xe49f…a3a9 | — | 0.00 | $0.01 | 325.35k | gated | $0.0747 | $0.0747 | $0.1928 | −7% |
| antseed-neon-puma-944e 0x6650…944e | — | 0.00 | — | — | gated | $0.0554 | $0.0554not advertised | $0.1705 | −31% |
| Linkrra Synap 0xd7cf…71da | — | 0.00 | $0.06 | 942.50k | gated | $0.043 | $0.043not advertised | $0.23 | −46% |
| Leftermute 0x388b…5389 | — | 0.00 | — | — | gated | $0.0348 | $0.0348not advertised | $0.0929 | −56% |
| surplus-hive 0xe177…e91c | — | 0.00 | $0.00 | 20.32k | gated | $0.0181 | $0.0181 | $0.0543 | −77% |
| Joi Gateway 0x8a90…7007 | — | 0.00 | — | — | gated | $0.0022 | $0.0022 | $0.0073 | −97% |
"Best price" and the seller table are live Antseed catalog data (advertised $/1M tokens — or $ per generated image for unit-billed image models — not settled amounts). Reputation = buyer trust score (0-100, the Antseed SDK's own formula). "Routing" = the SDK's default buyer routing (what the VPR desktop app ships with): a trust ≥ 60 gate on the effective reputation, then cheapest-first among routable sellers; live failover state (per-peer cooldowns) is buyer-side runtime and not included. Model knowledge (TLDR, provider, About) via the VeniceStats enrichment layer. Advertised catalog, not the model used in any specific purchase. "Usage on Antseed" counts only settlements whose buyers share the per-model split on-chain (metadata v2/v3, opt-in), so every usage figure is a lower bound.