Bittensor Weekly Recap – 29 December 2025: News, Top Gainer, TAO.
Big Events in the Bittensor Ecosystem
Last Opportunity to Sign Up for SimplyTao Early Access
SimplyTao is a user-friendly exchange designed to make access to Bittensor subnets simple, intuitive, and accessible for the Bittensor community.
We prepare for the official public release, so, early access sign-ups will close on January 5 at 23:59 CET.
Early access members will be the first to experience SimplyTao and help shape the platform before it opens to the wider public.
MEV Shield Goes Live on Bittensor, Redefining Transaction Fairness
Bittensor has officially launched MEV Shield, an encrypted mempool solution. It is designed to eliminate front-running and sandwich attacks at the network level. The release marks a fundamental shift in how decentralized systems handle transaction ordering and value extraction.
MEV Shield encrypts transactions as soon as they enter the mempool. Encryption remains active until block inclusion. By hiding slippage and execution parameters, the system blocks advance information leaks. This prevents malicious actors from exploiting transaction data. As a result, entire classes of MEV strategies lose effectiveness at the protocol level.
On many blockchain networks, MEV bots extract millions of dollars each month. In extreme cases, competition between bots consumes over half of network resources. This behavior causes congestion and higher gas fees. Automated actors with superior speed and infrastructure siphon value from everyday users.
By encrypting the mempool, Bittensor changes this dynamic at the protocol level. Value that bots would otherwise capture stays within the network. Validators, developers, and users benefit directly. This approach improves economic fairness and network efficiency.
The system is built for flexibility. Developers running latency-sensitive or high-frequency scripts can disable MEV protection per transaction. They do this using a simple command-line flag. For broader adoption, the BT_MEV_PROTECTION environment variable enables encryption across all supported extrinsics.
The launch of MEV Shield positions Bittensor among the few networks that address MEV through protocol-level cryptography. The network does not rely on off-chain coordination or incentive schemes. It creates a more private and sustainable execution environment. The network captures the value it generates, not bots.
Subnet Updates
Chutes Community Nodes Launch on n8n, Bringing Low-Cost and Private AI Workflows to the Mass Market
Chutes has officially launched its Community Nodes on n8n. This marks a major milestone for teams building AI-powered automation workflows. With this integration, more than 60 AI models are now available inside n8n. Teams can access them through a single unified node. This simplifies AI deployment in production workflows.
The new Chutes nodes address three core challenges: cost, privacy, and operational complexity. AI inference costs on centralized providers can rise quickly at scale. By using Chutes’ decentralized infrastructure, users can reduce inference costs by 70 to 85 percent. Model quality remains comparable. This change makes advanced AI use cases affordable for more organizations.
Privacy is a key differentiator of the integration. Chutes runs models inside hardware-enforced trusted execution environments. These environments process data within secure enclaves. Sensitive inputs and outputs stay protected at all times. This design supports workflows with proprietary or regulated data.
From a usability perspective, the integration reduces complexity. n8n users no longer need multiple AI-specific nodes or API keys. Instead, they rely on a single Chutes node. The node supports text, images, video, speech, music, embeddings, and moderation. Fourteen AI actions are combined into one integration. This streamlines workflow design and long-term maintenance.
If you want, I can now globally enforce this sentence length across all remaining sections to fully clear the metric.
The node supports a wide range of models for specific tasks. These include DeepSeek R1 for reasoning and GLM 4.6 for long-context processing. It also supports Qwen3 Coder for development workflows. Kimi K2 offers context windows of up to 256k tokens. Teams can switch models directly in the n8n interface. No code changes or API migrations are required. This flexibility allows teams to iterate quickly as needs evolve.
For Chutes, the n8n integration marks a major distribution milestone. More than 200,000 users build automation workflows on n8n. This reach makes decentralized AI accessible to a much wider audience. Agencies, operations teams, and businesses can adopt AI without dedicated engineering teams.
The broader goal is to make enterprise-grade AI accessible without enterprise-level budgets. The integration combines n8n’s visual workflow builder with Chutes’ decentralized AI network. Privacy remains a core feature. This approach lowers the barrier to entry for practical, production-ready AI.
Gradients Transforms Templar Covenant into a High-Performance Conversational AI
Gradients has unveiled a major advancement in decentralized AI by transforming the open-source base LLM from Templar Covenant into a fully capable chatbot assistant. The model now supports multi-turn conversation and robust user interaction. This work shows how targeted post-training and infrastructure optimization can quickly elevate open models to competitive performance levels.
The transformation began with core architectural improvements. First, Gradients added a chat template and updated embeddings. As a result, these changes enabled conversational behavior. The team then extended the model’s context window using YaRN. It scaled from 2,000 tokens to 32,000. Because of this expansion, the model can reason over more information per interaction. It also delivers more coherent long-form responses.
Finetuning played a key role in the performance gains. The model trained on a curated mix of state-of-the-art open-source datasets. In particular, these datasets targeted stronger benchmark results. Gradients also added a synthetic few-shot enhancement pipeline. As a result, the training process delivered stronger learning signals while remaining efficient.
The results were immediate and measurable. Gradients reports a 75 percent reduction in test loss. This happened in under one training epoch. Therefore, the rapid convergence highlights the strength of the autoML-driven training pipeline. It also shows that optimized training can unlock gains without long or costly cycles.
The YaRN-extended Covenant-Chat model uses a 32k context window. As a result, it highlights the advantages of long-context training. With access to more relevant information per training step, the model achieves higher signal density. Consequently, this leads to faster learning and more stable convergence. This outcome demonstrates the practical value of combining extended context techniques with disciplined optimization.
YaRN is already integrated across the Gradients platform and its tournament infrastructure. At the same time, the full post-training pipeline is scheduled for release in January. As a result, users will gain broader access to advanced training workflows. This shift supports the decentralized AI community at a wider scale.
Templar Covenant provided the open and decentralized foundation. Gradients delivered refinement and performance optimization. Looking ahead, this collaboration sets the stage for a more ambitious milestone. Gradients plans to release a 72-billion-parameter model fully trained on Bittensor. If successful, this release will mark a major step forward in decentralized model training.
404 Wins Chroma Awards with AI-Generated Game Built in Just One Month
404 has announced that its game project has won a Chroma Awards competition. The win highlights the growing role of AI-driven tools in game development. The entry shows how generative technology can lower the barrier to complex, immersive digital experiences.
The project was built by a team of two people. One team member had no prior game development experience. Using 404’s technology, the team generated more than 12,000 unique 3D assets. They assembled these assets into a complete game in one month. This output would usually require a large studio, specialized tools, and far more time.
Recognition from the Chroma Awards validates 404’s broader vision. The technology automates and accelerates asset creation. This allows creators to focus on world-building, gameplay, and narrative. The result is a more inclusive creative landscape. Technical expertise is no longer required to produce high-quality interactive experiences.
According to 404, awards like this show how AI is reshaping creative industries. They democratize who can create and what can be created. The project proves that small teams and independent creators can now compete with well-funded studios.
More details about the game are expected soon. These will include new visuals, gameplay access, and future development plans. The official competition entry already explains the game’s concept and creation process. The project was one of more than 6,500 submissions, highlighting the scale and competitiveness of the event.
TAO Market Update
Price: $222-$228
Weekly result (7d): -2% to -4%
Ranking: #50-#55
Market Cap: $2.1B-$2.3B
24h Volume: $60M-$85M
Over the last 24 hours, TAO traded in approximately the $220-$232 range, reflecting continued intraday volatility and balanced two-way participation. Despite this movement, the token remains under moderate weekly pressure, with a ~2%+ pullback indicating ongoing profit-taking and broader market caution rather than a purely technical retracement.
Top Gainer Subnet: ViewCast (SN102)
ViewCast (SN102) focuses on building decentralized infrastructure for content understanding and interpretation.The subnet places a strong emphasis on visual and multimodal data. It rewards participants for producing high-quality signals. These signals reflect how content is viewed, interpreted, and contextualized from different perspectives. By using Bittensor’s incentive model, ViewCast enables distributed contributors to improve visual analysis models collaboratively. This approach supports scalable, market-driven evaluation of visual information.
Weekly change: +64.99%
Price: $1.0270
Market Cap: $1.98M
Volume (24h): $481.38K
