After Repositioning Itself as an AI Layer 1, Where Does NEAR Actually Stand in 2026?

In early 2024 NEAR Protocol founder Illia publicly recast NEAR as the user owned AI blockchain, pushing on chain AI agents, data verifiability and private inference. Reactions split, some thought it was the next narrative grab, others called it a forced pivot for a chain without direction. Two years later, where does NEAR actually stand after the AI pivot? This piece avoids hype and snark, and lines up Nightshade performance, AI framework progress and ecosystem project counts in order.

NEAR’s Core Engineering Footprint

To judge the AI pivot, start with the engineering base. As of May 2026:

• Nightshade 2.0 sharding, scaled from 4 shards to 6, theoretical 100k TPS, mainnet peak measured at 18k TPS.
• Chain abstraction, NEAR accounts natively control Ethereum and Bitcoin addresses through MPC signatures. 1.8 million users in 2026.
• NEAR AI framework, released in 2024, core components open sourced in 2025, delivering model hosting, on chain inference and data verifiability.
• New accounts per second, steady at 3 to 5, far above most L1s.

Engineering quality at NEAR is underrated. Nightshade hit no major outages from 2024 to 2026, model student behavior compared to Solana’s bad years. But strong engineering does not equal strong narrative, which is exactly NEAR’s awkward spot.

What On Chain AI Actually Means in Practice

The phrase AI L1 is overused in 2026. What NEAR actually does breaks into four buckets:

One, model hosting and paid inference

• Developers deploy open source models to the NEAR AI platform, users pay inference fees in NEAR.
• As of May 2026, monthly inference calls around 140 million, hosted models number 320.
• Pricing roughly 0.05 USD per 1000 calls, clearly cheaper than centralized APIs.

Two, on chain AI agent actions

• An SDK lets AI agents originate on chain transactions, using chain abstraction to call Ethereum or Bitcoin.
• This is where NEAR differs from Bittensor, which emphasizes training. NEAR emphasizes execution.

Three, data verifiability

• Users park data on NEAR DA, inference results come with verifiable signatures.
• More realistic than so called zero knowledge ML. It does not prove computation correctness, but it proves data provenance.

Four, private inference (TEE experiment)

• Partnership with Phala and Marlin on Trusted Execution Environment, in staged rollout in 2026.
• Target use cases include medical and financial inference where raw data cannot leak.

Of the four, one and two have real traffic, three has live use cases, four is still experimental. Overall NEAR is not just shouting AI L1, it built a real infrastructure stack, the market just refused to price it in.

How NEAR AI Compares to Other AI L1s

Side by side with the main AI L1 contenders:

Two things stand out:

• NEAR’s inference volume leads the AI L1 pack, but token price does not reflect it.
• The whole AI L1 lane is down 2024 to 2026, not just NEAR.

Token down does not equal engineering failure. The combo of active chain plus weak token is common across L1s in 2026, same pattern as Cosmos covered above. Cross reference our AI crypto tokens 2026 overview and AI RWA projects 2025 to feel the broader sentiment.

Was the AI Pivot Right or Wrong

An honest look at both sides.

For the pivot

• The pure high TPS narrative was exhausted by 2024. Competing on TPS with Solana was a dead end.
• On chain AI was a genuine hot topic across 2024 to 2026, catching the narrative at least keeps industry attention alive.
• The NEAR founding team has machine learning background, so the move was not strategically forced.

Against

• The AI L1 label cost NEAR its slot in the general purpose L1 comparison with ETH and Solana. Neither a general L1 nor a pure AI chain.
• 140 million monthly inferences sounds large, but OpenAI handles 10 billion API calls per day, so on chain is still a niche play.
• Token value capture is weak, inference fees are low, burn is small.

My take: the pivot is smart, but the narrative and product need more time to prove out. This is not a few months job.

A Few Undervalued NEAR Ecosystem Projects

If you only watch the token and ignore the chain, you miss some genuinely interesting projects:

• HOT Wallet, a do everything wallet built on NEAR chain abstraction, 11 million active users in 2026.
• Mintbase, NEAR’s NFT mint tool, cumulative mints over 4.8 million.
• NEAR Tasks, users label AI training data for rewards, 350k monthly contributors.
• Aurora, the EVM compatibility layer on NEAR, still running but cooler than 2022.

These prove the ecosystem did not die, just shifted narrative center from general L1 to AI. Whether the shift succeeds plays out across 2027 and 2028.

A Framework for Holding NEAR

If you already hold NEAR or are considering buying, which indicators should you track in 2026?

1. Inference growth rate, three straight months above 10 percent month over month means the narrative is delivering.
2. Chain abstraction users, crossing 3 million is a structural bullish signal.
3. Major models on NEAR AI, watch for new models beyond Llama and Mistral joining steadily.
4. TEE inference reaching mainnet, that would be the qualitative shift, still testnet today.

Same logic as the differentiated L1 thesis in our notable L1s beyond ETH and Solana, key is whether the chain found its own distinct demand, not whether it tracks the broad market.

What NEAR’s Pivot Teaches the Industry

Step out of NEAR for a second. Its pivot trajectory matters for every late stage L1:

• One, general L1 has run out of differentiation space. Without a performance jump of an order of magnitude, squeezing between ETH and Solana is near impossible.
• Two, vertical narratives are the survival channel for late stage L1s. NEAR picked AI, Avalanche subnets went games and enterprise, both work better than fighting head on as general L1s.
• Three, token price drag during a pivot is inevitable. That is the normal cost of a narrative reset, what matters is engineering delivery speed.

NEAR’s biggest contribution over these two years is not how much money it made, but mapping a path other late stage L1s can follow. If NEAR actually pulls a 2027 AI driven revival, the case becomes industry curriculum. If it fails, it at least proves AI does not rescue every L1, both outcomes teach the industry something.