Channel
@savitrifoundation
On this record: Growth · Engagement · Reactions · Posts · Citations · Cite this entry
743subscribers
-9 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
| Telegram ID | -1002042247376 |
|---|---|
| Type | Channel |
| Username | @savitrifoundation |
| Created | Between 1 November 2023 and 31 May 2024— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 15 August 2026 |
| Measurements held | 3 |
| Confirmed unchanged | 1 time, most recently 15 August 2026 |
| On Telegram | t.me/savitrifoundation |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 15 Aug 2026, 16:43 | 743 | -8 |
| 8 Aug 2026, 04:55 | 751 | -1 |
| 7 Aug 2026, 11:03 | 752 | first reading |
16 posts held, back to 16 February 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 pageof Telegram’s post history, 20 posts per page.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 16 posts for this entry, the most recent from 28 April 2026. An engagement rate over an empty window would be a number about nothing.
56 reactions across 16 posts, in 6 distinct kinds. The most used accounts for 39.3% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 👍 | 22 | 39.3% | |
| 🔥 | 16 | 28.6% | |
| 👏 | 12 | 21.4% | |
| ❤ | 4 | 7.14% | |
| 🎉 | 1 | 1.79% | |
| 💯 | 1 | 1.79% |
No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.
Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.
Coverage. Reactions were read on 16 of the 16 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 56reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 16 most recent posts we hold, published 16 February 2026 to 28 April 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
📢 Ep.02 just dropped on X — "Why From Scratch (FL Reframe)" Two years ago we made one decision that's still the most contested internally: not forking. No Cosmos SDK, no Substrate, no Solana fork. Built consensus, mempool, BFT, RocksDB layer from zero. The thread on X explains the technical reasoning. What's NOT in the thread, and is honest to say here: we questioned that choice every six months for the first year.…
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After 2 years of development we just launched the public testnet of Savitri, a Layer 1 blockchain we built from scratch in Rust. The numbers (V8 test, April 3, 2026): - 25-node cluster on a single laptop (16 GB RAM): 5 masternodes + 20 lightnodes - 125,000+ TPS core engine throughput (Rust crate-level benchmark) - 3,712 TPS sustained on the full network test - 2.1 million TX accepted, 0 lost - Finality P50: 1s | P99…
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The Implementation Specs: • Zero-Copy sigverify: While Solana requires deserializing packets into CPU-friendly structures, Savitri’s src/sigverify/spsc_ring_buffer.rs reads directly from mapped memory, eliminating ns of latency per transaction. • NUMA-Aware Dispatching: Unlike Aptos’s Block-STM, which treats all CPU cores as equal, Savitri’s src/sigverify/numa.rs detects memory affinity. We schedule transaction veri…
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The Architecture Matrix: Why Savitri Outperforms Legacy L1s. Most L1s are built on top of generalized abstractions that ignore the underlying hardware topology. This results in the "Serialization Tax" and non-deterministic execution bottlenecks. Savitri is engineered as a distributed Real-Time OS, moving beyond the limitations of EVM-based or even early Move-based architectures. Today, we break down the fundamental …
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• MEV-Resistance Premium: Quantification of the capital saved by eliminating front-running via the PoU Scheduler. By removing the "hidden MEV tax," Savitri increases the net ROI for liquid providers and end-users. • Scalability Multiplier: Analysis of how the Object-Oriented State (resource isolation) allows for sub-linear fee growth during network congestion. • Validator ROI Projections: Algorithmic forecasting of r…
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From Throughput to Value: The Metrics Behind Savitri’s Economic Architecture. Technical performance (TPS) is irrelevant without a corresponding economic model that converts hardware efficiency into network value. Today, we release our internal Performance-to-Value (P2V) Dashboard, a metric-driven report designed for institutional stakeholders to evaluate the Savitri L1 based on deterministic code rather than market …
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The Implementation Specs: • Property-Based Testing: We utilize proptest to generate thousands of randomized transaction batches, ensuring our Fair Scheduling weights remain consistent under extreme throughput fluctuations. • Fuzzing the Consensus: Continuous fuzzing of the src/consensus/batching.rs module to detect potential deadlocks or invalid state transitions before they reach the Testnet. Coverage by Module: …
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Technical Quality: 80.4% Test Coverage. Why Savitri is Production-Ready. Code quality in a distributed L1 isn't a "nice-to-have" it's the difference between a resilient network and a catastrophic liveness failure. While many projects prioritize feature velocity over stability, we have maintained a strict 80%+ test coverage across our core modules. Using cargo-tarpaulin, we have verified that every critical path from…
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• Memory Efficiency: -40% RAM overhead compared to standard Rust-based L1s. By utilizing SPSC Ring Buffers and eliminating runtime deserialization, we kept the heap footprint minimal and stable. • Throughput Stability: The Fair Scheduling algorithm prevented MEV-driven congestion, maintaining a deterministic transaction flow regardless of individual node "selfishness." The Engineering Reality: The data proves that …
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Testnet Verdict: 21 Days, 0 Crashes. Savitri is Production-Ready. After 504 hours of continuous high-load operation, the Savitri Testnet has concluded its initial phase. While legacy L1s often struggle with state bloat and non-deterministic liveness failures under stress, Savitri’s architecture built on Zero-Copy memory and NUMA-aware scheduling maintained 100% uptime with zero kernel panics or consensus forks. We …
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Our Implementation in src/common/cache_align.rs: • Explicit Alignment: We utilize #[repr(align(64))] on high-contention structs like PoUTracker and ShardMetadata. This ensures each struct occupies its own cache line, preventing cross-core interference. • Padding Primitives: For critical atomics, we insert explicit padding to ensure that hot counters do not overlap within the L1 cache of adjacent physical cores. • Ca…
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Cache-Line Optimization: Preventing Performance Degradation via #[repr(align(64))]. In high-concurrency environments, data locality isn't enough; you must account for how the CPU manages its L1/L2 caches. Savitri optimizes its core consensus structs to prevent False Sharing a hardware-level phenomenon where multiple cores fight over the same 64-byte cache line, leading to massive performance regressions. The implem…
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Showing the 12 most recent of 16 posts we hold for @savitrifoundation. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.
Citation-graph rank — 958,790 of 1,481,306entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.
Named by 1 registered channel — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.
Named by
Channels on the register whose posts name this channel's handle.
A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.
A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 15 August 2026 — this entry's latest reading, not the date you are reading this.
“Savitri|Community Channel” (@savitrifoundation), 743 subscribers as measured 15 August 2026. Telegram Register, tgregister.com/channel/savitrifoundation.
Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.