Telegram RegisterThe public register of Telegram

Channel

Vibe Coding Daily

@gptfresh

On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Telegram's recommendations · Cite this entry

3,835subscribers

+14 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of 3,162–10,000.

Register entry

Telegram ID-1002039314171
TypeChannel
Username@gptfresh
CreatedBetween 1 November 2023 and 31 May 2024— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live13 August 2026
Measurements held4
Confirmed unchanged1 time, most recently 13 August 2026
On Telegramt.me/gptfresh

Growth

3,8213,8353,8287 August 2026 — 3,821 subscribers7 August 2026 — 3,821 subscribers10 August 2026 — 3,825 subscribers13 August 2026 — 3,835 subscribers7 August 202613 August 2026
4 measurements spanning 6 days, net +14. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 3,819–3,837 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
13 Aug 2026, 03:173,835+10
10 Aug 2026, 08:173,825+4
7 Aug 2026, 13:033,821no change
7 Aug 2026, 12:493,821first reading

Engagement

13 posts held, back to 4 August 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 3 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
3.78%
avg views ÷ 3,835 subscribers
Avg views / post
145
13 posts measured
Reaction rate
0.626%
reactions ÷ views · ER floor
Posts in window
13
of 13 held

ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.

ER is defined industry-wide as (forwards + reactions + comments) ÷ views— note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate. It is computed over the 4 of 13 measured posts that carry a reaction reading, and over those same posts' views.

What these figures were computed from
WindowRolling 30 days · latest post in window 7 August 2026
Posts held13 (4 August 20267 August 2026)
Views total1,886
Reactions total4
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken8 Aug 2026, 06:11 UTC

Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.

Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.

Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.

What this channel posts

Video runtime
2m 45s
Average length
18s

Measured directly from 9 videos with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no mark.

Reaction mix

4 reactions across 4 posts, in 4 distinct kinds. The most used accounts for 25.0% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
125.0%
👍125.0%
👏125.0%
😁125.0%

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 4 of the 13 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 4reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 13 most recent posts we hold, published 4 August 2026 to 7 August 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.

Recent posts

7 Aug 2026, 04:21 UTC131 viewsread 8 August 2026
Video

OpenAI has significantly updated ChatGPT: Free and Go users can now use GPT-5.6 Luna without limits in text chats — a model whose capabilities are already more than enough for most everyday tasks. In addition, the free tier now features a Think button, which allows the model to spend more time reasoning when answering complex questions. Plus and Pro users haven't been left without updates either. All new chats now

7 Aug 2026, 03:29 UTC116 viewsread 8 August 2026
Photo

Prime Intellect has launched Prime Agent, a framework designed to transform long, autonomous AI sessions into structured programming tasks. The system utilizes a persistent IPython kernel, allowing the model to: — Programmatically search its history and call tools. — Deploy persistent subagents. — Manage state outside the active context. Key Pillars: • Programmatic tool calling via RLM. • Persistent operation of mu

7 Aug 2026, 02:59 UTC101 viewsread 8 August 2026
Photo

It looks like OpenAI is working on a feature that will let you buy a reset of rate limits for Codex. This is indicated by findings in the public configuration of the payment page and the resources of the ChatGPT web app. Now it's clear why Tibo doesn't reset our limits. 🙂

7 Aug 2026, 02:28 UTC100 views1 reactionsread 8 August 2026
Photo

Bad news: the DeepSeek API page states that the cost of using the DeepSeek API will increase significantly in the near future. Now's the perfect time to squeeze the most out of Flash before it gets pricier. 👀

👍1

7 Aug 2026, 01:58 UTC106 viewsread 8 August 2026
Photo

COMEBACK: Meta has released Muse Spark 1.2 and its own IDE, Muse Code, in beta. 🍗 This is a fast follow-up to Muse Spark 1.1, which came out just a few weeks ago. The new version places greater focus on coding tasks and features a new harness. In tests, the model showed a notable improvement in Terminal Bench, DeepSWE, and internal benchmarks. In agentic scenarios, results improved on GDPVal and MCP Atlas. On Deep

5 Aug 2026, 06:28 UTC190 viewsread 8 August 2026
Photo

✔️ Liquid AI Launches On-Device Agent Model Liquid AI has released LFM2.5-2.6B, a compact 2.6B parameter model designed for local, on-device execution without cloud APIs. It excels at planning, tool calling, and multi-step tasks. Key Technical Specs: * Training: 34 trillion tokens, 128k vocabulary, 128k context window. * Methodology: Expert models (math, code, tools) were merged via on-policy distillation and f

4 Aug 2026, 16:37 UTC231 views1 reactionsread 8 August 2026
Photo

📌 Tencent’s AI agent solves a 50-year-old math mystery Tencent’s AI research agent, Hyra (based on the Hy3 model), has cracked a long-standing problem in combinatorial mathematics. The challenge involved determining the optimal upper bound for the size of a set of integer sums compared to its set of differences. While mathematicians knew the exponent did not exceed two, they could not prove if this bound was optima

👏1

4 Aug 2026, 15:37 UTC161 views1 reactionsread 8 August 2026
Video

Qwen 3.8 Max is truly impressive. The Qwen 3.8 Max, Claude Opus 5, Kimi K3, and GPT-5.6 Sol models were given the same photo of the sky and asked to draw the silhouette of an animal based on the shape of the clouds. In this test, Qwen 3.8 Max looked just as good as the other models. GPT, though, seems to have spotted something else entirely in the clouds. 😄

😁1

4 Aug 2026, 15:07 UTC149 viewsread 8 August 2026
Video

✔️ Andrej Karpathy proposed a new benchmark for AI He used the Opus 5 model to turn a paragraph from "The Lord of the Rings" into 5,500 lines of code for the Three.js browser graphics library. Generating the scene took about 2 hours, required a million tokens, and cost around $10. The sound was generated using ElevenLabs. According to Karpathy, familiar spatial reasoning tests — like drawing a pelican riding a bic

4 Aug 2026, 14:37 UTC141 viewsread 8 August 2026
Video

⚡️ Qwen 3.8 Max beat Fable 5 in a tough 3D physics generation test and cost almost 7 times less The Atomic Chat team gave both models the same task: create three standalone HTML files with interactive scenes. In the first, marbles climb a wheel and complete a loop. In the second, a car assembly line operates. In the third, a sawmill turns logs into boards. The model had to preserve object states, calculate collisi

4 Aug 2026, 14:07 UTC140 viewsread 8 August 2026
Video

A new tool for analyzing AI agent behavior with Monium Traces has appeared in the Yandex AI Studio interface. Traces are a key signal for observability in agent systems, allowing you to see the agent's entire execution path and understand why it made a particular decision. Unlike conventional applications, classic monitoring is no longer enough for AI agents. Even if the infrastructure runs without errors, an agent

Showing the 12 most recent of 13 posts we hold for @gptfresh. 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.

Appears in Telegram’s recommendations for other channels

The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.

Hi, AI • Tech News
@hiaimediaen · 568,891
Telegram ranks this channel #20 of 83 here — alongside 82 others — read 9 August 2026

This channel appears in 1 seed channel's Telegram-generated recommendation list in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.

Cite this entry

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 13 August 2026 — this entry's latest reading, not the date you are reading this.

“Vibe Coding Daily” (@gptfresh), 3,835 subscribers as measured 13 August 2026. Telegram Register, tgregister.com/channel/gptfresh.

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.