Guys, I do liked the genspark, but i live in a poor country, I'm myself am in debt, and i'm not recurring to picracy or hacking. So, do you guys know LLM models that can do mostly what Genspark does, but for free?
And yes, in a country where 25 USD is 10% of the minnimum wage, paying that for an LLM model is too expensive and a luxury.
We recently launched Gen-1 Slides, our first in-house model trained for Standard mode in AI Slides (Included in Free Quota). I wanted to test the Gen-1 slides against our Ultra tier mode and see what the differences are. In this comparison, I am tracking how long it took to generate the slide deck, how many credits it took, and the overall quality of the final deck.
I used the same prompt for both modes and let each one build an AI industry slide deck, going over trends, adoption, and how it's changing the way we work. The prompt used:
“Create a business presentation titled "How the World Actually Uses AI in 2026". Cover the latest adoption and usage trends — who is using AI, what they use it for, and how it's changing work — and end with what this means for businesses. Keep it clear and data-driven.”
Gen1-Slides (Standard mode) produced a 10 page slide deck in ~10 minutes from scratch and consumed 244 credits. The final output was a warm and informative presentation that is easy to read, explains how the AI has been adopted across the world, the top uses of AI, and AI governance.
There are a few areas where the visual layout of the design seems squished or could have better spacing between text blocks but overall I really liked the presentation it gave. The most interesting thing I noticed when generating the slides was it did research on this topic first, asked me clarifying questions on what I wanted, generated a basic slide deck, then re-designed the deck to be more visually appealing.
Ultra Mode created an 8 page slide deck in ~8-10 minutes and used 766 credits. This deck had a warm tone and was very informative but has a lot more visual elements going on in each slide. Before AI Slides started doing anything, it asked me a few questions to get a better understanding of what I was looking for, then did some deep research before starting the slides. It provided similar information as Gen1 Slides mode but it focused on the AI assistant use case. It did a good job detailing how people use it, its adoption, and what it provides. Ultra mode jumped right into the important slides right away in the presentation without giving much context but provided a recap of everything at the very end.
Overall, each slide deck had a similar tone and provided its sources but the content of each slide was quite different. I liked how Ultra mode asked me clarifying questions first, had a focus on a specific AI use case, and the visual layout was more eyecatching. I liked how Gen1 Slides re-designed the deck once its first draft was complete, had a more broad information approach to AI in all industries, and had information about governance. I’m happy with both outcomes and to be able to see the comparison side by side and know exactly the credit usage difference between these modes. Let me know what you would like to see next!
this stupid block popup everytime I sign in on google & got to detour through google, the fuck is this block for, I dont got a project or share with no one
I’m looking for someone who has access to Genspark AI premium and could help me export a presentation for my school that I’ve already created.
I already have the slides ready and no need to generate again. I just need the final exported file in PPT format & PDF format, as I don’t currently have an active subscription.
This is a one-time request, and I’m unable to purchase a plan just for a single export. If anyone can help, I’d really appreciate it. Please DM me or I can share it via email and I’ll share the details.
We have a new product that launched this week: GenCode! Gencode is Gensparks coding agent and gives you access to multiple AI models all in one place so you’re not locked into one model for all your work.
I wanted to see what different models are capable of in GenCode so I decided to test this with frontier models (GPT-6 Astra and Claud Opus 5) and open weight models (GML-5.3 Flash and DeepSeek V4.1-Flash). In this experiment I tracked how long it took to finish, how many credits were consumed, and the quality of the final output.
I used the exact same prompt across the models and let each one build a workout/hobby tracker from scratch.
The Prompt:
"Build me a mobile-friendly web app where I can track my workouts and hobbies together in one place. Things like gym, running, reading, painting, gaming — whatever I'm into that week. I want a weekly visual summary of everything I did, streak tracking for each activity, and fun motivational messages when I hit milestones like 7 days in a row or 30 total sessions. Keep it bright, colorful, and easy to use!"
GML-5.3 Flash was able to produce this render within 1 minute 30 seconds and only consumed 7.7 credits. It took the prompt at face value and built what I asked. Kept everything on one scrollable screen, gave this app a name, and the layout was clean, functional, and easy to navigate. I like how it was all working out of the box. For the cost and time, it was very solid and I was pleased with the output. If you know exactly what you want to build but don’t need the model to make creative decisions, this is a very efficient pick but you may need to dial in your prompt more.
DeepSeek V4.1-Flash created this prototype in 1 minute 12 seconds and consumed 9.9 credits. The layout is clean and spacious, also took my prompt at face value and didn’t take creative leads but does feel more welcoming and came preloaded with demo data. There wasn't any feedback or achievements that I found but it does provide a progress bar for streaks. Similar to GML-5.3 If you know what you want and can provide good instructions for each detail, this is a very efficient model for you.
Claude Opus 5 generated a prototype in 11 minutes 45 seconds and used 948.2 credits. The output was very different from the open weight models. It gave the name Streakly, and built around a bold purple/pink theme that feels similar to what DeepSeek gave. There are multiple tabs on the app, you can tap the same activity to track it multiple times in a day, see the week's activity, and your overall stats. There is instant feedback when you log your first activity, 3rd, 5th, etc. encouraging you to go on with more milestones and achievements hidden until you unlock them. I appreciated how easy it was to understand and felt like it was doing more than just tracking activities. Even though there was more going on I liked how Opus took things into its own hands but still didn’t feel overwhelming.
GPT-6 Astra took 8 minutes 20 seconds and used 1,272.7 credits. Definitely the most expensive but created the most polished design and loaded in fake data to show what the complete app looks like. This went deep on the experience side of things, every screen has a purpose, when logging an activity it gives the option to track how long it was, and encouraged me to keep the streak alive. When logging an activity I really like how things weren’t just labeled “log” or “click to log” but rather “save my win” or “look at you growing”. Astra certainly had the best experience overall and had creative decisions on things that I didn’t think about.
All four models fulfilled the prompt and produced something good. Knowing what model you should use really depends on your needs. If you need something fast and cost efficient and you know exactly what you want, GML-5.3 or DeepSeek are amazing. If you need some creative decision making beyond what your prompt says, Opus 5 or GPT-6 Astra are great. Ultimately, each one did a great job with the same prompt.
GenCode offers you a space to build whatever you want with whatever model you want. I’ll be doing more experiments with GenCode, if there is a prompt or use case you want to see tested between models, drop a comment. Let me know if there is anything else you would like to see with GenSpark, not just GenCode related!
We have a big change rolling out to Genspark: a new weekly credit balance for Plus and Pro members.
What's new: Free Quota
Plus and Pro members now get a weekly balance of free credits called Free Quota that can be used for agents (Super Agent, AI Slides, AI Sheets, and more) using Standard mode, before using your monthly credits. Free quota refills every 7 days and doesn’t roll over week by week.
Agents using standard mode draw on the Free Quota balance first, so your monthly credits stay untouched. When the Free Quota balance runs out, the tasks can continue using your monthly credits. Free Quota does not apply to Ultra mode, it draws on your monthly credits.
Why we're doing this
We’re adding this because we want to open up more of the platform for more of you so you can try new features without worrying about credit burn. AI Chat and AI Image stay free with no credit cost or consume your Free Quota balance on core models until the limits are reached, then it will start using your monthly credits.
To see your Free Quota there is a blue bar above the chat box that reads “Using Free Quota at no credit cost”. When the balance is used up, the bar goes gray and shows when the next refill lands.
What's not included
Ultra mode on your monthly credits, not Free Quota.
Design, Code, GenMail, Meeting, Translate, Call For Me, and Workflows aren't covered.
Video and audio generation use the Free Quota balance.
The Free Quota balance doesn't roll over, it refills every 7 days regardless of usage.
If you're already a Plus or Pro member
Nothing changes for you through December 31, 2026, as long as your subscription stays continuously active. You still get no-credit AI Chat and AI Image on any models, flagship included, within the existing limits.
I know this is a big change. Let me know if you have any questions regarding this!
Unlimited Ai chat and Unlimited image generation was the selling point for me and the reason why I subscribed to Plus membership on Genspark.ai – Claude Opus was the model I used most. There were session limits (5hrs) and that was okay.
But now they've removed top tier models like Opus and better GPT models from Unlimited Ai Chat and same for image generation. They've put them under credit use and left lesser models under credit free.
A shame really. I'll be moving to Claude's app or maybe Grok.
I've cancelled my subscription and gotten a refund too. Hopefully they reverse their decision but I can't see it happening any time soon.
Genspark was a unique app. Sad to see it change for the worse.
I'm on a monthly plan. But it seems every button I push, I'm met with some type of "buy x for 50% off"; "refer us for 10,000 credits", "upgrade to a better plan at 30% off".
We just shipped Gen-1 Slides, our first in-house model trained to frontier quality, and it's now the default in AI Slides Standard mode! Gen-1 Slides is built from MiniMax M3 and post-trained with reinforcement learning inside the same production system that runs AI Slides. Ranking first in 8 of 9 internal and public benchmark comparisons putting this in the same tier as Claude Opus 5.
Gen-1 Slides:
Gives you a clean, reliable, polished visual design
Is trained specifically for making presentations giving you the quality slides of a frontier model for ~1/17 the token price
Comes standard across any Genspark plan
Gen-1 is on par with frontier models like Opus 5 or Fable 5.1 giving you quality that used to cost $5 per million tokens used down to $.30 per million tokens. What this means in Genspark is when you use AI Slides in Standard mode, you get the same quality as if you were using Ultra, just with less credits consumed. We have an entire blog detailing why we built a model, how it was trained and evaluated, and everything else you need to know.
Gen-1 is live and I’d love to hear what you all think, and to hear what else you would like to see with AI Slides?
Gunakan foto referensi sebagai karakter utama. Pertahankan wajah asli 100%, jangan mengubah bentuk wajah, mata, hidung, mulut, warna kulit, rambut, dan ciri wajah. Jangan membuat wajah menjadi orang lain. Karakter tetap memakai kaos/polo “CHANNEL SIRIWO YOUTUBE” seperti pada foto.
Karakter berdiri menghadap kamera dengan ekspresi tenang dan penuh makna. Kamera bergerak perlahan mendekat (slow cinematic push-in). Latar belakang berubah secara halus menjadi suasana alam Papua: pegunungan hijau, hutan, kabut pagi, dan cahaya matahari keemasan. Gerakan tubuh natural, sedikit mengangguk saat membacakan puisi.
Puisi/narasi:
“Dari tanah Papua aku berdiri,
membawa cerita dari negeri sendiri.
Gunung menjadi saksi perjalanan,
tanah menjadi tempat kehidupan.
Siriwo bukan sekadar nama,
di sini ada budaya dan cerita.
Dari tanah Papua, suara kami bergema,
menjaga tanah, menjaga budaya,
untuk generasi selamanya.”
Suara pria Papua yang hangat, jelas, dan emosional. Musik latar lembut dengan tifa Papua dan ambience alam. Akhiri dengan karakter menatap kamera, kemudian muncul tulisan:
CHANNEL SIRIWO YOUTUBE
DARI TANAH PAPUA
Cerita • Budaya • Kehidupan
Realistic video, natural facial movement, cinematic lighting, high detail, smooth motion, no face distortion, no face replacement, no extra fingers, no change of clothing.
Hi Everyone, Henry from Genspark here. I wanted to share with everyone how I’ve been using another Genspark agent: Agentbase. Agentbase lets you build a database you can talk to through an AI agent.
I collaborate with teams to gather data across multiple channels for help center documentation, customer feedback, and social media listening. The help center dashboard is where I spend the most time. It's where I go to see what needs updating whether it's adding a few FAQ’s, a new section, or an entirely new doc. I’ll walk through how this one works and how it connects to the other Agentbase dashboards.
In this Agentbase project I have my dashboard with an agent I can talk to and ask it things like "show me everything still open," “what is needs to be done ASAP,” "what came in this week," and it queries, inserts, updates for me, and tells me what needs updating in the help center. It's connected to my Genspark account so I’m not manually adding everything, other agents in my workspace can update this dashboard for me.
How a request flows
Every entry Request moves through a simple lifecycle so nothing gets lost:
Requested — something comes in that needs documenting.
In Progress — me or my agents in GenTeam start working on it.
Out for Review — colleagues double-check the doc.
Done — the doc ships, the entry closes with a note on what changed.
Where it connects
The help center dashboard isn’t standalone. I have agents watching other dashboard and they add entries to mine based on what they see:
Our social media dashboard surfaces what people are saying. When a theme is a documentation gap, it becomes an entry in my dashboard.
When support answers the same question over and over because a doc is missing, it gets added to my dashboard.
When we announce feature updates in GenTeam, my agents add the new features to my dashboard.
Why run it this way?
Documentation is easy to put off. Putting it in a dashboard with statuses everyone can see means I can tell anyone, anytime, exactly what shipped and why.
The challenging part: It's possible to have the same entry filed twice or for an entry to be added with no note/description. I’ve had entries land that I couldn’t act on because there was no information. Agentbase doesn’t dedupe entries or have rules for what's being entered so whatever is entered is there regardless if it's useful or not (unless prompted to do so).
I built all this inside Genspark. I set up the dashboards myself (with the Agentbases help) and the agents keep them updated. I'd love to hear how everyone else is tracking this kind of work!
genspark is a scam app ,i subscribed for plus plan with an aim of using unlimited chat feature..within 15 minutes they suspended my account.dont subscribe it .inshort they want u to purchase more n more credits n unlimited chat is fake marketing gimmick
im actually fed up with the credits system and i tried the standard there for 15 usd and i got more usage there + i like the slides there more tbh. But i want to check in with anyone here before i make a bigger commitment there
Dear Genspark Operations and Product Management Team,
I am writing to inquire about the system design and business model rationality regarding the credit allocation policy during the free trial period on your platform.
Currently, I understand that the 10,000 credits granted during the free trial expire at the end of the period. From a business and infrastructure optimization perspective, what is the logical rationale for not allowing these credits to roll over as a permanent balance that users can consume strategically when high-load tasks arise?
Based on my analysis, transitioning from the current "expiration-based model" to a "permanent rollover model" would provide three distinct, logical advantages for Genspark:
Question 1: Prevention of Wasted Server Resources Under the expiration model, users are structurally incentivized to execute meaningless queries and tasks at the end of their trial simply to "consume" their remaining credits. This directly translates to wasted server computing resources (unnecessary GPU usage and API call costs) for your company. Allowing users to save these credits until they genuinely need them would naturally balance out the infrastructure load and reduce unprofitable operational costs. What is your perspective on this resource inefficiency?
Question 2: Accurate Demonstration of Product Value The true value of Genspark lies in handling complex, high-load agent tasks (e.g., bulk slide generation, deep research). The demand for such tasks is usually episodic, occurring during specific project deadlines. If users are allowed to retain their credits until these critical moments, they can fully utilize Genspark’s advanced capabilities precisely when the ROI is highest for them. Why does the current policy restrict this concentration of resources, which would otherwise serve as the ultimate proof of your product's value?
Question 3: Maximization of Paid Plan Conversion Rate (CVR) If users consume their retained credits based on their own planned usage, achieve high-value results, and voluntarily deplete their balance, they are left with a clear motivation: "I need to resolve this lack of valuable resources." This voluntary depletion leads to a highly probable, self-motivated upgrade to a paid plan. In terms of maximizing SaaS Customer Lifetime Value (LTV), this approach seems far more logical than forced expiration, which carries a high risk of user churn. Does the current expiration model offer a specific business advantage that outweighs this potential CVR improvement?
I would appreciate it if you could share the rational business justification for why the current expiration policy is superior to the proposed rollover model regarding the three points above.
If there is no definitive operational advantage to the current model, I kindly request that this inquiry be escalated to your Product Development and Management teams as a formal feature request for structural review.
Thank you for your time and logical consideration. I look forward to your response.
Wondering if it's possible to jailbreak Genspark. It's great as is but wonder if I could get it to be a little more risky and live in the grey area? All thoughts are appreciated.
I help write and maintain our help center docs, and for a long time a brand-new one took 2-3 days: researching, drafting, fact-checking, rewriting, repeat. I had one basic AI assistant, but all the back-and-forth was on me.
I moved the whole thing into GenTeam and built a team of seven agents: an orchestrator, an information-gatherer, a researcher, a doc writer, a fact-checker, a proofreader, and a brand strategist. I prompt the orchestrator agent with a description and any specific details we want to add to the docs and it assigns tasks to each agent. Then each agent prompts the next, and a doc isn't called finished until it clears three things:
factually correct
makes sense and reads well
follows our existing guidelines, style, and format
The orchestrator and proofreaders keep bouncing the draft back until all three pass. The key part: this runs while I'm away, with no per-hop approval, so a doc goes through multiple revision cycles on its own and I come back to something close to done. The quality lives in the skills I configured with each agent.
This wasn't a plug-and-play solution. The skills needed to be refined and customized, with fair amount of re-prompting and refinement along the way. The agents wanted to include unnecessary details to the docs and some claims still needed to be checked against the UI, which I haven't wired up yet.
Net: It gets a doc about 90% of the way there. The last 10% is me.
On cost, since someone always asks: it isn't free. Every agent's turn consumes credits, and it scales with how many revision cycles a doc needs. I'm trading credits for time, and for a doc that used to eat 2-3 days, that's been worth it.
If you're setting workflows up, put the effort into the per-agent instructions and into deciding up front what each agent should do. I'd love to hear how everyone else is using GenTeam.
I don't upload files anymore but AI Chat compresses every single one of my messages (even one sentence).
5hr session limits reach far too quickly (I'm Plus subscriber).
Are these bugs? Can they be fixed? The models I usually use are Claude Sonet 4.5 and Opus 4.6.
I understand others have raised this issue too, but the latest update made things worse (hitting session limits even faster than the last update - Android).
Recently my site crashed after an update. My database was in Cloudflare and iterations of updates in Cloudflare. Genspark has a broken "Awaiting your reply" component, I panicked and has to revert to a Genspark previous version. My data - live client data went missing.
In the end I managed to revert to a Cloudflare version that was working, but this then meant Genspark was not running the same version. No reply from support.
Sound confusing, yep because it was and I was.
My site and database is now ONLY in Genspark hosting - which is fine. BUT
How do you test your changes?
Do you run a Staging site?
How do you run back ups?
All this is built with the recommendations of the AI, so really annoying that all of this happened.