This is Hamamoto from TIMEWELL.
Genspark launched as a high-performance research AI and has since expanded substantially: image generation, video generation, multi-model AI chat, deep research, and fact-checking are now all part of the platform. This article covers each of these features in detail — including honest assessment of where the platform still has limitations — to help you decide how to incorporate it into your workflow.
Part 1: Core Research and AI Chat
Search with Mind Map Visualization
Genspark's primary search function goes beyond keyword retrieval. When you enter a search query, it gathers information from multiple sources simultaneously, structures the results, and presents them alongside an automatically generated mind map.
In a demonstration covering a specific company inquiry, Genspark scanned official websites, news articles, and other sources, then presented a structured overview of background, activities, and context — displayed in a visual format that shows relationships between information categories. Source citations are listed clearly, supporting fact-checking.
S-Pack Content Generation
From any search result, clicking the S-Pack generation button transforms the gathered information into a formatted article-style page. Sections are organized by topic (summary, background, recent activities), producing a readable document rather than raw search results.
Practical uses for S-Packs:
- Draft material for internal reports
- Structured information-sharing pages
- Quick reference documents on companies or topics
Generated S-Packs can be set to public access (shareable via link) or kept private. There are indications that published S-Packs can appear in search engine results, suggesting potential as a light-weight content publication tool.
Multi-Model AI Chat
The AI chat function gives access to multiple large language models from one interface:
- GPT-5.2
- Claude Opus 4.5 (Opus, Sonnet, Haiku tiers)
- Google Gemini
- DeepSeek
Web search can be enabled for any model, allowing real-time information integration into responses. File attachments are also supported — uploading a document allows the model to summarize, analyze, or answer questions about it.
Chat responses, like search results, can be displayed in mind map format for complex topics.
The ability to switch between models within a single session — using a fast lightweight model for simple queries and a high-capability model for complex analysis — is a practical advantage over managing multiple separate subscriptions.
Part 2: Image Generation (Image Studio)
Available Models
Genspark's Image Studio offers:
- Flux
- Ideogram
- Recraft
- Google Imagen 3
- DALL·E 4
Multiple models can be run simultaneously — the same prompt generates outputs from two or more models in parallel, allowing direct comparison before selecting the best result.
Auto-Prompt Feature
For users unfamiliar with prompt engineering, the auto-prompt function converts a simple description into a detailed, effective prompt.
Example: Input "smiling Japanese woman" → Auto-generated prompt: "A close-up photograph of a smiling Japanese woman in her 30s, natural lighting, soft background blur, high detail, realistic style."
Style Options
Style modifiers available for image generation:
- Illustration / cartoon
- Oil painting
- Watercolor
- 3D rendering
- Realistic photography
Image Remix
A remix function allows using an existing generated image as a base and modifying it through additional instructions — for example, "add a smartphone to her hand." This function was noted as occasionally producing errors in testing; stability may vary.
Mixture of Agents (MoA)
Instead of selecting a specific model, MoA lets Genspark's system automatically choose the most appropriate model for the task. Useful when you're unsure which model to use.
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Part 3: Video Generation
Two Entry Points
Image-to-video: Select a previously generated image and add a motion prompt (e.g., "the woman is laughing and talking"). The still image becomes a short video.
Text-to-video (zero-shot): Generate video directly from a text prompt without a starting image.
Available Models
- Kling (Chinese model, high performance)
- PixVerse
- Runway ML
- Luma Labs
- Veo / Imagen 2 (Google — generally considered the strongest performer)
- Hunyuan (Chinese model)
Configuration Options
- Aspect ratio: 4:3, 16:9, 9:16 (the 9:16 option is particularly useful for social media short-form content)
- Video duration in seconds
The ability to switch between models and adjust these parameters within a single interface — without navigating between multiple specialized video generation tools — reduces friction for iterative testing.
Current quality note: In testing, the text-to-video output occasionally interpreted prompts loosely (a "2D dog" prompt generated a 3D-style dog). Current video generation AI generally has room to improve on prompt fidelity; Genspark is no exception.
Part 4: Deep Research and Fact-Check — Current Limitations
Deep Research: The Concept vs. The Reality
Deep Research is Genspark's version of comprehensive multi-step research — the same concept as Perplexity Pro Search or OpenAI's deep research mode. When activated, it presents a detailed research plan covering background verification, competitive context, financial performance, technology landscape, and causal relationship mapping.
The research plan stage is impressively structured. However, testing revealed significant accuracy problems:
Hallucination example observed: In a research session on a specific company, Genspark stated it was focusing on "the correlation between the company's recently acquired nano-coding patents and expansion into medical devices" — information that was entirely unrelated to the company being researched, suggesting confusion with a different company.
More serious hallucination example: In a separate deep research session on another company, fabricated financial data appeared — specific quarterly revenue figures (¥19.04 billion in Q2 2025 revenue, 1.5% operating margin) that had no factual basis. Personnel information and overseas expansion details also contained errors.
Process instability: In one test, after the research plan was presented and "Start Research" was clicked, a "Failed to fetch" error prevented the actual research from executing.
Assessment: Deep Research is currently beta. The framework is well-designed, but the accuracy and stability gap between the research plan and the actual output is significant. For research where accuracy is critical, Perplexity AI Pro Search or Google Gemini Advanced are more reliable at this stage.
Fact-Check
The fact-check function evaluates whether a statement or piece of text is accurate. In testing with a simple factual statement, it successfully verified the claim, showing its process: initial quick answer, then source-based verification, consideration of counter-evidence, and cross-referencing with academic databases.
For short, clearly factual statements, the function shows useful capability. However, given the hallucination issues observed in Deep Research (which appears to use the same underlying infrastructure), complex or nuanced fact-checking outputs should be treated as preliminary rather than authoritative. Human verification remains necessary.
Pricing
Genspark offers monthly plans and credit packs. Free access provides basic functionality with limits; paid plans unlock higher-performance models and increased usage.
Summary
Genspark's function set and current assessment:
| Feature | Assessment |
|---|---|
| Basic search + mind map | Strong — reliable information gathering with visual output |
| S-Pack generation | Useful — structured content output with shareable link option |
| AI chat (multi-model) | Strong — convenient access to multiple models in one interface |
| Image generation | Strong — diverse model selection, auto-prompt, parallel comparison |
| Video generation | Adequate — good model options, some prompt fidelity limitations |
| Deep Research | Beta — sophisticated framework, significant hallucination risk |
| Fact-check | Adequate for simple statements; caution for complex claims |
Genspark is a genuinely capable platform across research, AI chat, and generative media. The image generation feature in particular — with its model diversity, auto-prompting, and simultaneous multi-model comparison — is a practical tool for content production. For deep research, the platform's current hallucination risk warrants using it as a supplement to rather than replacement for more reliable research tools.
Reference: https://www.youtube.com/watch?v=OMEurprg9n8
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