> For the complete documentation index, see [llms.txt](https://docs.qolaba.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.qolaba.ai/model-reference/chatbot-models.md). # Chatbot Models Qolaba's Chatbot gives you access to 30+ large language models across six providers — all from a single interface. Each model has a different context window, credit cost, and area of strength. Use this page as a reference when selecting a model for a specific task. *** ### How to Read This Page
ColumnWhat It Means
Context WindowMaximum tokens the model can process in a single request — includes your prompt, conversation history, uploaded files, and the model's response. See Model Information Panel → for a detailed explanation of how context windows work.
Input Credits / 1K tokensCredits consumed per 1,000 input tokens — your prompt, files, conversation history, and system instructions
Output Credits / 1K tokensCredits consumed per 1,000 output tokens — the model's generated response, including thinking tokens if Thinking Depth is enabled
{% hint style="info" %} Models marked with ⭐ are available on **paid plans only**. {% endhint %} *** ### Gemini Models *Google* Gemini models are Google's family of large language models — strong across long-context tasks, multimodal inputs, and general-purpose generation. The 1M token context window across most Gemini models makes them particularly well-suited for large document analysis, extended research sessions, and long conversations. | Model | Context Window | Input Credits / 1K | Output Credits / 1K | Best For | | ---------------------------- | -------------- | ------------------ | ------------------- | --------------------------------------------------------------------------------------- | | **Gemini 2.5 Flash** | 1M | 0.08 | 0.65 | Fast, cost-efficient general tasks — everyday queries, summarization, quick drafts | | **Gemini 2.5 Pro** | 1M | 0.33 | 0.39 | Balanced quality and cost — research, analysis, long-document processing | | **Gemini 3 Flash Preview** | 1M | 0.13 | 0.78 | Fast generation with improved quality over 2.5 Flash — content drafting, quick analysis | | **Gemini 3 Pro Preview** ⭐ | 1M | 0.52 | 3.12 | High-quality outputs — complex reasoning, detailed analysis, nuanced writing | | **Gemini 3.1 Pro Preview** ⭐ | 1M | 1.04 | 4.68 | Highest quality Gemini output — advanced reasoning, complex multi-step tasks | *** ### Claude Models *Anthropic* Claude models are Anthropic's family of large language models — known for strong instruction following, nuanced writing quality, and reliable performance on long-form content. Claude models have a 200K context window, making them well-suited for detailed documents, complex briefs, and extended reasoning tasks. | Model | Context Window | Input Credits / 1K | Output Credits / 1K | Best For | | ----------------------- | -------------- | ------------------ | ------------------- | --------------------------------------------------------------------------------------- | | **Claude Sonnet 4.6** ⭐ | 1M | 0.78 | 3.90 | Balanced quality and speed — writing, analysis, coding, general professional tasks | | **Claude Opus 4.6** ⭐ | 200K | 1.30 | 6.50 | Premium quality — complex reasoning, detailed writing, nuanced instruction following | | **Claude Opus 4.7** ⭐ | 200K | 1.30 | 6.50 | Latest Opus — advanced reasoning, high-complexity tasks, long-form professional content | *** ### OpenAI Models *OpenAI* OpenAI models span a wide range — from the most cost-efficient nano models for everyday tasks to advanced reasoning models for complex problem solving. The GPT and o-series models offer strong prompt comprehension, reliable structured output, and broad capability across coding, writing, and analysis. | Model | Context Window | Input Credits / 1K | Output Credits / 1K | Best For | | ------------------ | -------------- | ------------------ | ------------------- | --------------------------------------------------------------------------------------- | | **GPT-4.1** ⭐ | 1M | 0.52 | 2.08 | General-purpose — reliable across writing, coding, analysis, and summarization | | **GPT-4.1 Mini** | 1M | 0.10 | 0.42 | Cost-efficient general tasks — everyday queries, drafts, quick summaries | | **GPT-5 Nano** | 128K | 0.03 | 0.10 | Most cost-effective OpenAI model — rapid iteration, high-volume simple tasks | | **GPT-5 Mini** | 200K | 0.12 | 0.94 | Lightweight everyday tasks — content drafting, quick answers, basic analysis | | **GPT-5.2** ⭐ | 200K | 0.46 | 3.64 | Balanced quality — professional writing, structured analysis, coding assistance | | **GPT-5.2 Pro** ⭐ | 200K | 5.46 | 43.68 | Maximum GPT-5.2 capability — highest quality structured outputs, complex reasoning | | **GPT-5.4** ⭐ | 272K | 0.65 | 3.90 | Strong general capability — detailed analysis, complex writing, multi-step tasks | | **GPT-5.4 Mini** | 200K | 0.20 | 1.17 | Balanced speed and quality — content creation, moderate complexity tasks | | **GPT-5.4 Nano** | 128K | 0.05 | 0.33 | Fast, low-cost iteration — simple tasks, drafts, quick queries | | **GPT-5.5** ⭐ | 1M | 1.30 | 7.80 | Flagship GPT model — advanced reasoning, complex multi-step tasks, high-quality outputs | | **OpenAI o1** ⭐ | 200K | 4.29 | 17.16 | Advanced reasoning — complex logic, math, coding, multi-step problem solving | | **OpenAI o3** ⭐ | 200K | 0.52 | 2.08 | Strong reasoning at moderate cost — analytical tasks, structured problem solving | | **OpenAI o4 Mini** | 200K | 0.29 | 1.14 | Cost-efficient reasoning — logic tasks, coding, analysis at lower credit cost | *** ### DeepSeek Models *DeepSeek* DeepSeek models deliver strong technical performance — particularly for coding, mathematical reasoning, and analytical tasks — at highly competitive credit costs. Well-suited for developer workflows and cost-sensitive high-volume use cases.
ModelContext WindowInput Credits / 1KOutput Credits / 1KBest For
DeepSeek V3.2 ⭐131K0.070.10Cost-efficient general tasks — coding assistance, technical writing, analysis
DeepSeek V3.2 Speciale ⭐128K0.070.10General-purpose tasks — everyday queries, content drafting, summarization
DeepSeek R1 ⭐164K0.180.65Reasoning tasks — multi-step logic, math, structured problem solving
*** ### Grok Models *xAI* Grok models are xAI's family of large language models — built for fast, real-time responses with strong general capability. The 2M token context window makes Grok models the highest context capacity models available in Qolaba — suited for extremely long documents, large codebases, and extended multi-turn conversations. | Model | Context Window | Input Credits / 1K | Output Credits / 1K | Best For | | ------------------- | -------------- | ------------------ | ------------------- | ------------------------------------------------------------------------------------------------------------ | | **Grok 4.1 Fast** ⭐ | 2M | 0.05 | 0.16 | Fast, cost-efficient responses — everyday tasks, quick analysis, real-time queries | | **Grok 4.20** ⭐ | 2M | 0.52 | 1.56 | High-quality responses with maximum context — large document analysis, extended conversations, complex tasks | *** ### Perplexity Models *Sonar* Perplexity's Sonar models are purpose-built for web-grounded responses — all models have built-in internet search, delivering answers backed by live, up-to-date sources rather than training data alone. Best for research, fact-checking, competitive intelligence, and any query where current information matters. | Model | Context Window | Input Credits / 1K | Output Credits / 1K | Best For | | ------------------------- | -------------- | ------------------ | ------------------- | ------------------------------------------------------------------------------------------------ | | **Sonar** | 127K | 0.26 | 0.26 | Fast web-grounded responses — general research, current events, quick fact-checking | | **Sonar Pro** | 200K | 0.78 | 3.90 | Higher quality web-grounded responses — detailed research, in-depth analysis with live sources | | **Sonar Reasoning Pro** ⭐ | 200K | 0.52 | 2.08 | Web-grounded reasoning — research tasks requiring logical analysis of live information | | **Sonar Deep Research** ⭐ | 128K | 0.52 | 2.08 | Deep, multi-source research — comprehensive reports, competitive analysis, thorough fact-finding | *** ### Choosing the Right Model With 30+ models available, here is a practical starting point for common use cases: | Use Case | Recommended Model | Reason | | ---------------------------------------- | ----------------------------------- | ------------------------------------------------ | | **Everyday tasks and drafting** | Gemini 2.5 Flash or GPT-4.1 Mini | Low cost, reliable quality for standard tasks | | **Professional writing and analysis** | Claude Sonnet 4.6 or GPT-5.2 | Strong writing quality and instruction following | | **Complex reasoning and logic** | OpenAI o3 or DeepSeek R1 | Purpose-built for multi-step reasoning | | **Advanced reasoning — maximum quality** | OpenAI o1 or Gemini 3.1 Pro Preview | Highest reasoning capability available | | **Coding and technical tasks** | DeepSeek V3.2 or GPT-5.4 | Strong technical performance at competitive cost | | **Research with live web data** | Sonar or Sonar Deep Research | Built-in web search for current, sourced answers | | **Long document analysis** | Grok 4.20 or Gemini 2.5 Pro | 1M–2M context window for large inputs | | **High-volume, cost-sensitive tasks** | GPT-5 Nano or Grok 4.1 Fast | Lowest credit cost per token | | **Premium quality — best output** | GPT-5.5 or Claude Opus 4.7 | Flagship models for highest quality output | --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.qolaba.ai/model-reference/chatbot-models.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.