> ## Documentation Index > Fetch the complete documentation index at: https://docs.agentweb.pro/llms.txt > Use this file to discover all available pages before exploring further. > ## Agent Instructions > --- > About this documentation: Emma is the AI marketing agent built by AgentWeb (the product is also marketed as HireEmma; AgentWeb, Emma, and HireEmma refer to the same product). Emma learns a company's brand, ICP, and positioning, then executes marketing work inside that company's own accounts: research, ad campaigns on Google Ads, Meta, and LinkedIn Ads, LinkedIn and email outbound, organic content, CRM lead enrichment and ICP scoring, and landing pages deployed to the customer's domain. Actions that spend money or post publicly require the user's confirmation. > For what Emma can read, draft, publish, and spend on per channel, see https://docs.agentweb.pro/capabilities. For an overview of the product, see https://docs.agentweb.pro/what-is-emma. For terminology (skill, work plan, scheduled chat, template), see https://docs.agentweb.pro/concepts. # Model selection best practices > Which model to pick for each type of work in Emma — image generation, copywriting, OCR, research, lead enrichment, coding — with cost tiers, sourced benchmarks, and community references. Emma offers a broad, continuously updated catalog of models across leading providers. Which one you pick changes the speed, quality, and cost of every task — and no single model wins at everything. This page maps task types to the models that perform best at them, so you can make an informed choice from the model picker. **Emma's model picker** is at the top of every chat. Switch models mid-conversation if a task changes. Every model listed here is selectable on the current plan — Emma doesn't silently downgrade. ## The decision framework Model selection in 2026 is no longer "pick the best model." The community consensus — across Reddit's r/LocalLLaMA, r/ChatGPT, and r/ArtificialIntelligence, and confirmed by independent benchmarks — is that **multi-model routing beats single-model commitment**. The right question is: what am I asking the model to do *right now*? Three variables matter: * **Quality ceiling** — does this task need frontier reasoning, or is "good enough" actually good enough? * **Speed** — is this interactive (you're waiting) or batch (it runs overnight)? * **Cost** — one image at \$0.04 is fine; 500 images at \$0.19 each is a budget decision. ## Recommended models by task ### Ad creative and image generation **Recommended: Gemini 3.1 Flash Image** The best ROI for speed and quality in ad creative production. Independent testing shows Gemini Flash models produce legible text, correct diagrams, and brand-accurate product images at roughly \$0.04 per image in under 12 seconds — compared to GPT Image 2 at \~\$0.19 and 60+ seconds ([Meowapps benchmark, June 2026](https://meowapps.com/ai-image-model-comparison/)). For Emma's B2B Meta Ads work plan, which generates 20+ creatives per campaign, this difference compounds: a full creative arsenal costs under \$1 on Flash vs. \$4+ on GPT Image. The Reddit community on r/ArtificialIntelligence has reached consensus that Gemini image models (the "Nano Banana" family) offer the best overall value for production workflows — fast generation, strong text rendering, and the lowest cost per image among frontier models ([AI Tool Discovery, Reddit roundup, July 2026](https://www.aitooldiscovery.com/guides/ai-image-generator-reddit)). **When to upgrade:** GPT Image 2 produces the most detailed and illustrative output when absolute visual quality matters more than speed or cost — hero images for a homepage or a single high-stakes creative. Use it selectively, not as the default. ### Marketing copy, ad copy, and content writing **Recommended: Claude Sonnet 5** Claude models consistently produce the most natural-sounding prose and follow brand voice instructions more reliably than alternatives. The EQ-Bench Creative Writing leaderboard (August 2026) confirms Claude as the current benchmark for tone, nuance, and structural variety in marketing content ([EVY, August 2026](https://evy.so/compare/best-llms-for-writing/)). BenchLM rates Claude's instruction-following (Arena IF: 1500) as the highest among frontier models ([BenchLM, July 2026](https://benchlm.ai/blog/posts/best-llm-writing)) — which is exactly what matters when Emma is writing in your founder's voice from Brand Guidelines. For Emma's content workflows — LinkedIn posts, ad copy, email sequences, landing page text — Claude Sonnet 5 is the current Sonnet recommendation. It improves on Sonnet 4.6 while retaining Sonnet's standard \$3/\$15 per-million-token rate; AWS offers a temporary \$2/\$10 introductory rate through August 31, 2026 ([AWS pricing](https://aws.amazon.com/bedrock/pricing/)). **When to upgrade:** Claude Opus 5 for the highest-stakes content — investor-facing materials, long-form thought leadership, or anything where the first draft needs to be very close to publishable. Opus 5 keeps Opus 4.8's \$5/\$25 per-million-token price while improving agentic knowledge-work results ([Artificial Analysis](https://artificialanalysis.ai/articles/claude-opus-5-leader-agentic-knowledge-work)). ### Handwritten text extraction and document OCR **Recommended: Claude Sonnet 5 or GPT-5.5** Handwriting OCR is a task where frontier vision models have decisively overtaken traditional OCR engines. The 2026 benchmarks tell a clear story: frontier vision-language models achieve sub-2% character error rate on modern handwriting, compared to 9%+ for dedicated handwriting engines ([Journal of Documentation, 2025; CodeSOTA benchmark, 2026](https://www.codesota.com/ocr/best-for-handwriting)). Both Claude Sonnet 5 and GPT-5.5 work well. Claude is the better fit for dense, structured documents — contracts, multi-table pages, and technical reports — where the model must interpret as well as transcribe. Use GPT-5.5 when it is already selected for the surrounding workflow. The practical recommendation: use whichever model you're already running for the surrounding workflow. If you're processing event registration forms in a CRM pipeline, Claude is already loaded. If you're extracting data from scanned receipts in a standalone task, GPT handles the worst handwriting marginally better. **What doesn't work:** Gemini Flash models — their vision capabilities are excellent for general image understanding, but fine-grained text extraction on degraded or handwritten documents is not their strength. This is a task where you need frontier-tier vision, not the fast-and-cheap tier. ### Research, competitor analysis, and long-document processing **Recommended: Gemini 3.7 Flash** Google explicitly recommends Gemini 3.7 Flash as the migration target for both Gemini 3.5 Flash and Gemini 3.1 Pro. It supports a 1M-token context window, search grounding, function calling, and adjustable reasoning effort ([Google model guide](https://ai.google.dev/gemini-api/docs/latest-model)). For the research and long-document work that appears in Emma's work plans, this is both a quality and cost upgrade. Gemini 3.7 Flash has a higher Artificial Analysis Intelligence Index score than Gemini 3.5 Flash, with Google's introductory \$0.75/\$3.75 per-million-token rate through December 31, 2026 ([Artificial Analysis](https://artificialanalysis.ai/articles/gemini-3-7-time-frontier), [Google pricing](https://ai.google.dev/gemini-api/docs/pricing)). **When Claude is better:** Use Claude Sonnet 5 or Opus 5 when the work turns from gathering information into deep analysis, precision extraction, or a high-stakes deliverable. Gemini 3.7 Flash is the better default for broad research and long-document triage; Claude is the better escalation path for the analysis that follows. ### Lead enrichment and CRM workflows **Recommended: Claude Sonnet 5 at minimum; Claude Opus 5 strongly preferred for high-value batches** Lead enrichment is one of Emma's most demanding tasks. It chains web search, LinkedIn profile parsing, ICP scoring, and personalized outreach drafting across dozens of leads in a single run. Cheap models produce shallow enrichment — missing firmographic detail, generic ICP scores, and template-sounding outreach that contacts ignore. **The rule: the more advanced the model, the better the enrichment quality.** At the very least, use Claude Sonnet 5. For large enrichment runs (50+ leads, event guest lists, scheduled enrichment), Opus-class models produce meaningfully better results — deeper company research, more accurate ICP scoring, and outreach drafts that read like they were written by someone who actually read the prospect's LinkedIn. For the Field Event Luma Engagement work plan and batch CRM enrichment, use Claude Opus 5. The per-lead cost increase is small relative to the value of correctly qualifying and personalizing outreach to high-intent event leads. ### Coding, technical implementation, and skill development **Recommended: Claude Sonnet 5** Claude Sonnet 5 is the current Sonnet model for coding, agentic workflows, and professional work at scale ([AWS](https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-anthropic-claude-sonnet-5.html)). For Emma's internal skill development and landing page code editing, use Sonnet 5 rather than a retired 4.x Sonnet ID. **For cost-sensitive batch coding:** DeepSeek V4 Pro delivers 85-90% of frontier model performance at a fraction of the cost. Good for high-volume routine tasks where you're running many similar operations. ### X posts and tweet ranking **Recommended: Grok 4.6** Use Grok for X posts when the goal is strong distribution on X. Grok is built by xAI, the company behind X, so it is the specialist recommendation for writing in the conventions and topics that travel on that network. Keep this recommendation separate from the general model-refresh policy: a newer general-purpose model is not a substitute for an X-specific workflow. ### General-purpose and mixed-task conversations **Recommended: Gemini 3.7 Flash** or **Claude Sonnet 5** For conversations that jump between tasks — "update my Market Strategy, then draft a LinkedIn post, then check my CRM leads" — Gemini 3.7 Flash is the cost-efficient default. Switch to Claude Sonnet 5 when writing quality or more demanding multi-step reasoning matters. ## Quick-reference table | Task | Recommended model | Why | When to switch | | ------------------------ | -------------------------- | ----------------------------------------------------- | --------------------------------------------------- | | **Ad creative / images** | Gemini 3.1 Flash Image | Fast image generation and editing | GPT Image 2 for hero-quality singles | | **Marketing copy** | Claude Sonnet 5 | Current Sonnet quality at Sonnet pricing | Opus 5 for investor/long-form | | **Handwriting OCR** | Claude Sonnet 5 or GPT-5.5 | Frontier vision and document reasoning | Use the model selected for the surrounding workflow | | **Research / long docs** | Gemini 3.7 Flash | Current Gemini Flash with 1M context and grounding | Claude for precision extraction and reasoning | | **Lead enrichment** | Claude Opus 5 | Deep research, accurate ICP scoring, quality outreach | Sonnet 5 for higher-throughput runs | | **Coding / skills** | Claude Sonnet 5 | Current Sonnet for coding and agentic work | DeepSeek V4 for batch/cost | | **X posts / tweets** | Grok 4.6 | X-specific writing and ranking context | Sonnet 5 for non-X long-form writing | | **General purpose** | Gemini 3.7 Flash | Current cost-efficient default | Sonnet 5 when writing quality matters | ## Cost tiers at a glance Emma's models fall into three cost tiers. Knowing which tier you're in helps you budget: | Tier | Models | Typical use | | ------------- | ------------------------------------------------------------------------ | ------------------------------------------------------------------ | | **Budget** | Gemini 3.1 Flash Lite, Claude Haiku 4.5, GPT-5.4 Nano, DeepSeek V4 Flash | Simple lookups, lightweight scheduled chats | | **Mid-range** | Gemini 3.7 Flash, Claude Sonnet 5, GPT-5.5, DeepSeek V4 Pro | Day-to-day work — content, campaigns, CRM, research | | **Premium** | Claude Opus 5, GPT-5.6 Sol | Lead enrichment, complex multi-step work plans, frontier reasoning | ## Sources The recommendations above draw from both Emma's internal benchmarking and the broader practitioner community: * **Image generation:** Gemini 3.1 Flash Image is the stable image model currently served by Emma. GPT Image 2 remains the alternative for a small number of hero-quality images. * **Writing quality:** [Artificial Analysis' Sonnet 5 evaluation](https://artificialanalysis.ai/articles/claude-sonnet-5-agentic-cost) reports a six-point Intelligence Index gain over Sonnet 4.6 at the same standard token price. [AWS](https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-anthropic-claude-sonnet-5.html) confirms Claude Sonnet 5 is the current Bedrock model. * **Handwriting OCR:** CodeSOTA benchmark (2026) measures frontier VLMs at 1.2-1.5% CER, beating the GPT-4o 1.69% baseline from March 2025 (arXiv 2503.15195). TokenMix production testing (April 2026) reports GPT-4o Vision at 91.2% on handwritten forms, Claude at 97.6% on complex structured extraction. AIMultiple's 2026 handwriting benchmark reports Gemini 2.5 Pro at 93% accuracy, behind GPT-5 (95%). * **Research and long context:** [Google's migration guide](https://ai.google.dev/gemini-api/docs/latest-model) names Gemini 3.7 Flash as the target for Gemini 3.1 Pro and Gemini 3.5 Flash workloads. It has a 1M-token context window, grounding, and adjustable reasoning effort. * **Coding:** [AWS](https://aws.amazon.com/blogs/machine-learning/introducing-claude-sonnet-5-on-aws-anthropics-most-capable-sonnet-model/) documents Sonnet 5 as its most capable Sonnet model for coding and agentic work. Emma's current Sonnet option replaces retired 4.x Sonnet versions. * **Multi-model routing:** The 2026 practitioner consensus — visible across Reddit, Medium, and independent benchmarks — is that no single model wins everything. Teams routing Claude for coding and writing, Gemini for research and batch work, and GPT for mixed-modal tasks consistently outperform single-vendor setups. ## How to change models In the [Customer Portal](https://app.agentweb.pro): 1. **Per conversation:** Click the model name at the top of any chat to open the picker. Your selection persists for that conversation. 2. Scheduled chats: set the model when creating or editing a [scheduled chat](/concepts). Budget models like Gemini 3.1 Flash Lite are fine for lightweight tasks; use Opus for lead enrichment and complex workflows. 3. **For work plans:** Some work plans specify a default model (e.g., Meta Pre-Launch Gate defaults to Claude Opus). You can override this at the start of the conversation if you prefer a different model. ## Next steps * [Concepts](/concepts) — skill, work plan, scheduled chat, template. * [Agent Mode](/user-guide/agent-mode) — the chat interface where you select models. * [Settings](/user-guide/settings) — manage connected accounts and API configuration.