Choosing the Right AI Model

Estimated read time: 8 minutes

Overview

Every workflow in AskElephant runs on an AI model — the engine that powers your analysis, generates insights, and produces results. Different models have different strengths. Some are built for speed. Others handle massive amounts of information. Some specialize in deep reasoning.

Picking the right model means better results, faster. You don't need to deeply understand how AI works to make a smart choice. This guide walks you through when to use each model.

What's New

• claude-sonnet-4-6 — Anthropic's newest Sonnet, now with a 1M-token context window. Best general-purpose pick when you need both quality and long context.
• gpt-5.5 — OpenAI's frontier reasoning model with a ~1M-token context window. Strong on multi-step reasoning, long-form generation, and analytical extraction.
• grok-4-1-fast-reasoning and grok-4-1-fast-non-reasoning (Beta) — xAI's tool-calling specialists with a 2M-token context window and a togglable reasoning mode.

Key Terms

• AI model: The underlying technology that processes your instructions and information. Think of it as a specialized tool with particular strengths — like choosing between a hammer and a screwdriver for different jobs.
• Context window: How much information a model can process at once. A larger context window means more meetings, documents, or data in a single analysis.
• Token: The basic unit of information AI processes — roughly one word.
• Inference: The process of the model analyzing your information and producing results.

Start Here: The Recommended Default

claude-haiku-4-5 is your starting point for most workflows.

This model strikes the best balance:

• Handles writing, analysis, and creative thinking equally well
• Fast enough for real-time workflows
• 200,000-token context window (roughly 150,000 words)
• Reliable across a wide range of tasks

Processing capacity: approximately 20–30 hours of meeting recordings, or 150–200 individual transcripts.

When to Use It: meeting summaries, coaching analysis, CRM updates, customer insights, most general-purpose tasks.

If you're unsure, claude-haiku-4-5 is the answer. It won't be the fastest for every task, but it delivers solid results consistently.

For Speed: Gemini Flash or GPT-5 Nano

Choose models/gemini-flash-latest or gpt-5-nano when you need quick results without sacrificing quality. They're particularly strong when:

• You're looping through many meetings and pulling quick insights from each
• You need lightweight, snappy answers
• You're building workflows that run frequently
• Speed is the priority

Processing capacity: models/gemini-flash-latest handles ~100–150 hours of meetings (1M context); gpt-5-nano handles ~40–60 hours (400K context).

Best For: loop prompts that process 10+ meetings, real-time workflow notifications, lightweight analysis.

For General Excellence: Claude 4.6 Sonnet or Claude 4.5 Sonnet

claude-sonnet-4-6 is the new Swiss Army knife. It handles everything well, and with a 1M-token context window it now competes on volume too. Use it when:

• You need the highest-quality analysis on complex topics
• You're building mission-critical workflows (sales handoffs, customer health assessments)
• You're combining multiple data sources and need nuanced synthesis
• Quality matters more than speed

claude-sonnet-4-5 remains a great choice if you want the proven 4.5-generation behavior with a 200K context window.

Processing capacity: claude-sonnet-4-6 ~100–150 hours (1M context); claude-sonnet-4-5 ~20–30 hours (200K context).

Best For: complex coaching analysis, comprehensive customer summaries, detailed strategic recommendations, multi-source data synthesis.

For Analysis, Numbers, and Long-Form Reasoning: GPT-5.5 and the GPT-5.4 Family

OpenAI's newest models are strong at analytical thinking, structured extraction, and multi-step reasoning across long documents.

• gpt-5.5 — Frontier model. Reach for it when the problem is genuinely complex (deep customer analysis, strategic reasoning, intricate extraction) and you want OpenAI's best.
• gpt-5.4 — Same ~1M-token context, faster and cheaper than 5.5. Good default for analytical workflows that don't need the absolute frontier.
• gpt-5.4-mini — Lighter, faster 5.4 variant for medium-complexity work.
• gpt-5.4-nano — Fastest, cheapest 5.4. Use for high-volume extraction or classification tasks.

Best For: deal analysis, technical documentation review, financial summaries, precise data extraction, structured outputs at scale.

For Deep Reasoning: Claude 4.6 Sonnet, GPT-5.5, or Grok 4

These models are built to think through complex problems step by step. Use them when:

• You need the model to work through multi-step reasoning
• The problem is genuinely complex, not just long
• You're analyzing nuanced customer situations or strategic scenarios
• The extra analysis time is worth the deeper insights

Trade-off: reasoning models are slower than standard models but produce more thorough output.

Best For: strategic planning, complex competitive analysis, intricate customer situation assessments, detailed coaching recommendations.

For Massive Context: Grok 4.1 Fast, Grok 4 Fast, or Gemini Pro

When you're working with enormous amounts of information, these models handle the load.

• grok-4-1-fast-reasoning and grok-4-1-fast-non-reasoning (Beta) — 2M-token context, optimized for tool-calling and multi-step agentic work. Reasoning mode for analysis; non-reasoning for low-latency throughput.
• grok-4-fast-reasoning and grok-4-fast-non-reasoning — 2M-token context, the proven generation. Great for processing 50+ meetings or massive document libraries in one workflow.
• models/gemini-pro-latest — 1M-token context, strong multimodal reasoning and long-document synthesis.

When You Need This: quarterly business reviews, comprehensive account histories, analyzing entire customer journeys, processing years of meeting data in one workflow.

Reality Check: most workflows don't need this much capacity. Reach for these only when your standard model hits its limits.

For Open-Source or Specialized Tasks: Llama (Beta)

• llama-3.3-70b-versatile (Beta) — Strong on math, coding, and multilingual tasks. Good open-source option for specialized technical analysis.
• llama-3.1-8b-instant (Beta) — Lightweight conversational model. Use for rapid prototyping, simple classification, or content filtering where latency matters most.

How to Choose: The Decision Framework

Ask yourself these questions in order.

1. How Much Information Are You Processing?

• Just one meeting (1 hour)? claude-haiku-4-5 or models/gemini-flash-latest
• 5–20 meetings (5–20 hours)? claude-haiku-4-5, gpt-5.4, or claude-sonnet-4-5
• 50+ meetings or 50+ hours of data? grok-4-1-fast-reasoning, grok-4-fast-reasoning, models/gemini-pro-latest, or claude-sonnet-4-6

2. How Complex Is the Analysis?

• Straightforward summary or extraction? Use the fastest option
• Nuanced analysis or multiple perspectives? claude-sonnet-4-6, claude-sonnet-4-5, or gpt-5.4
• Deep reasoning or strategic thinking? claude-sonnet-4-6, gpt-5.5, or grok-4-latest

3. What's Your Priority?

• Speed: models/gemini-flash-latest, gpt-5-nano, or claude-haiku-4-5
• Quality: claude-sonnet-4-6 or gpt-5.5
• Volume of Data: grok-4-1-fast-reasoning, grok-4-fast-reasoning, or models/gemini-pro-latest
• Reasoning Power: gpt-5.5, claude-sonnet-4-6, or grok-4-1-fast-reasoning

Real Workflow Examples

Example 1: Daily Sales Call Summaries

Model: claude-haiku-4-5. Fast, handles writing and summary tasks well. Processes 1–2 hour calls with quick turnaround. Runs multiple times daily.

Example 2: Quarterly Customer Health Assessment

Model: claude-sonnet-4-6 or gpt-5.5. Requires deep analysis across multiple data points. Both can ingest 20–30 hours of customer interactions in a single pass. Quality of insights is the priority.

Example 3: Processing 100 Past Meetings for a Strategic Account Review

Model: grok-4-1-fast-reasoning or models/gemini-pro-latest. Can process 100+ hours of meetings or 1,000+ transcripts. Standard models would hit their limits. These handle the volume while maintaining quality.

Example 4: Extracting Pricing Details from 20 Recorded Calls

Model: gpt-5.4 or gpt-5.5. Analytical strength in parsing precise financial details. Both handle 20+ hours of recordings comfortably.

Settings That Matter

Once you've chosen a model, two additional settings shape your results.

Temperature

Controls how creative or consistent the output is. Lower temperatures (closer to 0) produce more consistent, predictable results. Higher temperatures (closer to 1) produce more varied, creative responses.

• For summaries and extraction: use lower temperature
• For brainstorming or creative writing: use higher temperature

Max Steps

Determines how thoroughly the model analyzes before stopping.

• More steps = deeper analysis but slower results
• Fewer steps = faster results but potentially less thorough

Most workflows use default settings. Adjust only if you notice results are consistently too brief or too verbose.

Start Simple, Optimize Later

Your first instinct should always be claude-haiku-4-5. Run your workflow. Check the results. If they're solid, you're done.

Only switch to a more specialized model if you notice specific problems:

• Results too shallow? Try claude-sonnet-4-6 or claude-sonnet-4-5
• Can't process all your data? Try grok-4-1-fast-reasoning or models/gemini-pro-latest
• Need analytical precision? Try gpt-5.4 or gpt-5.5
• Need deep reasoning? Try gpt-5.5, claude-sonnet-4-6, or grok-4-latest

You can always change models mid-project. There's no penalty for experimenting.

Complete AI Model Reference

Some models are currently in Beta. If you encounter issues or have questions, contact AskElephant Support.

*Call Time Capacity is approximate based on average meeting speech rates of 120–150 words per minute. Actual capacity varies based on transcript length, formatting, and additional context.

Need Additional Help?

If you have questions or need further assistance, the AskElephant support team is here to help:

• Click the chat button in the bottom right corner of your screen
• Email us at [email protected]
• Use @askelephant support in your dedicated Slack channel

We're committed to getting you the answers you need as quickly as possible.