Claude Fable 5 vs GPT-5 vs Gemini 2.5 Pro — which model should you use?

Why model choice matters

Using the wrong AI model for a task is like using a sledgehammer to hang a picture frame. You might get the result, but you burned unnecessary cost and time. The right model depends on what you're trying to do — and how much thinking the problem actually requires.

Here's a practical breakdown of every major model in AskWek and exactly when to use each one.

Tier 1: Frontier Models (Maximum intelligence)

Claude Fable 5 (Anthropic)

Cost: ~6,000 credits per typical exchange

Best for: Multi-step reasoning, complex analysis, long documents, code review, research synthesis

Fable 5 is Anthropic's most capable model. Its defining strength is structured, careful reasoning — it's excellent at following complex instructions with many conditions, spotting logical inconsistencies, and producing well-organised long-form output.

Use Fable 5 when:

• You're asking it to analyse a 50-page document
• You need a rigorous comparison of options with trade-offs
• You want high-quality code review with security analysis
• The answer needs to be genuinely correct, not just plausible

GPT-5 (OpenAI)

Cost: ~5,200 credits per typical exchange

Best for: Creative writing, nuanced tone matching, multi-modal tasks, business communication

GPT-5 is OpenAI's flagship. It excels at understanding tone and context, making it exceptional for email drafting, marketing copy, and anything where voice and style matter.

Use GPT-5 when:

• You need writing that sounds like a specific style or tone
• You're drafting client-facing communication
• You want creative output (stories, pitches, scripts)
• You need strong instruction-following across a long conversation

Gemini 2.5 Pro (Google)

Cost: ~4,800 credits per typical exchange

Best for: Data analysis, factual research, long context windows, Google Workspace workflows

Gemini 2.5 Pro has a massive context window (1M+ tokens) and exceptional accuracy on factual tasks. If you're analysing a massive dataset or long PDF, Gemini is often the right choice.

Use Gemini 2.5 Pro when:

• You're working with very long documents
• You need accurate factual answers (it has strong knowledge grounding)
• You're doing data interpretation or spreadsheet analysis

Tier 2: Mid-Range Models (Best balance)

Claude Sonnet 4.6 (Anthropic)

Cost: ~900 credits per typical exchange

Best for: Day-to-day AI work, professional writing, analysis, coding help

Sonnet 4.6 is the model most AskWek users spend the most time with. It's the sweet spot — strong enough for nearly every professional task, fast, and costs 6x less than Fable 5. If you're not sure what model to use, Sonnet 4.6 is almost always the right answer.

GPT-4o (OpenAI)

Cost: ~625 credits per typical exchange

Best for: Versatile everyday use, vision tasks, conversational AI

GPT-4o is OpenAI's workhorse. It handles images, audio, and text. Great for multi-modal tasks and day-to-day conversation.

Tier 3: Fast & Cheap Models (High volume tasks)

Claude Haiku 4.5 (Anthropic)

Cost: ~240 credits per typical exchange

Best for: Simple questions, summarisation, quick drafts, form filling

Haiku 4.5 is surprisingly capable for a cheap model. Great for anything that doesn't need deep reasoning.

GPT-4.1 Mini (OpenAI)

Cost: ~100 credits per typical exchange

Best for: High-volume tasks, quick queries, filtering and classification

GPT-4.1 Mini is fast, cheap, and surprisingly competent. Great for running a skill that calls AI many times in sequence.

Amazon Nova Micro

Cost: ~9 credits per typical exchange

Best for: Simple Q&A, formatting tasks, translation, basic summaries

Nova Micro is what the Free plan runs by default. It's ultra-fast, extremely cheap, and still does a respectable job on simple tasks. 50,000 free credits gives you roughly 5,500 Nova Micro exchanges per month.

Quick reference

The best approach: use Haiku or Nova Micro for your first attempt at any task. If the result isn't good enough, escalate to Sonnet or a frontier model. This way you get the best quality when you need it while preserving credits for the long run.