AI Model Comparison

Grok 3 mini Reasoning vs Claude Fable 5

Verdict
Grok 3 mini Reasoning vs Claude Fable 5: Claude Fable 5 scores higher on the Intelligence Index

Head-to-head specifications

MetricGrok 3 mini ReasoningClaude Fable 5Difference
Intelligence Index27.060.0-55.0%
Context window1M tokens1M tokens
Blended price ($/1M tokens)$0.16$1.68-90.5%
Output speed (tokens/s)6665+1.5%
AccessProprietary APIProprietary API
  • Claude Fable 5 leads overall capability (Intelligence Index 60.0 vs 27.0).
  • Grok 3 mini Reasoning is the cheaper model to run at $0.16/1M blended tokens — about 10.5× cheaper.

Verdict: Grok 3 mini Reasoning or Claude Fable 5?

Our recommendation
These two are closely matched — the right pick comes down to which specific strengths you value and the price you actually pay.

Grok 3 mini Reasoning advantages

  • Affordability (+90%)

Claude Fable 5 advantages

  • General intelligence (+55%)

Which should you choose?

  • Choose the Grok 3 mini Reasoning if you want the lowest cost per token at scale.
  • Choose the Claude Fable 5 if you need the strongest overall reasoning and accuracy.

Value for money

Grok 3 mini Reasoning offers more intelligence per dollar (4.7× the Intelligence-Index-per-cost of the alternative), making it the stronger value for high-volume use.

Grok 3 mini Reasoning vs Claude Fable 5: which should you choose?

Grok 3 mini Reasoning — xAI multimodal model with an Intelligence Index of 27, a 1M-token context window and a blended price of $0.16/1M tokens.

Claude Fable 5 — Anthropic multimodal model with an Intelligence Index of 60, a 1M-token context window and a blended price of $1.68/1M tokens.

Grok 3 mini Reasoning vs Claude Fable 5: Claude Fable 5 scores higher on the Intelligence Index. Claude Fable 5 leads overall capability (Intelligence Index 60.0 vs 27.0). Grok 3 mini Reasoning is the cheaper model to run at $0.16/1M blended tokens — about 10.5× cheaper.

Capability: intelligence, coding and agentic work

On the composite Intelligence Index the Claude Fable 5 scores 60.0 versus 27.0. Composite indices summarize many evaluations, but always test on your own workload before committing.

Context window and speed

The Grok 3 mini Reasoning accepts up to 1 million tokens per request, which sets how much documentation, transcript or code it can reason over at once. In measured throughput, Grok 3 mini Reasoning generates faster (66 vs 65 tokens/s), which matters for interactive apps and high-volume pipelines.

Pricing and access

At blended per-token rates, Grok 3 mini Reasoning is the cheaper model to run ($0.16 vs $1.68 per 1M tokens). Grok 3 mini Reasoning is proprietary api and Claude Fable 5 is proprietary api. Open-weight models can be self-hosted, trading per-call cost for infrastructure you manage; for production also weigh rate limits, throughput and data-residency requirements.

The verdict

Both are credible choices in the ai model comparison space; the specification table above lays out every metric so you can weigh the trade-offs that matter to you. Pick the one whose strengths line up with how you will actually use it.

Frequently asked questions

Is the Grok 3 mini Reasoning better than the Claude Fable 5?

These two are closely matched — the right pick comes down to which specific strengths you value and the price you actually pay. Claude Fable 5 leads overall capability (Intelligence Index 60.0 vs 27.0).

What is the main difference between the Grok 3 mini Reasoning and the Claude Fable 5?

Claude Fable 5 leads overall capability (Intelligence Index 60.0 vs 27.0). Grok 3 mini Reasoning is the cheaper model to run at $0.16/1M blended tokens — about 10.5× cheaper.

Which is better value?

Grok 3 mini Reasoning offers more intelligence per dollar (4.7× the Intelligence-Index-per-cost of the alternative), making it the stronger value for high-volume use.

Which should I choose?

Choose the Grok 3 mini Reasoning if you want the lowest cost per token at scale. Choose the Claude Fable 5 if you need the strongest overall reasoning and accuracy.

Methodology

Large language models are compared on independent leaderboard metrics: an Intelligence Index (a composite of reasoning and knowledge evaluations), Coding and Agentic indices where measured, community arena Elo, maximum context window, a blended API price per million tokens (weighted across cache-hit, input and output rates), and measured output speed in tokens per second. Where a model ships multiple reasoning-effort variants, we report its strongest variant. Benchmarks capture only part of real-world quality, which also depends on tool use, latency, safety and task fit — and this space moves quickly, so figures reflect the leaderboard snapshot on the page date.

MC
Marcus Chen
Hardware & Product Analyst

Marcus benchmarks processors, GPUs, phones and vehicles and maintains normalized performance databases.

MSc Computer Engineering10+ years review experience
✓ Reviewed by Priya Nair, Data Quality Reviewer.
Last updated 2026-07-01
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