Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | GPT-4 | Claude Fable 5.1 (Adaptive Reasoning, Max Effort, Default Fallback) |
|---|---|---|
| Input ($/M tokens) | $30 | $10 |
| Output ($/M tokens) | $60 | $50 |
Verdict. Claude Fable 5.1 (Adaptive Reasoning, Max Effort, Default Fallback) takes the aggregate benchmark matchup 2–0 across 2 categories. Real workloads usually care about a handful of specific tasks — see the per-benchmark table above.
Pricing. Both models sit in the premium bracket for output-token pricing. At 1.2× the per-million-token cost, Claude Fable 5.1 (Adaptive Reasoning, Max Effort, Default Fallback) is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). Claude Fable 5.1 (Adaptive Reasoning, Max Effort, Default Fallback) makes more sense when output volume is low and absolute reasoning quality justifies the premium.
Strengths. GPT-4 is strongest on Coding Index (13.1), Intelligence Index (6.8). Claude Fable 5.1 (Adaptive Reasoning, Max Effort, Default Fallback) leads on Coding Index (81.6), Intelligence Index (65.7).
Speed. Speed data is incomplete for this pair; benchmark and price should decide.
Provider. OpenAI and Anthropic sell to overlapping but distinct developer audiences: OpenAI tends to ship frontier reasoning models with premium positioning, while Anthropic often prices more aggressively. Your existing vendor relationships, billing, and SLA preferences may matter as much as the raw numbers above.
Workload cost. Workload scenarios (per million requests at 30M input + 15M output tokens): GPT-4 costs $1800.00 ($21600/year); Claude Fable 5.1 (Adaptive Reasoning, Max Effort, Default Fallback) costs $1050.00 ($12600/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): GPT-4 ≈ $270.00/run, Claude Fable 5.1 (Adaptive Reasoning, Max Effort, Default Fallback) ≈ $150.00/run. At agent/realtime scale (200M input / 100M output per million requests): GPT-4 ≈ $12000/run, Claude Fable 5.1 (Adaptive Reasoning, Max Effort, Default Fallback) ≈ $7000/run. Claude Fable 5.1 (Adaptive Reasoning, Max Effort, Default Fallback) becomes more attractive at higher volume — the absolute per-token pricing difference compounds when you ship at scale.
Recommendation. Both models have legitimate use cases — the right answer depends on whether you are optimizing for benchmark ceiling, latency, or unit cost. Start with the cheaper / faster model, evaluate against your specific task, and only switch if the upgrade shows a meaningful lift.
Data from Artificial Analysis API — 12 benchmarks
Claude Fable 5.1 (Adaptive Reasoning, Max Effort, Default Fallback) is cheaper overall. Its blended price (3:1 input/output ratio) is $20.00/M tokens vs $37.50/M for GPT-4.
Claude Fable 5.1 (Adaptive Reasoning, Max Effort, Default Fallback) wins 2 out of 12 benchmarks compared to 0 for GPT-4. See the detailed benchmark chart above for per-category results.
Claude Fable 5.1 (Adaptive Reasoning, Max Effort, Default Fallback) generates tokens faster at 66 tok/s vs — tok/s. However, Claude Fable 5.1 (Adaptive Reasoning, Max Effort, Default Fallback) has lower time-to-first-token (282.34s vs —s).
Choose based on your priorities: Claude Fable 5.1 (Adaptive Reasoning, Max Effort, Default Fallback) for lower cost, Claude Fable 5.1 (Adaptive Reasoning, Max Effort, Default Fallback) for stronger benchmark performance, and Claude Fable 5.1 (Adaptive Reasoning, Max Effort, Default Fallback) for faster generation. For latency-sensitive apps, check the TTFT comparison above.