Compare/Claude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 Fallback) vs o1

Claude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 Fallback)vso1

Side-by-side comparison of pricing, 12 benchmarks, and generation speed.

Anthropic

Claude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 Fallback)

Input
$10/M
Output
$50/M
Speed
58 tok/s
TTFT
52.46s
OpenAI

o1

Input
$15/M
Output
$60/M
Speed
TTFT

Winner by Category

Cheaper
Claude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 Fallback)
Faster (tok/s)
Claude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 Fallback)
Lower Latency
o1
Benchmarks (6-4)
Claude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 Fallback)

Pricing Comparison

MetricClaude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 Fallback)o1
Input ($/M tokens)$10$15
Output ($/M tokens)$50$60
Cost for 1M input + 100K output tokens:
Claude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 Fallback)$15.00
o1$21.00

Speed Comparison

Output Speed (tokens/s) — higher is better
Claude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 Fallback)
58 tok/s
o1
Time to First Token (seconds) — lower is better
Claude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 Fallback)
52.46s
o1

Editorial Analysis

Verdict. Claude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 Fallback) wins the overall benchmark matchup 6–4 across 10 overlapping categories, but raw benchmark score is only one input to the decision.

Pricing. Both models sit in the premium bracket for output-token pricing. At 0.8× the per-million-token cost, Claude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 Fallback) is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). Claude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 Fallback) makes more sense when output volume is low and absolute reasoning quality justifies the premium.

Strengths. Claude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 Fallback) is strongest on GPQA Diamond (93%), Coding Index (76.5), IFBench (63%). o1 leads on MATH-500 (97%), MMLU-Pro (84%), GPQA Diamond (75%).

Speed. On throughput, Claude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 Fallback) generates tokens at 58 tok/s versus 0 tok/s — about 100% faster. On time-to-first-token, o1 responds in 0ms vs 52464ms, which matters most for chat-style UIs.

Provider. Anthropic and OpenAI sell to overlapping but distinct developer audiences: Anthropic tends to ship frontier reasoning models with premium positioning, while OpenAI 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): Claude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 Fallback) costs $1050.00 ($12600/year); o1 costs $1350.00 ($16200/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): Claude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 Fallback) ≈ $150.00/run, o1 ≈ $195.00/run. At agent/realtime scale (200M input / 100M output per million requests): Claude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 Fallback) ≈ $7000/run, o1 ≈ $9000/run. Claude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 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.

Head-to-head deltas

  • On throughput, Claude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 Fallback) is 5830.60× faster (58 tok/s vs 0 tok/s). For streaming chat or real-time agents this alone often flips the recommendation.
  • Time-to-first-token differs by 524640.0× — o1 responds in 0ms vs 52464ms. For interactive chat UIs this can matter more than raw benchmark wins.

Benchmark Comparison

Data from Artificial Analysis API — 12 benchmarks

Intelligence Index
59.923.4
Coding Index
76.539.7
Math Index
GPQA Diamond
92.6%74.7%
MMLU-Pro
84.1%
LiveCodeBench
67.9%
AIME 2025
MATH-500
97.0%
Humanity's Last Exam
53.3%7.7%
SciCode
60.2%35.8%
IFBench
63.5%70.3%
TerminalBench
62.9%12.9%
Claude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 Fallback)6 wins
4 winso1

Frequently Asked Questions

Which is cheaper, Claude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 Fallback) or o1?

Claude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 Fallback) is cheaper overall. Its blended price (3:1 input/output ratio) is $20.00/M tokens vs $26.25/M for o1.

Which model performs better on benchmarks?

Claude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 Fallback) wins 6 out of 12 benchmarks compared to 4 for o1. See the detailed benchmark chart above for per-category results.

Which is faster for real-time applications?

Claude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 Fallback) generates tokens faster at 58 tok/s vs 0 tok/s. However, o1 has lower time-to-first-token (0.00s vs 52.46s).

When should I use Claude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 Fallback) vs o1?

Choose based on your priorities: Claude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 Fallback) for lower cost, Claude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 Fallback) for stronger benchmark performance, and Claude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 Fallback) for faster generation. For latency-sensitive apps, check the TTFT comparison above.