Read alongside the Opus 5 comparison
Since Opus 5 shipped on July 24, 2026 the default recommendation for most work is now Opus 5 at half the price. This Fable 5 vs GPT-5.5 page still stands for the models it compares — but for teams not tied to OpenAI, check the Opus 5 comparison before deciding a default.
Fable 5 vs Opus 5Updated August 2026
Claude Fable 5 vs GPT-5.5
Fable 5 out-scores GPT-5.5 on every published agentic-coding benchmark and carries 2.5x the context window, but at roughly double the list price. Here is the sourced comparison and which model to pick per job.
The short answer
Fable 5 leads GPT-5.5 on every published coding and agentic benchmark — SWE-bench Pro 80.3% vs 58.6%, FrontierCode 29.3% vs 5.7% — and has 2.5x the context (1M vs 400K), at a higher price ($10/$50 vs $5/$30). GPT-5.5 is cheaper and strong inside the OpenAI ecosystem, but trails on agentic coding and long-context work. Choose Fable 5 for coding and long-context; choose GPT-5.5 for price or OpenAI-ecosystem lock-in.
Specs and pricing side by side
Fable 5 figures come from src/lib/model-pricing.ts (last verified August 4, 2026 against Anthropic's pricing docs). GPT-5.5 is OpenAI's published list pricing as of August 2026.
| Claude Fable 5 | GPT-5.5 | |
|---|---|---|
| Price (input / output per MTok) | $10 / $50 | $5 / $30 |
| Context window | 1M | 400K |
| Max output | 128K | Not confirmed (as of August 2026) |
| Data retention | 30 days, mandatory — ZDR agreements do not apply | Standard OpenAI enterprise retention stance |
Benchmarks: where Fable 5 leads
Every row is labeled: Anthropic (Fable 5) and OpenAI (GPT-5.5) results are lab-published, run under settings each vendor chose — treat them as directional, and compare only within the same harness.
| Claude Fable 5 | GPT-5.5 | Source | |
|---|---|---|---|
| SWE-bench Pro (agentic coding) | 80.3% | 58.6% | |
| FrontierCode (Diamond) | 29.3% | 5.7% | |
| GDPval (knowledge work) | 1932 | 1769 | |
| OSWorld (computer use) | 85.0% | 78.7% |
Sources: Anthropic's Fable 5 launch table (June 9, 2026) and OpenAI's published GPT-5.5 results, as of August 2026. Cross-lab benchmarks are run by the labs themselves under their own settings; an independent reproduction of each figure has not been published as of this writing.
Decision guide: which model, for which job
Five decision rows based on the published figures and both vendors' product posture.
You're doing agentic / frontier-hard coding
Fable 5 leads on every published row — SWE-bench Pro 80.3% vs 58.6%, and FrontierCode 29.3% vs 5.7%, where GPT-5.5 effectively can't play. Fable 5.
You need 1M-context / full-repo work
Fable 5's 1M window vs GPT-5.5's 400K is a real difference for whole-repo reads and long-context analysis. If the full repo has to fit in one context, Fable 5.
You're optimizing cost at scale
GPT-5.5 at $5/$30 is roughly half Fable 5's $10/$50 list. For high-volume production where both clear the quality bar, price decides. GPT-5.5.
You're locked into the OpenAI ecosystem
Structured outputs, Assistants tooling and existing GPT integrations carry switching costs no benchmark offsets. If you're already built on OpenAI, GPT-5.5.
Your compliance policy requires retention
Fable 5's mandatory 30-day retention is exactly the log-retention some policies require, and it excludes zero-data-retention agreements. GPT-5.5's privacy posture differs. Fable 5.
Decision guide as of August 2026, based on published benchmarks and both vendors' product posture. Your own evals on your own workloads beat any default.
The retention difference
Fable 5 requires a mandatory 30-day retention window for safety monitoring, and zero-data-retention agreements do not apply to it. GPT-5.5 follows OpenAI's standard enterprise retention posture. For teams with a hard data-retention or ZDR requirement, this can be the deciding factor — not the benchmark table.
Price your own workload before you pick
Run your real monthly volume through the calculator at both price points — with caching and batching stacked, the gap between $10/$50 and $5/$30 is workload-specific.