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Head-to-head comparison

Claude Fable 5.1 vs GPT-5.6 Terra

Claude Fable 5.1 (Anthropic) and GPT-5.6 Terra (OpenAI) compared on the ModelCap Index, API price, context window, provider availability, weight access and every public benchmark board they share. Figures are the same ones shown on the live rankings; nothing here is a hidden score.

Snapshot as of 18 October 2026

As of 18 October 2026, Claude Fable 5.1 holds the stronger ModelCap Index position (#3 vs #28); and GPT-5.6 Terra is 4.2× cheaper per output token ($12.00/1M vs $50.00/1M).

Which should you choose?

Choose Claude Fable 5.1 if…

  • you want the stronger overall ModelCap Index position — #3 against #28 (85.8 vs 75.3 points).
  • you want provider choice — 4 listed API providers against 3.
  • Arena text is your yardstick — 1502 against 1466.
  • Arena coding is your yardstick — 1537 against 1517.
  • LMArena Agent is your yardstick — 14.0% against 0.4%.
  • ARC-AGI-2 is your yardstick — 90.0% against 83.9%.
  • AA Intelligence Index is your yardstick — 53.4 against 42.1.
  • AA Terminal-Bench 2.1 is your yardstick — 91.4% against 88.0%.
  • AA Humanity's Last Exam is your yardstick — 59.1% against 42.9%.
  • Terminal-Bench 4.0 is your yardstick — 57.9% against 21.5%.
  • you want the more recently listed model — Claude Fable 5.1 was listed 1 September 2026, GPT-5.6 Terra 9 July 2026.

Choose GPT-5.6 Terra if…

  • API cost matters — $12.00/1M output tokens against $50.00/1M, about 4.2× cheaper.
  • your workload is prompt-heavy — input tokens cost $2.00/1M against $10.00/1M.

Claude Fable 5.1 vs GPT-5.6 Terra: specs, pricing and context

Specification comparison of Claude Fable 5.1 and GPT-5.6 Terra
FieldClaude Fable 5.1AnthropicGPT-5.6 TerraOpenAI
ModelCap Index position#3#28
Index score85.875.3
EvidenceMeasuredMeasured
Input price / 1M tokens$10.00$2.00
Output price / 1M tokens$50.00$12.00
Context window1M tokens1M tokens
Declared route output cap128K128K
API providers listed43
Weight accessNo linked weightsNo linked weights
Input modalitiesText, Image, FileFile, Image, Text
First listed1 September 20269 July 2026
PublisherAnthropicOpenAI

Evidence: 4 public benchmark observations across 4 boards · 5 public benchmark observations across 5 boards. Prices are the lowest listed API offer per million tokens observed on the OpenRouter catalogue.

Benchmark scores: Claude Fable 5.1 vs GPT-5.6 Terra

Public benchmark boards where Claude Fable 5.1 or GPT-5.6 Terra has a published result
BoardClaude Fable 5.1GPT-5.6 TerraLeads
Arena textArena (LMArena)15021496–1508Max14661462–1471X-HighClaude Fable 5.1
Arena codingArena (LMArena)15371526–1549Max15171510–1523X-HighClaude Fable 5.1
LMArena AgentLMArena14.0%12.0%–16.0%Max0.4%-0.9%–1.7%X-HighClaude Fable 5.1
ARC-AGI-2ARC Prize Foundation90.0%Max83.9%MaxClaude Fable 5.1
ARC-AGI-3ARC Prize Foundation—0.8%MaxOnly one result
AA Intelligence IndexArtificial Analysis53.4Reasoning42.1MaxClaude Fable 5.1
AA Terminal-Bench 2.1Artificial Analysis91.4%Reasoning88.0%MaxClaude Fable 5.1
AA τ²-Bench TelecomArtificial Analysis—86.3%MaxOnly one result
AA Humanity's Last ExamArtificial Analysis59.1%Reasoning42.9%MaxClaude Fable 5.1
Terminal-Bench 4.0Terminal-Bench (Laude Institute)57.9%54.1%–61.6%Claude Code · Max21.5%18.3%–24.8%Codex · MaxClaude Fable 5.1

Scores are the sources' own published figures for each model's best evaluated configuration; ModelCap never re-runs a benchmark.

Want a different pairing? Open the interactive comparison tool to swap either model for any current ranked language model.

Claude Fable 5.1 vs GPT-5.6 Terra: common questions

Is Claude Fable 5.1 better than GPT-5.6 Terra?

Claude Fable 5.1 ranks higher on the ModelCap Index as of 18 October 2026: #3 against #28. That is a capability ranking built from public benchmark evidence with published uncertainty; whether it is "better" for you also depends on price, context and where you can run it. Their published uncertainty intervals do not overlap, but the aggregate Index does not predict performance on every task; compare the relevant benchmark configurations before choosing.

Is Claude Fable 5.1 cheaper than GPT-5.6 Terra?

GPT-5.6 Terra is cheaper on output tokens: $12.00/1M against $50.00/1M. Input tokens are $10.00/1M for Claude Fable 5.1 and $2.00/1M for GPT-5.6 Terra. Prices are the lowest listed API offer ModelCap observed, in USD per million tokens. For 1,000 requests with 2,000 input and 500 output tokens each (2M input + 0.5M output), the listed-rate estimate is $45.00 for Claude Fable 5.1 versus $10.00 for GPT-5.6 Terra. GPT-5.6 Terra costs 77.8% less in this scenario. This excludes caching, batch discounts, prompt-length tiers, tool charges and retries; verify the selected endpoint before budgeting.

Which has the bigger context window, Claude Fable 5.1 or GPT-5.6 Terra?

Both publish a 1M-token context window. OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified.

Which is better for coding, Claude Fable 5.1 or GPT-5.6 Terra?

Arena coding: Claude Fable 5.1 1537, GPT-5.6 Terra 1517 — Claude Fable 5.1 leads. AA Terminal-Bench 2.1: Claude Fable 5.1 91.4%, GPT-5.6 Terra 88.0% — Claude Fable 5.1 leads. Terminal-Bench 4.0: Claude Fable 5.1 57.9%, GPT-5.6 Terra 21.5% — Claude Fable 5.1 leads.

Are Claude Fable 5.1 and GPT-5.6 Terra open-weight models?

Claude Fable 5.1: No linked weights. GPT-5.6 Terra: No linked weights. Open weights mean the checkpoint can be downloaded and self-hosted under its licence. A missing weight link does not identify every API or chat product that offers a model.

Where can I run Claude Fable 5.1 and GPT-5.6 Terra?

ModelCap currently lists 4 API providers for Claude Fable 5.1 and 3 for GPT-5.6 Terra, from the OpenRouter catalogue snapshot the site serves; each model page lists the providers and their prices.

How current is this Claude Fable 5.1 vs GPT-5.6 Terra comparison?

Every figure and ModelCap Index position comes from the same published snapshot dated 18 October 2026. Publication and page updates happen separately; use the snapshot date shown on the page.

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