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- Claude Fable 5 vs. GPT-6.1 Terra
Claude Fable 5vs.GPT-6.1 Terra
Which one is better?
Level in the overall index: the gap is too small for a clear winner. GPT-6.1 Terra is cheaper: Claude Fable 5 costs 10 times as much per token.
Claude Fable 5
Rank 10 to 14
GPT-6.1 Terra
Rank 12 to 27
Claude Fable 5
fairly slow
GPT-6.1 Terra
fairly slow
Claude Fable 5
expensive
GPT-6.1 Terra
fairly expensive
Claude Fable 5
- Subscription
At Anthropic from €107.10 a month (Claude Max 5x). Through other providers from ≈ €10.60 a month (Zed Pro). 24 plans in Germany.
- Via API
$10 input, $50 output per 1M tokens, unchanged since our price tracking began on Aug 14, 2026.
- Note
- There is a successor: Claude Fable 5.1 (rank 2 to 5, same price).
GPT-6.1 Terra
- Subscription
Subscriptions in Germany: n/a
- Via API
$1 input, $5 output per 1M tokens.
Overall index with data through Oct 29, 2026 · Prices from Oct 29, 2026 · Speed: measured by Artificial Analysis · Subscriptions as of Oct 24, 2026 · Subscription prices incl. VAT
Where is the difference?
Values from 0 to 100 per task area. We only name a winner when the gap is large enough and there are enough tests.
Fable 5 ahead: 3GPT-6.1 Terra ahead: 1level: 2too little data: 4of 10 areas
Show 2 more areas that do not count toward the overall index
See for yourself: same task, one attempt
The same prompt for both models. We show the latest attempt without fixes; it does not count toward the overall index.
Pelican on a bicycle
A community classic for free-form SVG drawing.
Claude Fable 5

Reasoning (requested): high
Current attempt
- Run date
- Sep 7, 2026
- API provider
- openrouter
- Requested API model
- anthropic/claude-fable-5
- API model reported in response
- anthropic/claude-fable-5
- Reasoning setting
- high
- Pinned endpoint
- Anthropic | anthropic/claude-5-fable-20260609
- Temperature
- Provider default
- Token limit including reasoning
- 8,192 tokens
- Test protocol
- community-visual-tests-v1
- Technical checks
- Passed, not a quality rating
- Response time
- 53.1 s
Visually reviewed. This individual test does not establish overall model quality.
GPT-6.1 Terra
Not tested yet
Prompt and test conditions
Generate an SVG of a pelican riding a bicycle
Token limit including reasoning: 8,192 tokens
Task origin (Simon Willison)SVG short test
There is no shared test round for this selection. Results from different rounds are not mixed.
All data side by side
The better value is bold. For the overall index only when the gap is clear.
| Metric | Claude Fable 5 | GPT-6.1 Terra |
|---|---|---|
| Intelligence | ||
| Overall index0 to 100, higher is better | 80 | 67 |
| Rank | Rank 10 to 14 of 95 | Rank 12 to 27 of 95 |
| Price per 1M tokens | ||
| Inputwhat you send | $10 | $1above 272,000 tokens: $2 |
| Outputwhat the model writes | $50 | $5above 272,000 tokens: $7.50 |
| Speed | ||
| Tokens per second | 70 | 91 |
| Technical | ||
| Context windowhow much text the model reads at once | 1 M tokens≈ 1,500 A4 pages | 1.05 M tokens≈ 1,580 A4 pages |
| Knowledge cutoff | January 2026 | Jun 1, 2026 |
| Released | Jun 9, 2026 | Oct 26, 2026 |
| Availability | Active | Active |
| Open weights | no | no |
- GPT-6.1 Terra, 12-hour cache write: The table's cache-write rate covers 30-minute retention. With 12-hour retention it is $2.50 per 1M tokens through 272,000 input tokens, $5 above. Source
- GPT-6.1 Terra, Long-context billing: Above 272,000 input tokens, the higher rates apply to the entire request. Input and cache rates double, while output costs 1.5 times the standard rate. Source
- GPT-6.1 Terra, Batch and Flex pricing: 50% off standard pricing Source
- GPT-6.1 Terra, Fast pricing: Fast mode costs twice the standard price Source
- GPT-6.1 Terra, Regional processing: 10% surcharge over standard processing Source
Prices without caching or batch discounts · Page count as a rule of thumb from Artificial Analysis
Shared benchmarks
Single results from the same benchmark version, task and metric. A value is bold only with the same test setup and a clear gap.
A: Claude Fable 5B: GPT-6.1 Terra
Show 31 more benchmarks
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