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Claude Fable 5.1 vs GPT-5.6 Terra

Compare Claude Fable 5.1 and GPT-5.6 Terra side-by-side. See how these vision models stack up in Object Detection, OCR, Image Captioning, Open Prompt, and Classification.

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AnthropicClaude Fable 5.1
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OpenAIGPT-5.6 Terra
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Models in this comparison

Claude Fable 5.1 vs GPT-5.6 Terra on Vision Evals

Claude Fable 5.1 scores higher on all five Vision Evals tasks.

The widest gap is OCR, where Claude Fable 5.1 leads 72.9% to 56.3%.

Overall, Claude Fable 5.1 averages 74.7% (#14 of 63) against 66.0% (#26 of 63) for GPT-5.6 Terra.

GPT-5.6 Terra is cheaper ($0.010 vs $0.039 per sample), while Claude Fable 5.1 is faster (8.3s vs 9.5s per sample).

Claude Fable 5.1GPT-5.6 Terra

Claude Fable 5.1 vs GPT-5.6 Terra Comparison Table

Evals updated October 13, 2026Pricing updated October 17, 2026

PropertyClaude Fable 5.1GPT-5.6 Terra
OrganizationAnthropicOpenAI
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateSep 2026Jul 2026
Context Window1.0M1.1M
ParametersUnknownUnknown
LicenseProprietaryProprietary
Commercial usecommercial use per vendor termscommercial use per vendor terms
Pricing per 1M tokens
Input $/1M$10.00$2.00
Output $/1M$50.00$12.00
Vision Tasks
CaptioningDemoDemo
Chart Question AnsweringSupportedSupported
ClassificationDemoDemo
Document Question AnsweringSupportedSupported
Image TaggingSupportedSupported
Multi-Label ClassificationSupportedSupported
Object DetectionDemoDemo
OCRDemoDemo
Vision LanguageSupportedSupported
Visual Question AnsweringDemoDemo
Model Features
Foundation VisionSupportedSupported
LLMs with Vision CapabilitiesSupportedSupported
Multimodal VisionSupportedSupported
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort
Overall
74.7%
66.0%
Avg cost / sample$0.039$0.010
Avg speed / sample8.35s9.52s
By task
Object Detection (low)
61.4%
±0.5, Mean of 3 runs, range 61.0 to 62.0
$0.060
60.6%
±0.2, Mean of 3 runs, range 60.3 to 60.7
$0.014
Object Detection (high)
65.0%
±0.4, Mean of 3 runs, range 64.6 to 65.3
$0.078
61.3%
±0.4, Mean of 3 runs, range 60.8 to 61.6
$0.026
Counting (low)
69.4%
±2.7, Mean of 3 runs, range 66.2 to 71.6
$0.019
65.8%
±2.0, Mean of 3 runs, range 63.5 to 67.6
$0.0056
Counting (high)
73.0%
±4.7, Mean of 3 runs, range 67.6 to 77.0
$0.023
62.6%
±2.7, Mean of 3 runs, range 59.5 to 64.9
$0.0076
Identification (low)
97.9%
±1.6, Mean of 3 runs, range 96.9 to 100.0
$0.013
86.5%
±1.6, Mean of 3 runs, range 84.4 to 87.5
$0.0034
Identification (high)
96.9%
±3.1, Mean of 3 runs, range 93.8 to 100.0
$0.014
86.5%
±3.1, Mean of 3 runs, range 84.4 to 90.6
$0.0038
OCR (low)
72.9%
$0.039
56.3%
$0.011
by category
Single value
64.3%
Transcription
84.7%
Structured JSON
89.2%
Text localization
46.5%
Single value
36.1%
Transcription
79.9%
Structured JSON
76.8%
Text localization
42.3%
OCR (high)
75.3%
$0.051
56.9%
$0.021
by category
Single value
69.1%
Transcription
95.2%
Structured JSON
89.5%
Text localization
43.4%
Single value
37.4%
Transcription
80.2%
Structured JSON
77.3%
Text localization
41.9%
Reasoning (low)
72.0%
±1.3, Mean of 3 runs, range 70.9 to 73.5
$0.019
60.9%
±2.0, Mean of 3 runs, range 59.6 to 63.6
$0.0051
Reasoning (high)
73.1%
±2.0, Mean of 3 runs, range 71.5 to 75.5
$0.028
65.3%
±1.0, Mean of 3 runs, range 64.2 to 66.2
$0.0067

Claude Fable 5.1 vs GPT-5.6 Terra: Overview

Claude Fable 5.1

Claude Fable 5.1 is a proprietary multimodal model from Anthropic in the Mythos-class tier of the Claude 5 family, positioned above Claude Opus for demanding reasoning and long-horizon agentic work. It accepts text and images as input and returns text, with a one million token context window and a maximum output of 128 thousand tokens. Adaptive thinking is always on, and an effort parameter controls how much reasoning the model applies to a given request. Anthropic reports a reliable knowledge and training data cutoff of June 2026. Claude Fable 5.1 and Claude Mythos 5.1 share the same underlying model; the difference between them is the set of safety classifiers applied to dual-use cybersecurity and biology requests.

On the vision side, Anthropic documents improvements in reading dense charts, financial filings, and tables nested inside PDF documents, which extends the model toward document understanding, chart question answering, and spreadsheet and slide work. Reported evaluations cover agentic scientific research on Terminal-Bench-Science 0.1, agentic coding on Terminal-Bench 4.0, computer use on OSWorld 2.0, and multidisciplinary reasoning on Humanity's Last Exam. Model weights are not published.

GPT-5.6 Terra

GPT-5.6 Terra is the mid-tier reasoning model in OpenAI's GPT-5.6 family, which also includes the flagship Sol and the lightweight Luna. Introduced in a limited preview on June 26, 2026, and made broadly available on July 9, 2026, Terra accepts text and image input and produces text output, supporting vision, function calling, tool use, and agentic workflows. It is designed as a balanced option for everyday professional and production workloads — including coding assistance, document analysis, customer support, and multi-step agent tasks — where both output quality and cost efficiency matter. OpenAI positions Terra as delivering performance competitive with GPT-5.5 at approximately half the price, with a context window of around 1,050,000 tokens. On Terminal-Bench 2.1, Terra scores 84.3%, matching Claude Fable 5 on that benchmark. Under OpenAI's Preparedness Framework, Terra is rated High for cybersecurity and biological capabilities, meaning it demonstrates meaningful capability in those domains without reaching the Critical threshold.

GPT-5.6 introduces a new naming convention in which the generation number (5.6) is paired with a durable capability tier name (Sol, Terra, or Luna), allowing each tier to advance on its own schedule. Terra carries the API identifier gpt-5.6-terra and supports the same reasoning effort controls available across the family, including adjustable reasoning depth. The model includes prompt caching with explicit cache breakpoints and a 30-minute minimum cache life, with cache writes billed at 1.25x the uncached input rate and cache reads receiving a 90% discount. GPT-5.6 Terra is a proprietary, closed-weights model served through the OpenAI API, Codex, and ChatGPT.

Frequently Asked Questions

On Roboflow's Vision Evals, Claude Fable 5.1 performed better. It scores higher on all five vision tasks and averages 74.7% (#14 of 63) against 66.0% (#26 of 63) for GPT-5.6 Terra. These scores measure vision capabilities only; either model may perform differently on work outside this benchmark's tasks.

Yes. On the Vision Evals OCR benchmark at low effort, Claude Fable 5.1 leads with 72.9% against 56.3%. This is the widest gap between the two models across the benchmark's tasks.

GPT-5.6 Terra is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.010 per sample against $0.039. Claude Fable 5.1 is priced at $10.00 per 1M input tokens and $50.00 per 1M output; GPT-5.6 Terra is priced at $2.00 per 1M input tokens and $12.00 per 1M output. Actual costs depend on your image sizes, prompts, and output length.

Claude Fable 5.1 is faster. Across Roboflow's Vision Evals it averaged 8.3s per inference against 9.5s. Latency varies with image size, prompt length, and provider load, so treat these as relative rather than guaranteed figures.

Yes. The comparison demo on this page runs both models on the same image side by side for object detection and OCR in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.