Roboflow

GPT-5.6 Sol vs GPT-5.6 Terra

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

Compare GPT-5.6 Sol vs GPT-5.6 Terra live

Run the same image across every model that supports a task and compare their outputs side-by-side.

Detect and compare bounding boxes across models on the same image.

Open Object Detection in the full playground
OpenAIGPT-5.6 Sol
Run to compare this model.
OpenAIGPT-5.6 Terra
Run to compare this model.

Models in this comparison

GPT-5.6 Sol vs GPT-5.6 Terra on Vision Evals

GPT-5.6 Sol scores higher on all six Vision Evals tasks.

The widest gap is Counting, where GPT-5.6 Sol leads 74.3% to 65.8%.

Overall, GPT-5.6 Sol averages 79.0% (#16 of 60) against 73.8% (#24 of 60) for GPT-5.6 Terra.

GPT-5.6 Sol is cheaper ($0.0088 vs $0.0088 per sample), while GPT-5.6 Terra is faster (7.7s vs 10.3s per sample).

GPT-5.6 SolGPT-5.6 Terra

GPT-5.6 Sol vs GPT-5.6 Terra Comparison Table

Evals updated October 7, 2026Pricing updated October 8, 2026

PropertyGPT-5.6 SolGPT-5.6 Terra
OrganizationOpenAIOpenAI
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateJul 2026Jul 2026
Context Window1.5M1.1M
ParametersUnknownUnknown
LicenseProprietaryProprietary
Pricing per 1M tokens
Input $/1M$2.00$2.00
Output $/1M$10.00$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 6 vision tasks, pooled at low effort
Overall
79.0%
73.8%
Avg cost / sample$0.0088$0.0088
Avg speed / sample10.32s7.74s
By task
Object Detection (low)
68.4%
±0.7, Mean of 3 runs, range 67.9 to 69.3
$0.015
60.6%
±0.2, Mean of 3 runs, range 60.3 to 60.7
$0.014
Object Detection (high)
68.4%
±0.8, Mean of 3 runs, range 67.7 to 69.3
$0.035
61.3%
±0.4, Mean of 3 runs, range 60.8 to 61.6
$0.026
Counting (low)
74.3%
±1.4, Mean of 3 runs, range 73.0 to 75.7
$0.0049
65.8%
±2.0, Mean of 3 runs, range 63.5 to 67.6
$0.0056
Counting (high)
76.1%
±2.0, Mean of 3 runs, range 74.3 to 78.4
$0.0078
62.6%
±2.7, Mean of 3 runs, range 59.5 to 64.9
$0.0076
Identification (low)
89.6%
±4.7, Mean of 3 runs, range 84.4 to 93.8
$0.0028
86.5%
±1.6, Mean of 3 runs, range 84.4 to 87.5
$0.0034
Identification (high)
92.7%
±1.6, Mean of 3 runs, range 90.6 to 93.8
$0.0030
86.5%
±3.1, Mean of 3 runs, range 84.4 to 90.6
$0.0038
OCR (low)
90.7%
±0.1, Mean of 3 runs, range 90.6 to 90.7
$0.011
89.4%
±0.8, Mean of 3 runs, range 88.8 to 90.3
$0.012
OCR (high)
90.2%
±0.2, Mean of 3 runs, range 90.0 to 90.4
$0.025
89.4%
±0.6, Mean of 3 runs, range 88.8 to 90.1
$0.023
Data Extraction (low)
84.9%
±1.0, Mean of 3 runs, range 83.5 to 85.6
$0.0033
79.7%
±0.5, Mean of 3 runs, range 79.4 to 80.4
$0.0038
Data Extraction (high)
86.9%
±0.5, Mean of 3 runs, range 86.6 to 87.6
$0.0041
80.4%
±1.0, Mean of 3 runs, range 79.4 to 81.4
$0.0043
Reasoning (low)
66.0%
±2.6, Mean of 3 runs, range 63.6 to 68.9
$0.0043
60.9%
±2.0, Mean of 3 runs, range 59.6 to 63.6
$0.0051
Reasoning (high)
71.7%
±1.3, Mean of 3 runs, range 70.2 to 72.8
$0.0061
65.3%
±1.0, Mean of 3 runs, range 64.2 to 66.2
$0.0067

GPT-5.6 Sol vs GPT-5.6 Terra: Overview

GPT-5.6 Sol

GPT-5.6 Sol is the flagship model in OpenAI's GPT-5.6 family, which also includes Terra (a balanced everyday-work tier) and Luna (a fast, cost-efficient tier). Sol is designed for demanding reasoning, long-horizon agentic workflows, software engineering, computer use, scientific research, and cybersecurity tasks. It introduces two new capability modes: a "max" reasoning effort setting that allocates additional compute time for difficult problems, and an "ultra" mode that coordinates multiple subagents in parallel to accelerate complex, multi-step work. The model supports native multimodal input, allowing it to process screenshots, diagrams, charts, documents, and photographs alongside text. A reported context window of approximately 1.5 million tokens enables processing of large codebases, lengthy research documents, and extended agentic sessions.

GPT-5.6 Sol was announced on June 26, 2026, initially in a limited preview for trusted partners, and reached general availability on July 9, 2026. On the Agents' Last Exam benchmark, which evaluates long-running professional workflows across 55 fields, Sol scores 53.6. On Terminal-Bench 2.1, which tests command-line agentic coding workflows, Sol Ultra achieves 91.9%. The model also demonstrates gains in life sciences evaluations, including long-horizon genomics and quantitative biology analyses. OpenAI paired the release with its most extensive safety evaluation to date, combining human red teaming with large-scale automated testing, and classified Sol as High capability in both cybersecurity and biological risk under its Preparedness Framework, though it does not cross the Critical threshold in either category.

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, GPT-5.6 Sol performed better. It scores higher on all six vision tasks and averages 79.0% (#16 of 60) against 73.8% (#24 of 60) 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 Counting benchmark at low effort, GPT-5.6 Sol leads with 74.3% against 65.8%. This is the widest gap between the two models across the benchmark's tasks.

GPT-5.6 Sol is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0088 per sample against $0.0088. GPT-5.6 Sol is priced at $2.00 per 1M input tokens and $10.00 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.

GPT-5.6 Terra is faster. Across Roboflow's Vision Evals it averaged 7.7s per inference against 10.3s. 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 OCR and image captioning in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.