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GPT-5 Mini vs GPT-6.1 Sol

GPT-6.1 Sol: 81.7% average across five Vision Evals tasks (#9 of 69 models). We have not run GPT-5 Mini through Roboflow's Vision Evals, so there is no head-to-head score. Run both on your own image below.

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GPT-5 Mini vs GPT-6.1 Sol Comparison Table

Evals updated November 12, 2026Pricing updated November 13, 2026

PropertyGPT-5 MiniGPT-6.1 Sol
OrganizationOpenAIOpenAI
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateAug 2025Sep 2026
Context Window400K1.1M
ParametersUnknownundisclosed
LicenseProprietaryProprietary
Commercial usecommercial use per vendor termscommercial use per vendor terms
Pricing per 1M tokens
Input $/1M$0.250$2.00
Output $/1M$2.00$10.00
Vision Tasks
Promptable Concept SegmentationNot listedDemo
Both support 10 more tasks
Model Features
Both support 3 more features
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort
OverallNot evaluated
81.7%
Avg cost / sample–$0.0068
Avg speed / sample–12.82s
By task
Object Detection (low)–
80.8%
±0.1, Mean of 3 runs, range 80.7 to 80.9
$0.010
Object Detection (high)–
81.6%
±0.4, Mean of 3 runs, range 81.1 to 82.0
$0.022
Counting (low)–
78.8%
±3.4, Mean of 3 runs, range 75.7 to 82.4
$0.0037
Counting (high)–
80.2%
±3.4, Mean of 3 runs, range 77.0 to 83.8
$0.0057
Identification (low)–
89.6%
±1.6, Mean of 3 runs, range 87.5 to 90.6
$0.0025
Identification (high)–
88.5%
±1.6, Mean of 3 runs, range 87.5 to 90.6
$0.0030
OCR (low)–
75.8%
$0.0069
by category
Single value
58.3%
Transcription
95.7%
Structured JSON
89.5%
Text localization
74.4%
OCR (high)–
75.8%
$0.016
by category
Single value
56.5%
Transcription
96.0%
Structured JSON
90.4%
Text localization
76.7%
Reasoning (low)–
83.7%
±1.3, Mean of 3 runs, range 82.1 to 84.8
$0.0033
Reasoning (high)–
88.7%
±2.0, Mean of 3 runs, range 87.4 to 91.4
$0.0042

GPT-5 Mini vs GPT-6.1 Sol: Overview

GPT-5 Mini

GPT-5 Mini, released by OpenAI on August 7, 2025, is a mid-tier variant of the GPT-5 family that balances cost, speed, and capability. It is multimodal, supporting both text and image inputs, and offers a substantial input context window of ~400,000 tokens with output lengths up to ~128,000 tokens. While less powerful than the full GPT-5, it inherits its safety tuning, instruction-following improvements, and multimodal reasoning, making it a practical choice for developers who need large context handling without the expense of premium models.

GPT-5 Mini is optimized for affordability while retaining strong reasoning performance. Benchmarks show it outperforming earlier models such as GPT-4o on many multimodal and medical VQA tasks, though it lags behind GPT-5 on the most complex problems. Ideal use cases include prototyping, scalable content generation, document analysis, and mid-range reasoning tasks where efficiency and context capacity matter more than top-tier accuracy.

GPT-6.1 Sol

GPT-6.1 Sol is a reasoning model in OpenAI's GPT-6 series that accepts text and image input and returns text. It is an upgrade to GPT-6 Sol positioned to approach the intelligence of the larger GPT-6 Astra model on agentic coding, computer use, and professional knowledge work. The model exposes an adjustable reasoning effort control, ranging from low settings for simple turns to maximum settings for harder tasks, and can be driven with tool use enabled or disabled. It operates over a context window of roughly one million tokens and emits up to 128,000 output tokens in a single response, which supports long-running agent loops over large codebases and multi-document collections. Audio and video inputs are not supported.

OpenAI reports that GPT-6.1 Sol performs on par with or better than GPT-6 Sol across its image input safety evaluations, and that the share of responses containing a factual error at low reasoning effort falls from 11.4 percent to 7.7 percent.