GPT-5 Mini vs GPT-6 Sol
GPT-6 Sol: 76.9% average across five Vision Evals tasks (#13 of 65 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 Sol Comparison Table
Evals updated October 26, 2026Pricing updated November 7, 2026
| Property | GPT-5 Mini | GPT-6 Sol |
|---|---|---|
| Organization | OpenAI | OpenAI |
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | Aug 2025 | Sep 2026 |
| Context Window | 400K | 1.1M |
| Parameters | Unknown | undisclosed |
| License | Proprietary | Proprietary |
| Commercial use | commercial use per vendor terms | commercial use per vendor terms |
| Pricing per 1M tokens | ||
| Input $/1M | $0.250 | $2.00 |
| Output $/1M | $2.00 | $10.00 |
| Vision Tasks | ||
| Promptable Concept Segmentation | Not listed | Demo |
| Model Features | ||
Both support 3 more features | ||
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort | ||
| Overall | Not evaluated | 76.9% |
| Avg cost / sample | – | $0.0074 |
| Avg speed / sample | – | 10.20s |
| By task | ||
| Object Detection (low) | – | 74.7% ±0.7, Mean of 3 runs, range 74.1 to 75.5 |
| Object Detection (high) | – | 76.4% ±1.2, Mean of 3 runs, range 75.0 to 77.4 |
| Counting (low) | – | 76.6% ±2.0, Mean of 3 runs, range 74.3 to 78.4 |
| Counting (high) | – | 77.5% ±1.3, Mean of 3 runs, range 75.7 to 78.4 |
| Identification (low) | – | 93.8% ±0.0, Mean of 3 runs, range 93.8 to 93.8 |
| Identification (high) | – | 92.7% ±1.6, Mean of 3 runs, range 90.6 to 93.8 |
| OCR (low) | – | 66.7% |
| by category |
| |
| OCR (high) | – | 68.8% |
| by category |
| |
| Reasoning (low) | – | 72.6% ±3.6, Mean of 3 runs, range 69.5 to 76.8 |
| Reasoning (high) | – | 77.7% ±1.0, Mean of 3 runs, range 76.8 to 78.8 |
GPT-5 Mini vs GPT-6 Sol: Overview
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 Sol is a proprietary multimodal reasoning model from OpenAI, released on September 22, 2026 alongside GPT-6 Luna as an efficiency-oriented tier of the GPT-6 family that began with GPT-6 Astra. OpenAI states that Sol and Luna are trained with methods similar to those used for Astra, carrying the same work on professional tasks, factuality, coding, computer use, and alignment into models that run faster. Sol accepts text and image input and returns text output, and OpenAI documents a context window of roughly one million tokens together with a knowledge cutoff of April 20, 2026.
The model targets complex coding and agentic workflows and exposes a configurable reasoning effort setting with levels of none, low, medium, high, xhigh, and max, which trades latency and token consumption against answer quality. Its vision behavior covers image understanding tasks such as visual question answering, captioning, document and chart interpretation, and text recognition.