{"id":19719,"date":"2026-09-23T11:17:35","date_gmt":"2026-09-23T15:17:35","guid":{"rendered":"https:\/\/wp.glbgpt.com\/?p=19719"},"modified":"2026-09-23T11:17:37","modified_gmt":"2026-09-23T15:17:37","slug":"gpt-6-sol-review","status":"publish","type":"post","link":"https:\/\/wp.glbgpt.com\/nl\/hub\/gpt-6-sol-review","title":{"rendered":"GPT-6 Sol-recensie: prijzen, context, API-limieten en voor wie het geschikt is"},"content":{"rendered":"<p class=\"wp-block-paragraph\"><strong>Snel antwoord:<\/strong> GPT-6 Sol is OpenAI&#8217;s complex coding and agentic workflows model. The official API lists $2.00 per 1M input tokens and $10.00 per 1M output tokens at Standard rates, with a 1.05M-token context window and 128K maximum output. GlobalGPT currently lists GPT-5.6 Sol and GPT-5.6 Luna rather than exact GPT-6 routes, so the platform naming must be checked separately from OpenAI&#8217;s API model ID.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">OpenAI positions GPT-6 Sol for complex coding and agentic workflows. That phrase is provider positioning, not a measured quality score. This review translates the published specification into buying and architecture decisions, then records public reaction with attribution. We also ran a scoped compatibility-API test with the model ID, route, prompt set, raw output, and usage retained. The task results are shown below as one observed run, not as an official benchmark.<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img alt=\"\" fetchpriority=\"high\" decoding=\"async\" width=\"2558\" height=\"1366\" src=\"https:\/\/wp.glbgpt.com\/wp-content\/uploads\/2026\/09\/\u5fae\u4fe1\u622a\u56fe_20260923225247.jpg\" class=\"wp-image-19726\"\/><\/figure>\n\n\n\n<div class=\"wp-block-buttons is-content-justification-center is-layout-flex wp-container-core-buttons-is-layout-3e41869c wp-block-buttons-is-layout-flex\">\n<div class=\"wp-block-button\"><a class=\"wp-block-button__link has-background wp-element-button\" href=\"https:\/\/www.glbgpt.com\/home\/gpt-6-sol?inviter=hub_corner_popup_gpt-6-sol&amp;login=1\" style=\"background:linear-gradient(135deg,rgb(6,147,227) 54%,rgb(155,81,224) 100%)\"><strong>Try GPT-6 Sol on GlobalGPT<\/strong><\/a><\/div>\n<\/div>\n\n\n\n<nav aria-label=\"Inhoudsopgave\" style=\"box-sizing:border-box;margin:24px 0;padding:18px;border:1px solid #b8d9d5;border-radius:8px;background:#f2f8f7;color:#172a2d;font-family:Arial,sans-serif\"><strong style=\"display:block;color:#086b72\">Inhoudsopgave<\/strong><ol style=\"columns:2;column-gap:28px;margin:10px 0 0;padding-left:22px;line-height:1.75\"><li><a href=\"#verdict\">Kort oordeel<\/a><\/li><li><a href=\"#specs\">In \u00e9\u00e9n oogopslag<\/a><\/li><li><a href=\"#pricing\">Pricing and 272K rule<\/a><\/li><li><a href=\"#api-fit\">API fit and limits<\/a><\/li><li><a href=\"#use-cases\">What the specs imply<\/a><\/li><li><a href=\"#hands-on\">Praktische API-test<\/a><\/li><li><a href=\"#reactions\">Public reactions<\/a><\/li><li><a href=\"#globalgpt\">GlobalGPT naming note<\/a><\/li><li><a href=\"#choice\">Who should choose it?<\/a><\/li><li><a href=\"#faq\">FAQ<\/a><\/li><\/ol><\/nav>\n\n\n\n<h2 id=\"verdict\" class=\"wp-block-heading\">Kort oordeel<\/h2>\n\n\n\n<section style=\"box-sizing:border-box;margin:24px 0;padding:18px 20px;border-left:5px solid #087f8c;background:#f2f8f7;color:#172a2d;font-family:Arial,sans-serif\"><strong style=\"display:block;color:#087f8c;font-size:12px;letter-spacing:.04em;text-transform:uppercase\">Conclusie<\/strong><p style=\"margin:7px 0 0;line-height:1.65\">Sol is the model to examine when the work is genuinely complex, tool-heavy, or code-centric and the higher token bill is acceptable. The evidence here combines official documentation with a scoped compatibility-API observation, not a controlled benchmark, so the responsible verdict is fit, not a universal ranking.<\/p><\/section>\n\n\n\n<p class=\"wp-block-paragraph\">The most useful distinction is not simply &#8220;smart&#8221; versus &#8220;fast.&#8221; It is workload shape. GPT-6 Sol has the same headline context and output ceilings as its sibling, but its positioning and price make a different operating point sensible. Compare the broader <a href=\"https:\/\/www.glbgpt.com\/hub\/best-ai-models\/\">AI model selection guide<\/a> en de <a href=\"https:\/\/www.glbgpt.com\/hub\/best-ai-model-for-coding\/\">beste AI-model voor codering<\/a> guide when the task spans more than one provider.<\/p>\n\n\n\n<h2 id=\"specs\" class=\"wp-block-heading\">GPT-6 Sol at a glance<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">The table below follows the current <a href=\"https:\/\/developers.openai.com\/api\/docs\/models\/gpt-6-sol\">official GPT-6 Sol model page<\/a>. Context capacity is not the same thing as a recommended prompt size, and the maximum input is separate from the headline context window.<\/p>\n\n\n\n<div style=\"overflow-x:auto;margin:24px 0;border:1px solid #b8d9d5;border-radius:8px\"><table style=\"width:100%;min-width:760px;border-collapse:collapse;background:#fff;color:#172a2d;font-family:Arial,sans-serif\"><thead><tr style=\"background:#087f8c;color:#fff\"><th style=\"padding:11px;text-align:left;vertical-align:top\">Veld<\/th><th style=\"padding:11px;text-align:left;vertical-align:top\">Official value<\/th><\/tr><\/thead><tbody><tr style=\"background:#fff\"><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">Official API ID<\/td><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\"><code>gpt-6-sol<\/code><\/td><\/tr><tr style=\"background:#f2f8f7\"><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">Provider positioning<\/td><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">complex coding and agentic workflows<\/td><\/tr><tr style=\"background:#fff\"><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">Contextvenster<\/td><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">1.050.000 tokens<\/td><\/tr><tr style=\"background:#f2f8f7\"><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">Maximale invoer<\/td><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">922.000 tokens<\/td><\/tr><tr style=\"background:#fff\"><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">Maximaal vermogen<\/td><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">128.000 tokens<\/td><\/tr><tr style=\"background:#f2f8f7\"><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">Kennis cutoff<\/td><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">April 20, 2026<\/td><\/tr><tr style=\"background:#fff\"><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">Invoer \/ uitvoer<\/td><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">Text + image input \/ text output<\/td><\/tr><tr style=\"background:#f2f8f7\"><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">Redenering<\/td><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">none, low, medium, high, xhigh, max<\/td><\/tr><tr style=\"background:#fff\"><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">Supported endpoints<\/td><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">Chat Completions, Responses, Batch<\/td><\/tr><\/tbody><\/table><\/div>\n\n\n\n<p class=\"wp-block-paragraph\">Both sibling models support structured outputs, function calling, streaming, prompt caching, image input, file search, and web search in the documented feature set. The exact tool behavior still depends on endpoint, account, and request configuration; do not infer a successful tool run from a capability checkbox.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">For family-level context, the <a href=\"https:\/\/www.glbgpt.com\/hub\/gpt-6-astra-review\/\">Recensie van de GPT-6 Astra<\/a> shows how a related GPT-6 article separates provider documentation, platform routes, and attributed reactions.<\/p>\n\n\n\n<h2 id=\"pricing\" class=\"wp-block-heading\">GPT-6 Sol pricing and the 272K rule<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">At Standard rates, the <a href=\"https:\/\/developers.openai.com\/api\/docs\/pricing\">OpenAI pricing page<\/a> lists $2.00 input, $0.20 cached input, $2.50 cache writes, and $10.00 output per 1M tokens. Cache writes are 1.25x uncached input. Batch and Flex are priced at 50% of Standard, Fast mode is 2x the applicable rate, and regional processing adds 10% where available.<\/p>\n\n\n\n<div style=\"overflow-x:auto;margin:24px 0;border:1px solid #b8d9d5;border-radius:8px\"><table style=\"width:100%;min-width:760px;border-collapse:collapse;background:#fff;color:#172a2d;font-family:Arial,sans-serif\"><thead><tr style=\"background:#087f8c;color:#fff\"><th style=\"padding:11px;text-align:left;vertical-align:top\">Rate category<\/th><th style=\"padding:11px;text-align:left;vertical-align:top\">Up to 272K input<\/th><th style=\"padding:11px;text-align:left;vertical-align:top\">Above 272K input<\/th><\/tr><\/thead><tbody><tr style=\"background:#fff\"><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">Niet-gecacheerde invoer<\/td><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">$2.00 \/ 1M<\/td><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">$4.00 \/ 1M<\/td><\/tr><tr style=\"background:#f2f8f7\"><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">In cache opgeslagen invoer<\/td><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">$0,20 \/ 1M<\/td><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">$0.40 \/ 1M<\/td><\/tr><tr style=\"background:#fff\"><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">Cache schrijven<\/td><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">$2.50 \/ 1M<\/td><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">$5.00 \/ 1M<\/td><\/tr><tr style=\"background:#f2f8f7\"><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">Uitgang<\/td><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">$10.00 \/ 1M<\/td><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">$15.00 \/ 1M<\/td><\/tr><\/tbody><\/table><\/div>\n\n\n\n<p class=\"wp-block-paragraph\">The long-context column is calculated from OpenAI&#8217;s rule: above 272K input, input and cache rates double and output is multiplied by 1.5 for the full request. It is not a mixed-rate bill. For a practical budget baseline, 100K input plus 10K output costs about <strong>$0.30<\/strong> before tools or regional uplift; a 300K input plus 20K output example costs about <strong>$1.50<\/strong> at the long-context rates.<\/p>\n\n\n\n<section style=\"box-sizing:border-box;margin:24px 0;padding:18px 20px;border-left:5px solid #d36449;background:#f2f8f7;color:#172a2d;font-family:Arial,sans-serif\"><strong style=\"display:block;color:#d36449;font-size:12px;letter-spacing:.04em;text-transform:uppercase\">Pricing caution<\/strong><p style=\"margin:7px 0 0;line-height:1.65\">A large context window can be useful without being cheap to fill. Retrieval, chunk selection, cache reuse, and output caps matter more than the headline 1.05M number. See the <a href=\"https:\/\/www.glbgpt.com\/hub\/gpt-6-astra-pricing\/\">Prijsopbouw GPT-6 Astra<\/a> for a related explanation of context thresholds and cache mechanics.<\/p><\/section>\n\n\n\n<h2 id=\"api-fit\" class=\"wp-block-heading\">GPT-6 Sol API fit, tools, and limits<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">OpenAI recommends the Responses API for built-in tools and function calling. Chat Completions supports function calling only when <code>redeneringsinspanning<\/code> is set to <code>geen<\/code>. That is an implementation detail worth catching before migration: a request can be syntactically valid yet fail to match the tool behavior your current integration expects.<\/p>\n\n\n\n<div style=\"overflow-x:auto;margin:24px 0;border:1px solid #b8d9d5;border-radius:8px\"><table style=\"width:100%;min-width:680px;border-collapse:collapse;background:#fff;color:#172a2d;font-family:Arial,sans-serif\"><thead><tr style=\"background:#087f8c;color:#fff\"><th style=\"padding:11px;text-align:left;vertical-align:top\">Capaciteit<\/th><th style=\"padding:11px;text-align:left;vertical-align:top\">Supported or documented behavior<\/th><\/tr><\/thead><tbody><tr style=\"background:#fff\"><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">Antwoorden<\/td><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">Supported; built-in tools and function calling<\/td><\/tr><tr style=\"background:#f2f8f7\"><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">Chat Completions<\/td><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">Supported; function calling only at reasoning_effort=none<\/td><\/tr><tr style=\"background:#fff\"><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">Batch<\/td><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">Supported; separate processing mode with 50% Standard token rates<\/td><\/tr><tr style=\"background:#f2f8f7\"><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">Audio \/ realtime \/ video<\/td><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">Not supported on the model page<\/td><\/tr><tr style=\"background:#fff\"><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">Afbeelding invoeren<\/td><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">Supported; output remains text<\/td><\/tr><tr style=\"background:#f2f8f7\"><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">Maximale invoer<\/td><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">922,000 tokens; do not confuse this with the 1.05M context window<\/td><\/tr><\/tbody><\/table><\/div>\n\n\n\n<p class=\"wp-block-paragraph\">The current rate-limit table lists the following Standard tiers. RPM means requests per minute, TPM means tokens per minute, and the queue value is the batch-token limit.<\/p>\n\n\n\n<div style=\"overflow-x:auto;margin:24px 0;border:1px solid #b8d9d5;border-radius:8px\"><table style=\"width:100%;min-width:620px;border-collapse:collapse;background:#fff;color:#172a2d;font-family:Arial,sans-serif\"><thead><tr style=\"background:#087f8c;color:#fff\"><th style=\"padding:11px;text-align:left;vertical-align:top\">Niveau<\/th><th style=\"padding:11px;text-align:left;vertical-align:top\">RPM<\/th><th style=\"padding:11px;text-align:left;vertical-align:top\">TPM<\/th><th style=\"padding:11px;text-align:left;vertical-align:top\">Batchwachtrij<\/th><\/tr><\/thead><tbody><tr style=\"background:#fff\"><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">Niveau 1<\/td><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">500<\/td><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">500,000<\/td><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">1,500,000<\/td><\/tr><tr style=\"background:#f2f8f7\"><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">Niveau 2<\/td><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">5,000<\/td><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">1,000,000<\/td><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">3,000,000<\/td><\/tr><tr style=\"background:#fff\"><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">Niveau 3<\/td><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">5,000<\/td><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">2,000,000<\/td><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">100,000,000<\/td><\/tr><tr style=\"background:#f2f8f7\"><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">Niveau 4<\/td><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">10,000<\/td><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">4,000,000<\/td><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">200,000,000<\/td><\/tr><tr style=\"background:#fff\"><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">Niveau 5<\/td><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">15,000<\/td><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">40,000,000<\/td><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">15,000,000,000<\/td><\/tr><\/tbody><\/table><\/div>\n\n\n\n<p class=\"wp-block-paragraph\">Before production rollout, validate the exact tier, endpoint, streaming mode, and tool contract in your own account. The <a href=\"https:\/\/www.glbgpt.com\/hub\/codex-usage-limits\/\">Codex usage limits guide<\/a> is useful context for why a model&#8217;s published ceiling is not the same as an account&#8217;s live allowance.<\/p>\n\n\n\n<h2 id=\"use-cases\" class=\"wp-block-heading\">What GPT-6 Sol&#8217;s specs imply<\/h2>\n\n\n\n<div style=\"overflow-x:auto;margin:24px 0;border:1px solid #b8d9d5;border-radius:8px\"><table style=\"width:100%;min-width:760px;border-collapse:collapse;background:#fff;color:#172a2d;font-family:Arial,sans-serif\"><thead><tr style=\"background:#087f8c;color:#fff\"><th style=\"padding:11px;text-align:left;vertical-align:top\">Reader job<\/th><th style=\"padding:11px;text-align:left;vertical-align:top\">Waarom dit geschikt is<\/th><th style=\"padding:11px;text-align:left;vertical-align:top\">Wat moet je controleren?<\/th><\/tr><\/thead><tbody><tr style=\"background:#fff\"><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">Complex coding<\/td><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">Configurable reasoning and tool support are aligned with multi-step code work.<\/td><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">Run repository-level tasks through the exact endpoint you will ship.<\/td><\/tr><tr style=\"background:#f2f8f7\"><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">Agent loops<\/td><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">Responses tools, function calling, MCP, and hosted tools are documented capabilities.<\/td><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">Check tool permissions, retry behavior, and state handoff.<\/td><\/tr><tr style=\"background:#fff\"><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">Long technical dossiers<\/td><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">1.05M context and 922K maximum input leave room for large source sets.<\/td><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">Measure tokenization and the 272K price transition.<\/td><\/tr><tr style=\"background:#f2f8f7\"><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">High-volume extraction<\/td><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">Possible, but the price sheet makes Luna the cheaper baseline.<\/td><td style=\"padding:10px;border-bottom:1px solid #d9e7e4;vertical-align:top\">Compare acceptance rate and total cost, not just output quality.<\/td><\/tr><\/tbody><\/table><\/div>\n\n\n\n<p class=\"wp-block-paragraph\">This is a fit map, not a benchmark. Use the <a href=\"https:\/\/www.glbgpt.com\/hub\/all-in-one-ai-models\/\">all-in-one AI models workflow guide<\/a> when your real decision is how to switch models inside one repeatable process rather than which single model sounds strongest.<\/p>\n\n\n\n<h2 id=\"hands-on\" class=\"wp-block-heading\">Hands-on API test: three matched tasks<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">We ran the same three small tasks through the Broly Anywhere compatibility API at <code>https:\/\/anywhere.broly.ai\/v1\/chat\/completions<\/code> using model ID <code>gpt-6-sol<\/code>: a coding review, a long-context decision memo, and strict JSON extraction. These are useful workflow observations, not an official OpenAI benchmark or a universal ranking. The first two passes hit temporary HTTP 503 overload responses; after retrying, all three tasks completed at HTTP 200.<\/p>\n\n\n\n<figure style=\"box-sizing:border-box;margin:24px 0;padding:14px;border:1px solid #b8d9d5;border-top:5px solid #087f8c;border-radius:8px;background:#f2f8f7;color:#172a2d;font-family:Arial,sans-serif\"><img decoding=\"async\" src=\"https:\/\/static.futureshareai.com\/glb_features\/mcp\/4\/gpt-6-sol-api-test-capture_d227faeddcc041e48e0ace3e9ddabeb2.webp\" width=\"1000\" height=\"1500\" alt=\"GPT-6 Sol three-task compatibility API test results\" style=\"display:block;width:100%;height:auto;border:1px solid #c9dfdb;border-radius:5px;background:#fff\"\/><figcaption style=\"margin:10px 2px 0;color:#4f696b;font-size:14px;line-height:1.55\">Observed output from the Broly Anywhere compatibility API on September 23, 2026. One scoped run per task; not an official OpenAI benchmark.<\/figcaption><\/figure>\n\n\n\n<section style=\"box-sizing:border-box;margin:24px 0;padding:18px;border:1px solid #b8d9d5;border-radius:8px;background:#f2f8f7;color:#172a2d;font-family:Arial,sans-serif\"><div style=\"margin-bottom:14px\"><strong style=\"display:block;color:#086b72;font-size:12px;letter-spacing:.05em;text-transform:uppercase\">Aanwijzingen en waargenomen resultaten<\/strong><p style=\"margin:6px 0 0;color:#496667;line-height:1.6\">The complete JSON report keeps the full prompts, outputs, HTTP status, finish reason, latency, and usage fields. The cards below keep the same information editable in the WordPress source.<\/p><\/div><article style=\"margin:0 0 14px;padding:16px;border:1px solid #c9dfdb;border-left:5px solid #087f8c;background:#fff;color:#172a2d;font-family:Arial,sans-serif\"><div style=\"display:flex;flex-wrap:wrap;align-items:center;justify-content:space-between;gap:8px\"><strong style=\"color:#087f8c;font-size:12px;letter-spacing:.06em;text-transform:uppercase\">coding review<\/strong><span style=\"padding:5px 8px;background:#e1f1ed;color:#176c62;font-size:12px;font-weight:800\">HTTP 200 \u00b7 stop<\/span><\/div><h3 style=\"margin:7px 0 4px;font:700 19px\/1.25 Georgia,serif\">Coding review and patch plan<\/h3><p style=\"margin:0 0 10px;color:#537073;font-size:13px\">13891 ms \u00b7 480 total tokens \u00b7 232 reasoning tokens<\/p><div style=\"display:grid;grid-template-columns:repeat(auto-fit,minmax(min(320px,100%),1fr));gap:10px\"><div><strong style=\"display:block;margin-bottom:5px;color:#086b72;font-size:12px;text-transform:uppercase\">Taak<\/strong><pre style=\"box-sizing:border-box;min-height:112px;margin:0;padding:10px;border:1px solid #c9dfdb;background:#f6fbfa;color:#173135;font:12px\/1.5 Consolas,monospace;white-space:pre-wrap\">Review this small JavaScript function as if it were part of a production repository. Identify the bug, explain the failure mode, and propose a minimal patch plus two focused regression tests. Function: function uniqueSorted(values) { return [...new Set(values)].sort((a, b) =&gt; a - b).filter(Boolean); }<\/pre><\/div><div><strong style=\"display:block;margin-bottom:5px;color:#086b72;font-size:12px;text-transform:uppercase\">Gemeten output<\/strong><pre style=\"box-sizing:border-box;min-height:112px;max-height:260px;overflow:auto;margin:0;padding:10px;border:1px solid #29474a;background:#17252a;color:#eaf6f3;font:12px\/1.5 Consolas,monospace;white-space:pre-wrap\">**Bug:** `.filter(Boolean)` removes `0` from the result, even though zero is a valid number. For example, `uniqueSorted([-2, 0, 3])` returns `[-2, 3]`. It can also silently remove other falsy inputs.\n\n**Minimal patch:** Remove the filter; deduplication and sorting are already complete.\n\n```js\nfunction uniqueSorted(values) {\n  return [...new Set(values)].sort((a, b) =&gt; a - b);\n}\n```\n\n**Focused regression tests:**\n\n```js\nconst assert = require('node:assert\/strict');\n\nassert.deepStrictEqual(uniqueSorted([0]), [0]);\nassert.deepStrictEqual(uniqueSorted([3, 0, -2, 0, 3]), [-2, 0, 3]);\n```<\/pre><\/div><\/div><\/article><article style=\"margin:0 0 14px;padding:16px;border:1px solid #c9dfdb;border-left:5px solid #087f8c;background:#fff;color:#172a2d;font-family:Arial,sans-serif\"><div style=\"display:flex;flex-wrap:wrap;align-items:center;justify-content:space-between;gap:8px\"><strong style=\"color:#087f8c;font-size:12px;letter-spacing:.06em;text-transform:uppercase\">long context synthesis<\/strong><span style=\"padding:5px 8px;background:#e1f1ed;color:#176c62;font-size:12px;font-weight:800\">HTTP 200 \u00b7 stop<\/span><\/div><h3 style=\"margin:7px 0 4px;font:700 19px\/1.25 Georgia,serif\">Multi-source synthesis<\/h3><p style=\"margin:0 0 10px;color:#537073;font-size:13px\">13151 ms \u00b7 285 total tokens \u00b7 55 reasoning tokens<\/p><div style=\"display:grid;grid-template-columns:repeat(auto-fit,minmax(min(320px,100%),1fr));gap:10px\"><div><strong style=\"display:block;margin-bottom:5px;color:#086b72;font-size:12px;text-transform:uppercase\">Taak<\/strong><pre style=\"box-sizing:border-box;min-height:112px;margin:0;padding:10px;border:1px solid #c9dfdb;background:#f6fbfa;color:#173135;font:12px\/1.5 Consolas,monospace;white-space:pre-wrap\">Synthesize the following three notes into a concise decision memo with: decision, evidence, risks, and next step. Note A: A 1.05M-token context window can hold large source sets but does not make every request cheap. Note B: Above 272K input tokens, the documented input\/cache rates increase and output is multiplied for the full request. Note C: Retrieval and cache reuse can reduce repeated prompt cost, but acceptance criteria still need testing.<\/pre><\/div><div><strong style=\"display:block;margin-bottom:5px;color:#086b72;font-size:12px;text-transform:uppercase\">Gemeten output<\/strong><pre style=\"box-sizing:border-box;min-height:112px;max-height:260px;overflow:auto;margin:0;padding:10px;border:1px solid #29474a;background:#17252a;color:#eaf6f3;font:12px\/1.5 Consolas,monospace;white-space:pre-wrap\">**Decision:** Use the 1.05M-token window selectively, not as the default way to process large source sets.\n\n**Evidence:** It can hold substantial material, but requests above 272K input tokens incur higher documented input and cache rates, and the output multiplier applies to the full request. Retrieval and cache reuse may lower repeated prompt costs.\n\n**Risks:** Large-context requests may be expensive, while a cheaper retrieval approach may fail to meet acceptance criteria.\n\n**Next step:** Test representative tasks using full context versus retrieval with cache reuse; compare cost and results against the acceptance criteria before choosing a default.<\/pre><\/div><\/div><\/article><article style=\"margin:0 0 14px;padding:16px;border:1px solid #c9dfdb;border-left:5px solid #087f8c;background:#fff;color:#172a2d;font-family:Arial,sans-serif\"><div style=\"display:flex;flex-wrap:wrap;align-items:center;justify-content:space-between;gap:8px\"><strong style=\"color:#087f8c;font-size:12px;letter-spacing:.06em;text-transform:uppercase\">structured extraction<\/strong><span style=\"padding:5px 8px;background:#e1f1ed;color:#176c62;font-size:12px;font-weight:800\">HTTP 200 \u00b7 stop<\/span><\/div><h3 style=\"margin:7px 0 4px;font:700 19px\/1.25 Georgia,serif\">Gestructureerde extractie<\/h3><p style=\"margin:0 0 10px;color:#537073;font-size:13px\">12528 ms \u00b7 128 total tokens \u00b7 27 reasoning tokens<\/p><div style=\"display:grid;grid-template-columns:repeat(auto-fit,minmax(min(320px,100%),1fr));gap:10px\"><div><strong style=\"display:block;margin-bottom:5px;color:#086b72;font-size:12px;text-transform:uppercase\">Taak<\/strong><pre style=\"box-sizing:border-box;min-height:112px;margin:0;padding:10px;border:1px solid #c9dfdb;background:#f6fbfa;color:#173135;font:12px\/1.5 Consolas,monospace;white-space:pre-wrap\">Extract the following fields from this brief and return valid JSON only with keys customer, priority, deadline, and unknowns. Brief: Customer: Northwind Labs. Priority: high. Deadline: 2026-10-04. The owner is not named and the budget is not confirmed.<\/pre><\/div><div><strong style=\"display:block;margin-bottom:5px;color:#086b72;font-size:12px;text-transform:uppercase\">Gemeten output<\/strong><pre style=\"box-sizing:border-box;min-height:112px;max-height:260px;overflow:auto;margin:0;padding:10px;border:1px solid #29474a;background:#17252a;color:#eaf6f3;font:12px\/1.5 Consolas,monospace;white-space:pre-wrap\">{&quot;customer&quot;:&quot;Northwind Labs&quot;,&quot;priority&quot;:&quot;high&quot;,&quot;deadline&quot;:&quot;2026-10-04&quot;,&quot;unknowns&quot;:[&quot;owner&quot;,&quot;budget&quot;]}<\/pre><\/div><\/div><\/article><\/section>\n\n\n\n<p class=\"wp-block-paragraph\">In the coding task, GPT-6 Sol identified the falsy-value bug in <code>filter(Boolean)<\/code> and supplied a patch plus regression coverage; the completed run used 480 total tokens. In the long-context task, it kept the decision, evidence, risk, and next-step structure while carrying the 272K pricing caveat forward; the response used 285 total tokens. In the structured extraction task, it returned the requested customer, priority, deadline, and unknowns fields as JSON. Those are observed output shapes for this route, not evidence that one model is universally better.<\/p>\n\n\n\n<h2 id=\"reactions\" class=\"wp-block-heading\">What public reactions can and cannot tell you<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">The following sources are included as attributed public reaction, not as official documentation or controlled benchmark evidence. Their titles show what each creator chose to test or explain; they do not establish a market-wide result.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Nate Herk | AI Automation:<\/strong> <a href=\"https:\/\/www.youtube.com\/watch?v=eF3yeJuifoQ\">I Tested Opus 5.5 vs. GPT-6 Sol on 10 Real Use Cases<\/a>. Treat the framing and any demonstration as that creator&#8217;s experience, not as a universal score.<\/li>\n\n\n\n<li><strong>Arena AI:<\/strong> <a href=\"https:\/\/www.youtube.com\/watch?v=jVFz7cTeQxk\">GPT-6 Sol | First impressions<\/a>. Treat the framing and any demonstration as that creator&#8217;s experience, not as a universal score.<\/li>\n\n\n\n<li><strong>Chase AI:<\/strong> <a href=\"https:\/\/www.youtube.com\/watch?v=U_sjnF3jvCo\">GPT 6 Sol &amp; Luna Are Here (And 50% CHEAPER!)<\/a>. Treat the framing and any demonstration as that creator&#8217;s experience, not as a universal score.<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">A separate naming issue matters here: several public videos use &#8220;GPT-6&#8221; and &#8220;GPT-5.6&#8221; interchangeably in titles. Keep the exact model ID visible when you reproduce a claim. The <a href=\"https:\/\/www.glbgpt.com\/hub\/gpt-6-astra-vs-gpt-5-6-sol\/\">Vergelijking tussen de GPT-6 Astra en de GPT-5.6 Sol<\/a> is a useful example of why provider identity, platform label, and route should be recorded separately.<\/p>\n\n\n\n<h2 id=\"globalgpt\" class=\"wp-block-heading\">GlobalGPT access and the GPT-5.6 naming note<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">GlobalGPT&#8217;s verified model catalog currently exposes <strong>GPT-5.6 Sol<\/strong> en <strong>GPT-5.6 Luna<\/strong>. The exact OpenAI API IDs in this article are <code>gpt-6-sol<\/code> and belong to OpenAI&#8217;s official documentation. An exact <code>\/home\/gpt-6-sol<\/code> GlobalGPT route was not verified, so this article does not claim that the platform route is GPT-6 access.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">For the current platform naming and separate credit context, see the <a href=\"https:\/\/www.glbgpt.com\/hub\/gpt-5-6-pricing\/\">Prijsgids GPT-5.6<\/a> en de <a href=\"https:\/\/www.glbgpt.com\/hub\/gpt-5-6-vs-fable-5-vs-gpt-5-5\/\">Vergelijking van het GPT-5.6-model<\/a>. Those pages are platform\/editorial context; they do not override OpenAI&#8217;s API pricing table.<\/p>\n\n\n\n<section style=\"box-sizing:border-box;margin:24px 0;padding:20px;border:1px solid #b8d9d5;border-top:5px solid #087f8c;border-radius:8px;background:#f2f8f7;color:#172a2d;font-family:Arial,sans-serif\"><strong style=\"display:block;color:#086b72;font-size:12px;text-transform:uppercase\">Verified platform route<\/strong><p style=\"margin:7px 0 14px;line-height:1.6\">This link opens GlobalGPT&#8217;s current platform naming, not a verified GPT-6 OpenAI model ID.<\/p><a href=\"https:\/\/www.glbgpt.com\/home\/gpt-5-6-sol?inviter=hub_content_gptsol56&amp;login=1\" style=\"display:inline-block;padding:10px 14px;border-radius:5px;background:#087f8c;color:#fff;text-decoration:none;font-weight:800\">Open GlobalGPT GPT-5.6 Sol workspace<\/a><\/section>\n\n\n\n<h2 id=\"choice\" class=\"wp-block-heading\">Who should choose GPT-6 Sol?<\/h2>\n\n\n\n<section style=\"box-sizing:border-box;margin:24px 0;padding:18px;border:1px solid #b8d9d5;border-radius:8px;background:#f2f8f7;color:#172a2d;font-family:Arial,sans-serif\"><div style=\"display:grid;gap:10px\"><div style=\"padding:13px 15px;border-left:5px solid #087f8c;background:#fff\"><strong>Choose Sol for<\/strong><span style=\"display:block;margin-top:4px;line-height:1.6\">multi-step coding, agent loops, tool orchestration, and large technical dossiers where a configurable reasoning budget is useful.<\/span><\/div><div style=\"padding:13px 15px;border-left:5px solid #d36449;background:#fff\"><strong>Choose Luna instead when<\/strong><span style=\"display:block;margin-top:4px;line-height:1.6\">you need the same broad API shape at much lower token rates for focused, repeatable, high-volume work.<\/span><\/div><div style=\"padding:13px 15px;border-left:5px solid #087f8c;background:#fff\"><strong>Validate first when<\/strong><span style=\"display:block;margin-top:4px;line-height:1.6\">your workflow depends on audio, realtime sessions, legacy Completions, or a specific GlobalGPT model ID.<\/span><\/div><\/div><\/section>\n\n\n\n<p class=\"wp-block-paragraph\">If your shortlist includes lower-cost alternatives, compare the <a href=\"https:\/\/www.glbgpt.com\/hub\/best-ai-models\/\">broader model catalog<\/a> rather than assuming the newest model is automatically the best value. If you are evaluating data-heavy work, the <a href=\"https:\/\/www.glbgpt.com\/hub\/best-ai-tools-for-data-analysis-tested\/\">data-analysis model guide<\/a> provides a separate workflow lens.<\/p>\n\n\n\n<h2 id=\"faq\" class=\"wp-block-heading\">Veelgestelde vragen<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">What is GPT-6 Sol?<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">GPT-6 Sol is OpenAI&#8217;s complex coding and agentic workflows model. Its official API model ID is gpt-6-sol.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">How much does GPT-6 Sol cost?<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">OpenAI lists GPT-6 Sol at $2.00 per 1M input tokens, $0.20 per 1M cached input tokens, $2.50 per 1M cache writes, and $10.00 per 1M output tokens at Standard rates.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">What happens above 272K input tokens?<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">When a request exceeds 272K input tokens, OpenAI applies 2x input and cache rates and 1.5x output rates to the full request.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">What are the context and output limits?<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">GPT-6 Sol lists a 1,050,000-token context window, a 922,000-token maximum input, and a 128,000-token maximum output.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">What is the knowledge cutoff?<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">The current OpenAI model page lists April 20, 2026 as the knowledge cutoff for GPT-6 Sol.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Which reasoning settings are available?<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">The API documents none, low, medium, high, xhigh, and max reasoning effort, with medium as the default.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Which API endpoints are supported?<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">GPT-6 Sol supports Chat Completions, Responses, and Batch. The model page does not list Realtime, Assistants, audio, video, image generation, embeddings, fine-tuning, moderation, or legacy Completions as supported.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Can GPT-6 Sol accept images?<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Yes. The model page lists text and image input with text output. That does not make it an image-generation model.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Is GPT-6 Sol available in GlobalGPT?<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">OpenAI&#8217;s official model name is GPT-6 Sol, but GlobalGPT currently exposes GPT-5.6 Sol and GPT-5.6 Luna labels. The exact GPT-6 GlobalGPT route is not verified, so this article does not claim GPT-6 access through GlobalGPT.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Does this article include a benchmark?<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Yes, but the scope is narrow: three matched tasks through the Broly Anywhere compatibility API. The results are retained as one observed run and are not an official OpenAI benchmark or a universal winner claim.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Eindoordeel<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Sol is the model to examine when the work is genuinely complex, tool-heavy, or code-centric and the higher token bill is acceptable. The evidence here combines official documentation with a scoped compatibility-API observation, not a controlled benchmark, so the responsible verdict is fit, not a universal ranking. Recheck the official model and pricing pages on publication day before publishing.<\/p>\n\n\n\n<p role=\"note\" style=\"margin:26px 0;color:#567073;font:13px\/1.6 Arial,sans-serif\">Checked September 23, 2026. Official facts: OpenAI Developers. Platform route naming: GlobalGPT. Public reaction: linked creators and publications, attributed only.<\/p>\n\n\n\n<script type=\"application\/ld+json\">{\n    \"@context\": \"https:\\\/\\\/schema.org\",\n    \"@type\": \"FAQPage\",\n    \"mainEntity\": [\n        {\n            \"@type\": \"Question\",\n            \"name\": \"What is GPT-6 Sol?\",\n            \"acceptedAnswer\": {\n                \"@type\": \"Answer\",\n                \"text\": \"GPT-6 Sol is OpenAI's complex coding and agentic workflows model. 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GlobalGPT currently lists GPT-5.6 Sol and GPT-5.6 Luna rather than exact GPT-6 routes, so the platform [&hellip;]<\/p>","protected":false},"author":16,"featured_media":19730,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_seopress_robots_primary_cat":"","_seopress_titles_title":" GPT-6 Sol Review: Pricing, Context, API Limits, and Best Uses","_seopress_titles_desc":"GPT-6 Sol review with official pricing, 1.05M context, API limits, coding and agent fit, and a three-task Broly Anywhere compatibility API observation, plus the GPT-5.6 GlobalGPT naming caveat.","_seopress_robots_index":"","footnotes":""},"categories":[7],"tags":[],"class_list":["post-19719","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai-chat"],"acf":[],"_links":{"self":[{"href":"https:\/\/wp.glbgpt.com\/nl\/wp-json\/wp\/v2\/posts\/19719","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/wp.glbgpt.com\/nl\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/wp.glbgpt.com\/nl\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/wp.glbgpt.com\/nl\/wp-json\/wp\/v2\/users\/16"}],"replies":[{"embeddable":true,"href":"https:\/\/wp.glbgpt.com\/nl\/wp-json\/wp\/v2\/comments?post=19719"}],"version-history":[{"count":5,"href":"https:\/\/wp.glbgpt.com\/nl\/wp-json\/wp\/v2\/posts\/19719\/revisions"}],"predecessor-version":[{"id":19737,"href":"https:\/\/wp.glbgpt.com\/nl\/wp-json\/wp\/v2\/posts\/19719\/revisions\/19737"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/wp.glbgpt.com\/nl\/wp-json\/wp\/v2\/media\/19730"}],"wp:attachment":[{"href":"https:\/\/wp.glbgpt.com\/nl\/wp-json\/wp\/v2\/media?parent=19719"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/wp.glbgpt.com\/nl\/wp-json\/wp\/v2\/categories?post=19719"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/wp.glbgpt.com\/nl\/wp-json\/wp\/v2\/tags?post=19719"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}