GPT-6 Sol Pro Online | Pro Reasoning on NetRoom
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GPT-6 Sol Pro

Current version: 6.0 updated

Same GPT-6 Sol weights served with pro reasoning. 1M token context.

Category
Language
Modality
Text · Reasoning · Tool use
Context
1M
Released
Sep 2026
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What's new in GPT-6 Sol Pro 6.0

  • Same weights as GPT-6 Sol, served with reasoning.mode = pro
  • 1.05M token context, up to 128K tokens in a single reply
  • More internal reasoning per step for higher quality on hard tasks
  • Text, image and file input, text-only output
  • Tool calling, JSON-schema structured outputs and seed
Strengths

What it's the best tool for

  • Same weights as GPT-6 Sol, served with reasoning.mode = pro
  • 1.05M token context, up to 128K tokens in a single reply
  • Text, images and files in one request
  • Tool calling in three modes: auto, required and a named function
  • Structured outputs against a JSON schema, plus seed and reasoning_effort
Limitations

When to reach for something else

  • Slower than base Sol: pro mode thinks longer at every step
  • Burns noticeably more reasoning tokens, so the same task costs more
  • On short, unambiguous prompts it gains little over base Sol
  • Text output only: the model does not generate images or video
  • No built-in web search in chat, fresh data has to come in the prompt
Sample output

How GPT-6 Sol Pro responds

Prompt
Here is a day of slow-query logs from production plus the database schema. Work out why the reporting export degrades towards the evening, explain the cause step by step, and propose a fix plan with a risk estimate for each change.
GPT-6 Sol Pro
It is one reporting query, not the overall load. 1) orders_report joins order_items with no index on (order_id, created_at) — the plan falls back to a seq scan, and the daily row batch roughly triples by the evening. 2) The same query runs in a loop per manager: 140 calls instead of one grouped query. 3) Statistics on order_items were last refreshed eight days ago, so the planner underestimates the selection. Fix plan: start with a composite index on (order_id, created_at) — low risk, builds online. Then rewrite the loop as a single GROUP BY query — medium risk, reconcile the totals on a copy first. Touch autovacuum settings for order_items last. Checked against timestamps: the slow-query peak lands in the 18:00-20:00 window, when the export is triggered en masse.
Where teams use it

Four scenarios where it pays for itself

01
Heavy refactoring
Reading an unfamiliar codebase and justifying every change
02
Agent scenarios
Multi-step pipelines where one wrong step breaks the session
03
Document audit
Finding contradictions across hundreds of pages of contracts and reports
04
Calculations and data
Long derivations where every intermediate step matters
About model

More about GPT-6 Sol Pro

GPT-6 Sol Pro Online — the Deeper Reasoning Mode of GPT-6 Sol

GPT-6 Sol Pro is the same OpenAI model as GPT-6 Sol, served with reasoning.mode = pro. There are no separate Pro weights: the whole difference is how long the model thinks before it answers. Sol is the high-end workhorse of the GPT-6 generation — it sits below the flagship GPT-6 Astra and above the fast Luna tier, and it is built for demanding professional work. On NetRoom both versions live in the same chat, with no VPN and no foreign card required.

What pro mode buys you

Pro spends more internal reasoning on every step. Where the answer depends on a dozen linked conditions — reading unfamiliar code, a long calculation chain, hunting contradictions in a document — the model cuts fewer corners for the sake of speed. On short, unambiguous prompts the difference is barely visible: base Sol answers just as well, only faster. The technical specs are identical across both versions: a 1.05M-token context, up to 128K tokens in a single reply, text, image and file input, and text output.

What it can do

Tool calling works in three modes: automatic choice, required call, and a named function. Structured output is validated against a JSON schema, so the reply can move down the pipeline without parsing free text. There is a seed for reproducibility and reasoning_effort — an effort level on top of pro mode when you want to tune the balance between depth and latency. Images and files travel in the same request as text: a stack-trace screenshot, a scanned contract and your question about them go out as one message.

When to pick Sol Pro over base Sol

Pro earns its keep where a wrong answer costs more than extra tokens: heavy refactoring, auditing long documents, multi-step agent scenarios, analysis with long derivations. For quick chat, drafts and routine questions, base GPT-6 Sol makes more sense — it replies noticeably faster and burns fewer reasoning tokens on the same task. If the job needs the very top of the line, look at GPT-6 Astra Pro.

How to start

Sign up on NetRoom, top up your balance and pick GPT-6 Sol Pro from the model list. It runs right in the browser: write a prompt, attach files and images, get an answer — no API keys and no extra setup.

Recent changes

What changed GPT-6 Sol Pro

  • + Added text model GPT-6 Sol Pro (OpenAI).
Full changelog →
Versions

Version history of GPT-6 Sol Pro

Version Date What changed
6.0 current
  • Same weights as GPT-6 Sol, served with reasoning.mode = pro
  • 1.05M token context, up to 128K tokens in a single reply
  • More internal reasoning per step for higher quality on hard tasks
  • Text, image and file input, text-only output
  • Tool calling, JSON-schema structured outputs and seed

Use GPT-6 Sol Pro via the API

The same engine, straight from your code: one key and one balance for text, images, video and sound. Pay only for the requests you make.

curl
curl https://netroom.ai/api/v1/chat/completions \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model": "openai/gpt-6-sol-pro", "messages": [{"role": "user", "content": "Hello"}]}'

The format is OpenAI SDK compatible — point base_url at https://netroom.ai/api/v1 and use your NetRoom key.

The model id is already in the example. The full parameter reference and prices live in GET /api/v1/models and in the docs.

API documentation Get an API key

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