GPT-6 Sol Review

For the newer version, see our GPT-6.1 Sol review. The analysis below covers the original GPT-6 Sol.

GPT-6 Sol launched on September 22, 2026, with a clear proposition: complex coding and agent workflows at $2 input and $10 output per million tokens. Our assessment is that Sol belongs on the shortlist for development work with several connected decisions, while routine extraction should first be evaluated on Luna. The useful question is how much work survives review at the end of a run.

GPT-6 Sol release date and availability

OpenAI's API changelog records the release of gpt-6-sol and gpt-6-luna on September 22, 2026. The publication or update date shown on this article is an editorial date, not a different model release date.

On September 25, OpenAI reported an image-encoding fix for Sol and Luna in the API and Codex and recommended rerunning affected visual evaluations. API release, a client's model picker and access through a particular account or gateway are separate checks. Confirm your route's catalog and permissions instead of treating a release announcement as universal access.

GPT-6 Sol review: is it worth using?

Test Sol on multi-file changes, debugging and tool-driven analysis. Those tasks match OpenAI's published positioning. Success means preserving requirements, making the right edits and passing verification, not producing a longer explanation.

Its $2/$10 Standard rates make a 100K-input, 10K-output run a $0.30 token calculation. That is a useful budget baseline, not proof of cheaper completed work. Keep your existing model available until a matched task set shows acceptable quality, latency and repair cost.

GPT-6 Sol specifications and context window

Sol defaults to medium reasoning. Reserving the full 128,000 output tokens inside a 1,050,000-token context leaves 922,000 tokens for input by subtraction; this is a budgeting calculation, not a separate documented input-limit claim. Reasoning also consumes output allowance, and the client or route can impose additional constraints. Matching context sizes do not establish matching recall or coding quality.

GPT-6 Sol API pricing

Direct OpenAI prices in USD per one million tokens, using Standard processing. These are not OmniaKey gateway quotes.

Above 272K input tokens, the entire request uses 2x input/cache rates and 1.5x output rates. The multiplier is not limited to the excess tokens. Exactly 272K remains in the lower bracket under the current wording.

OpenAI lists Batch and Flex at 50% of applicable Standard rates, Fast mode at 2x, and regional processing at a 10% premium where available. Processing options have their own eligibility and behavior; a price multiplier is not a latency guarantee.

What does a GPT-6 Sol coding task cost?

The first row is 0.10 × $2 + 0.01 × $10 = $0.30. The second uses the long-context rates: 0.30 × $4 + 0.01 × $15 = $1.35. An agent that resends a large repository across several tool turns can cross this boundary repeatedly, so measure the full conversation rather than only the final answer.

These are calculations, not observed bills. Output includes billed reasoning tokens as well as visible text. The examples assume one attempt, no cache writes or hits, and exclude tool fees, storage, taxes and human review. Use actual usage fields when reconciling a run.

GPT-6 Sol coding performance: what the evidence supports

OpenAI describes Sol as built for complex coding and agentic workflows. Its API supports the mechanisms such workflows need, including tools, structured output and long context. Those are verified capabilities, but they are not a SWE-bench score or an independent estimate of success on your repository. This review does not assign an invented benchmark rank.

A useful coding evaluation includes a bug spanning multiple files, a refactor with compatibility constraints and a failing test that requires investigation. Check whether the final patch passes the original tests, adds the intended behavior and avoids unrelated edits. Record retries and manual repairs: a plausible patch that takes twenty minutes to fix is not a cheap completion.

When to choose Sol, Luna or Astra

• Start with Sol for connected engineering work. It is a sensible candidate when a task combines reading code, choosing an approach and making changes; confirm the choice with tests.
• Start with Luna for bounded work. Classification, field extraction and short transformations have clearer validators and a much lower listed token price. See the Luna review.
• Evaluate Astra for difficult failures. OpenAI positions Astra as its most capable model. Escalate because a task needs it, rather than assuming every request should use the flagship.

GPT-6 Sol is a distinct ID from gpt-5.6-sol. Preserve the old route during a migration, pin the model name and compare identical inputs, tool permissions and acceptance commands. Changing the model and the agent harness together makes the result difficult to interpret.

API compatibility and tool calling

Both models support Responses and Chat Completions. For reasoning together with tools, use Responses API. Their model pages allow Chat Completions function calling only when reasoning_effort is none; endpoint support does not imply identical tool behavior.

On Responses, the documented reasoning.effort values are none, low, medium, high, xhigh, and max. Start with a fixed setting and raise it only when an acceptance test justifies the extra work. Function calling, structured outputs and image input are supported. Native output is text; using an image-generation tool is a separate operation.

curl --fail-with-body https://api.openai.com/v1/responses \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-6-sol",
    "reasoning": {
        "effort": "medium"
    },
    "input": "Review this function for edge cases and propose a minimal fix: function divide(a, b) { return a / b; }"
}'

The request example and prices on this page refer to OpenAI directly. For OmniaKey, check the live model catalog for the exact route, supported features and current quote. OpenAI's release does not by itself verify a gateway route, a Codex picker or a ChatGPT plan entitlement.

Frequently asked questions

When was GPT-6 Sol released?

OpenAI's API changelog records September 22, 2026. The exact ID is gpt-6-sol. This page replaces our earlier pre-release status article while retaining its URL.

Is GPT-6 Sol better than GPT-6 Luna for coding?

Sol is positioned for complex coding; Luna for focused, high-volume work. That makes Sol a reasonable first candidate for broad changes, but this review has no matched benchmark proving it wins every coding task. The Sol vs Luna comparison explains how to price that decision.

Is there a GPT-6 Terra?

As checked on September 23, the public GPT-6 catalog lists gpt-6-astra, gpt-6-sol and gpt-6-luna. It does not list gpt-6-terra; GPT-5.6 Terra is a different generation.

Related reviews

• GPT-6 Luna review
• GPT-6 Sol vs Luna: which should you choose?
• GPT-6 Astra review
• View the model catalog

Official sources

• OpenAI: GPT-6 Sol
• OpenAI: GPT-6 Luna
• OpenAI: API changelog
• OpenAI: API pricing
• OpenAI: Reasoning
• OpenAI: Model catalog