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Decision summary

  • New Sol work -> GPT-6.1 Sol
  • Existing gpt-6-sol route -> this card's $2 / $10 rates
  • Pinned gpt-5.6-sol -> replay before you cut over
  • Above 272K input tokens -> price the full request from each card
  • Need Astra -> do not stop at Sol

OpenAI Sol successor comparison

Frontier comparison

GPT-6 Sol vs GPT-5.6 Sol

GPT-6 Sol (gpt-6-sol) and GPT-5.6 Sol (gpt-5.6-sol) are both still documented OpenAI API models.

Featured · Updated 7 days ago · Last verified: October 2026

Choose GPT-6 Sol when

An existing gpt-6-sol route. New Sol work is documented on GPT-6.1 Sol.

Choose GPT-5.6 Sol when

A deployment that is still pinned to gpt-5.6-sol.

  • New Sol work: GPT-6.1 Sol
  • Existing gpt-6-sol route: this card's $2 / $10 rates
  • Pinned gpt-5.6-sol: replay before you cut over

Decision axes: Best for · Access and platforms · Context window · Input and output

Reasoning

Both cards list none through max, default medium.

Coding

GPT-6 Sol is the September Sol ID. GPT-6.1 Sol is the newer Sol model named on that card. No score table is published.

Multimodal

Text and image in, text out, on both cards.

Speed

GPT-6 Sol Fast mode is 2× Standard. Do not copy that rate onto GPT-5.6 Sol.

Enterprise

Both IDs remain on the model cards. A pin is a deployment choice, not a quality ranking.

Curated matrix for GPT-6 Sol vs GPT-5.6 Sol — confirm live limits and pricing on each vendor’s official pages.

How they compare

Criterion-by-criterion notes from the catalog—not a ranking. Validate on your own gold set.

CriterionGPT-6 SolGPT-5.6 Sol
Best forAn existing gpt-6-sol route. New Sol work is documented on GPT-6.1 Sol.A deployment that is still pinned to gpt-5.6-sol.
Access and platformsAPI ID gpt-6-sol. The model card points to gpt-6.1-sol as the newer Sol model.API ID gpt-5.6-sol. The gpt-5.6 alias routes to this model.
Context window1,050,000 context, 922,000 max input, 128,000 max output. Knowledge cutoff April 20, 2026.1,050,000 context, 922,000 max input, 128,000 max output. Knowledge cutoff February 16, 2026.
Input and outputText and image in; text out.Text and image in; text out.
Reasoning controlnone, low, medium (default), high, xhigh, and max. Chat Completions function calling only at none.none, low, medium (default), high, xhigh, and max.
Coding and agentsBuilt for complex coding and agentic workflows. Responses API for built-in tools.The prior Sol ID. Daybreak Blue's October 30 overview still names it for reduced refusals.
Cost posture$2 input / $0.20 cached / $2.50 cache write / $10 output per million. Above 272K input tokens: 2× input and cache, and 1.5× output, for the full request. Fast mode is 2×. Regional processing adds 10%.$4 input / $0.40 cached / $20 output per million. Cache writes are 1.25× uncached input. Above 272K input tokens: 2× input and 1.5× output for the full request. Promotional pricing lasts at least through November 21, 2026.
Operational riskReplay a pinned eval before you leave gpt-5.6-sol. Do not treat the sticker gap as a quality score.Staying pinned avoids a migration and keeps the higher list price until the promo date.

Key insights

Concrete technical or product signals.

  • Short-context stickers are $2/$10 versus $4/$20. GPT-5.6 Sol's card says that promotional pricing lasts at least through November 21, 2026.
  • Above 272K input tokens, GPT-6 Sol charges 2× input and cache and 1.5× output for the whole request. GPT-5.6 Sol's card charges 2× input and 1.5× output. It does not say the cache rate doubles.
  • Cached input is $0.20 on GPT-6 Sol and $0.40 on GPT-5.6 Sol. GPT-6 Sol lists cache writes at $2.50. GPT-5.6 Sol states cache writes at 1.25× the uncached input rate.

Use cases

Where this shines in production.

  • Comparing gpt-6-sol with a pinned gpt-5.6-sol deployment
  • Pricing a request that crosses 272K input tokens
  • Seeing that new Sol work is documented on GPT-6.1 Sol

Limitations & trade-offs

What to watch for.

  • This page is not GPT-6 Sol versus GPT-6.1 Sol, and it is not Sol versus Astra or Luna.
  • No quality scores are published on these two cards, so none are stated.
  • Daybreak Blue's October 30 overview names both models. Project enablement is still separate, and GPT-6.1 Sol follows a different access rule.

Watch-outs

Who should pass, and what to validate before rollout.

  • Do not treat $2/$10 as proof that GPT-6 Sol matches GPT-5.6 Sol on your eval.
  • Do not apply GPT-6 Sol's doubled cache rate to GPT-5.6 Sol.
  • Do not open a new Sol route on gpt-5.6-sol.

Final recommendation

What to do after reading the table.

Use GPT-6.1 Sol for a new Sol route. Keep gpt-5.6-sol where the replay has not passed, and keep gpt-6-sol where that ID is already the pin.

FAQ

Is GPT-6 Sol better than GPT-5.6 Sol?

Use GPT-6.1 Sol for a new Sol route. Keep gpt-5.6-sol where the replay has not passed, and keep gpt-6-sol where that ID is already the pin.

Which is better for coding: GPT-6 Sol or GPT-5.6 Sol?

GPT-6 Sol: Built for complex coding and agentic workflows. Responses API for built-in tools. GPT-5.6 Sol: The prior Sol ID. Daybreak Blue's October 30 overview still names it for reduced refusals. The catalog does not declare a winner on coding and agents.

Which is cheaper: GPT-6 Sol or GPT-5.6 Sol?

Listed unit prices: GPT-6 Sol $2 input / $0.20 cached / $2.50 cache write / $10 output per million. Above 272K input tokens: 2× input and cache, and 1.5× output, for the; GPT-5.6 Sol $4 input / $0.40 cached / $20 output per million. Cache writes are 1.25× uncached input. Above 272K input tokens: 2× input and 1.5× output. A lower listed unit price is not the same as a lower total workload cost—tokens, session minutes, caching, introductory rates, and add-on modes can reverse the ranking. Confirm live rates on each vendor’s official page.

Can I use both GPT-6 Sol and GPT-5.6 Sol?

Yes. Many teams keep both and route by constraint. Use GPT-6 Sol for An existing gpt-6-sol route. New Sol work is documented on GPT-6.1 Sol, and GPT-5.6 Sol for A deployment that is still pinned to gpt-5.6-sol. Confirm vendor terms before mixing them in one production workflow.

Continue with

Official sources

This page is based on publicly available documentation, benchmarks, and real-world usage patterns. Last reviewed for accuracy recently.