Model comparison
GPT-6 Sol vs Gemini 3.1 Pro Preview: a near price tie
GPT-6 Sol and Gemini 3.1 Pro Preview both charge $2 input and $0.20 per cache hit. Which one costs less flips by workload, so limits and status decide.
· Prices as of September 28, 2026
GPT-6 Sol
OpenAI · Released September 22, 2026
The mid-priced GPT-6 model, which OpenAI pitches for complex coding and agent workflows and which the Codex docs recommend for complex coding.
GPT-6 Sol facts and comparisonsGemini 3.1 Pro Preview
Google · Released February 19, 2026 · Preview
Google's only current Pro model, still in preview, positioned for deep reasoning and agentic coding.
Gemini 3.1 Pro Preview facts and comparisons
The short answer
On price these two are almost level: the example agentic coding session costs $2.10 on GPT-6 Sol and $2.00 on Gemini 3.1 Pro Preview, while output-heavy generation costs $0.86 on Sol and $1.02 on Gemini. Limits and status separate them more than cost does, since GPT-6 Sol is a current release that writes up to 128K tokens and Gemini 3.1 Pro Preview is a preview capped at 65.5K. Sol fits Codex users and Gemini 3.1 Pro Preview fits Gemini CLI users.
Choose GPT-6 Sol if
- Your work is output-heavy: Sol charges $10 per million output tokens against $12.
- You need responses longer than 65.5K tokens, up to Sol's 128K.
- Your prompts fall between 200K and 272K input tokens, where Gemini's long-context rates apply and Sol's standard rates still hold.
- You work in Codex, or in GitHub Copilot, which retired Gemini 3.1 Pro Preview on September 1, 2026.
Choose Gemini 3.1 Pro Preview if
- Your sessions write a lot to the cache, since Google bills written tokens as ordinary input and OpenAI charges 1.25x.
- Gemini CLI is your daily tool, and its default auto model already uses Gemini 3.1 Pro Preview for its Pro half.
- Your agent depends on custom tools, which Google says its customtools endpoint is built to prioritize alongside bash.
Side by side
Specs and prices
| Fact | GPT-6 Sol | Gemini 3.1 Pro Preview |
|---|---|---|
| Maker | OpenAI | |
| API model id | gpt-6-sol | gemini-3.1-pro-preview |
| Released | September 22, 2026 | February 19, 2026 |
| Status | Current | Preview |
| Context window | 1.05M tokens | 1.05M tokens |
| Max output | 128K tokens | 65.5K tokens |
| Open weights | No | No |
| Input, per 1M tokens | $2 | $2 |
| Cache hit, per 1M | $0.20 | $0.20 |
| Cache write, per 1M | $2.50 | $2 (same as input) |
| Output, per 1M tokens | $10 | $12 |
| Runs in | Codex, OpenCode, OpenRouter, and GitHub Copilot | Cursor, Gemini CLI, OpenCode, and OpenRouter |
Standard API rates in US dollars, as published by each maker on September 28, 2026. Batch and priority tiers, taxes, and subscription plans are not included. GPT-6 Sol: Requests over 272K input tokens cost 2x for input and cache and 1.5x for output, for the whole request. Gemini 3.1 Pro Preview: Prompts over 200K input tokens cost $4 input, $0.40 cached, and $18 output per million tokens.
Cost
What the same work costs
The same token counts, priced at each model’s published rates. Cached tokens are billed at each maker’s cache prices, so the session shows what caching is worth on each model.
Real sessions differ: the two models count the same code as different numbers of tokens, and reasoning settings change how much each one writes. Your own history is the real test.
| Workload | GPT-6 Sol | Gemini 3.1 Pro Preview |
|---|---|---|
| Agentic coding session, 100K input, 400K written to cache, 2M read from cache, 50K output | $2.10 | $2.00 |
| Large one-off review, 150K input with no cache hits, 10K output | $0.40 | $0.42 |
| Output-heavy generation, 30K input, 80K output | $0.86 | $1.02 |
| A month of sessions, 110 sessions: 5 a day, 22 working days | $231.00 | $220.00 |
| Where the session’s cost goes | ||
| Cache writes | $1.00 | $0.80 |
| Cache reads | $0.40 | $0.40 |
| Uncached input | $0.20 | $0.20 |
| Output | $0.50 | $0.60 |
- caching saves on the session with GPT-6 Sol (62%)
- $3.40
- caching saves on the session with Gemini 3.1 Pro Preview (64%)
- $3.60
Which is cheaper depends on the workload
GPT-6 Sol and Gemini 3.1 Pro Preview charge the same $2 per million input tokens and the same $0.20 per cache hit. They differ in two places: Gemini's output costs $12 against Sol's $10, and Sol's cache writes cost $2.50, 1.25x input, while Google bills writes at the $2 input rate.
Those two differences decide each workload. On the example session, Sol's write premium outweighs Gemini's higher output rate: writes come to $1.00 against $0.80, output to $0.50 against $0.60, and the totals to $2.10 against $2.00. On the uncached review only output differs, so Gemini costs $0.42 against Sol's $0.40. On output-heavy generation Sol is 16% cheaper, $0.86 against $1.02.
Over 110 sessions a month the example comes to $231.00 on Sol and $220.00 on Gemini, an $11.00 difference small enough that reasoning settings can matter more. Both models reason by default, Sol at medium effort and Gemini at a high thinking level it cannot turn off.
Where the long-context lines fall
Both models list a 1.05M context window, but they start charging long-context rates at different points. Google moves Gemini 3.1 Pro Preview to $4 input, $0.40 cached, and $18 output for prompts over 200K input tokens. OpenAI bills a Sol request over 272K input tokens at 2x for input and cache and 1.5x for output, for the whole request, and caps input at 922K tokens.
Between 200K and 272K input tokens, Sol keeps its standard rates while Gemini's go up. Above 272K, both cost more. The example session keeps each request under 200K, so none of this appears in the cost table.
Status, caching controls, and tools
Sol was released on September 22, 2026. The Codex docs recommend it for complex coding, and Codex suggests it in place of GPT-5.6 Sol, GPT-5.6 Terra, and GPT-5.4. Gemini 3.1 Pro Preview has been a preview since February 19, 2026, and Google has announced Gemini 3.5 Pro, which is not yet released.
Caching works differently in practice. On Sol you can mark up to four explicit cache breakpoints, a cached prefix stays reusable for at least 30 minutes after its last use, and caching starts at 1,024 input tokens. Gemini's implicit caching applies its discount automatically but does not assure a hit, while explicit caching assures the discount and adds storage at $4.50 per million tokens per hour on Pro models.
To see which one costs less on your mix of work, EveryToken prices your Codex and Gemini CLI history at each maker's API rates and shows what caching saved or cost per model.
Prompt caching
How each maker bills cached tokens
OpenAI
Prompt caching is on by default. From GPT-5.6 on you can also mark up to four explicit cache breakpoints, while GPT-5.5 and earlier cache automatically only.
From GPT-5.6 on, a cache write costs 1.25x the uncached input price and a cache hit costs 0.1x. GPT-5.5 and earlier add no charge for writing the cache: written tokens are billed as ordinary input, and a hit costs 0.1x on the models compared here.
On GPT-5.6 and later, a cached prefix stays reusable for at least 30 minutes after its last use, and caching starts at 1,024 input tokens.
Source: OpenAI: Prompt caching
Implicit caching is on by default for Gemini 2.5 and newer. When a request repeats a prefix Google has cached, the discount is applied automatically, but a hit is not guaranteed.
Explicit caching creates a cache you reference by name, with a guaranteed discount. It adds a storage charge for as long as the cache lives, 1 hour by default: $4.50 per million tokens per hour on Pro models and $0.50 to $1 on Flash models.
On every model compared here, a cache hit costs 10% of the input price. Google publishes no separate cache-write price, so this blog prices written tokens as ordinary input.
Source: Google: Context caching
Your own numbers
See what GPT-6 Sol and Gemini 3.1 Pro Preview really cost you.
everyaitoken reads your Codex, OpenCode, OpenRouter, Gemini CLI, and Cursor history on your Mac and prices every request at API rates, with what caching saved or cost. $9 once.
FAQ
Questions
Is GPT-6 Sol cheaper than Gemini 3.1 Pro Preview?
It depends on the work. Sol is cheaper on output-heavy generation, $0.86 against $1.02, and Gemini is cheaper on the cached agentic session, $2.00 against $2.10. The differences are small enough that reasoning settings can outweigh them.
Why does GPT-6 Sol cost more on the cached session?
OpenAI charges 1.25x input to write the cache on GPT-5.6 and later, while Google bills written tokens as ordinary input. On the session's 400K written tokens, that makes writes $1.00 on Sol and $0.80 on Gemini.
Which has the larger output limit?
GPT-6 Sol writes up to 128K tokens per response. Gemini 3.1 Pro Preview stops at 65.5K.
Is Gemini 3.1 Pro Preview going to be replaced?
Google has announced Gemini 3.5 Pro but has not released it. Until it does, Gemini 3.1 Pro Preview remains Google's current Pro model and the Pro half of Gemini CLI's default auto model.
Sources
- OpenAI: API pricing
- OpenAI docs: GPT-6 Sol
- OpenAI: Introducing GPT-6 Sol and Luna
- OpenAI: API changelog
- Codex docs: Models
- OpenRouter: GPT-6 Sol
- OpenCode docs: Zen
- GitHub Docs: Supported AI models in Copilot
- Google: Gemini API pricing
- Google docs: Gemini 3.1 Pro Preview
- Google: Gemini models
- Google: Gemini 3.1 Pro
- Google DeepMind: Gemini
- Gemini CLI source: model configuration
- Cursor docs: Gemini 3.1 Pro
- OpenRouter: Gemini 3.1 Pro Preview
- OpenAI: Prompt caching
- Google: Context caching