GPT-5.6 Sol vs Gemini 3.1 Pro: Benchmarks, Price & Which to Pick (2026)

Comparison · August 2026

GPT-5.6 Sol (OpenAI API) and Gemini 3.1 Pro Preview (Google API) are two ~1.05M Pro-class models with the same $2/M input sticker. The split is output price, modalities, and voice. This guide covers published API rates, three workload costs, live writing and coding snippets, and a routing matrix. Keep both if you mix send-ready prose with audio/video packs. Start in a multi-model AI workspace or on i10X.

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Persona picker

You are…	Start with	Why
Writer / marketer	GPT-5.6 Sol	Sol kept every fact in two tight paragraphs. Gemini added week-greeting filler and truncated in our capture.
Developer / agent builder	Sol default. Gemini for multimodal packs.	Empty-list bug was a tie. Sol is slightly cheaper on output. Gemini’s card adds audio and video.
Researcher / analyst	Gemini if the pack has recordings. Sol for text.	Windows are a hair (1,050,000 vs 1,048,576). Modalities are not.
Budget / high volume	GPT-5.6 Sol, slightly	Same $2 input and $0.20 cache. $10 vs $12 output. Chat $0.007 vs $0.008. Repo $0.20 vs $0.208. Agent $0.42 vs $0.46.

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What we are comparing (exact versions)

This page is GPT-5.6 Sol versus Gemini 3.1 Pro Preview, not ChatGPT vs the Gemini app, and not GPT-5.5. For the prior OpenAI ID see GPT-5.5 vs Gemini 3.1 Pro. For Grok in this lane see Grok 4.6 vs Gemini 3.1 Pro and Grok 4.6 vs GPT-5.6 Sol.

Field	GPT-5.6 Sol	Gemini 3.1 Pro
Provider	OpenAI	Google
API model	GPT-5.6 Sol (OpenAI API)	Gemini 3.1 Pro Preview (Google API)
Listed card name	OpenAI: GPT-5.6 Sol	Google: Gemini 3.1 Pro Preview
Family / tier	GPT-5.6 series flagship	Gemini Pro-class preview
App vs API note	Also in ChatGPT-family apps. This article uses the API model.	Also in Gemini app / Google AI Pro. This article uses the API preview model.

Preview IDs move. Do not mix Sol prices with GPT-5.5 prices. For routing across many models, see AI model routing.

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Spec sheet (API card, 2026-08-24)

Spec	GPT-5.6 Sol	Gemini 3.1 Pro Preview
Context window	1,050,000 tokens	1,048,576 tokens
Input modalities (card)	text, image, file	text, image, file, audio, video
Output	text	text
Open weights	No	No
Vendor positioning (card)	GPT-5.6 flagship for complex reasoning, coding, and agentic workflows. Particularly strong at command-line and multi-step coding.	Frontier reasoning. Enhanced software engineering, agentic reliability, efficient token use, multimodal foundation.

We did not invent max-output or reasoning-effort rows. Confirm those on live vendor pages. Context is a rounding error. Audio and video are not.

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Pricing and real workload cost

Matched input and matched cache. Output is the wedge. Rates as of 2026-08-24. Verify live.

Price	GPT-5.6 Sol	Gemini 3.1 Pro Preview
Input / 1M tokens	$2.00	$2.00
Output / 1M tokens	$10.00	$12.00
Cache read / 1M	$0.20	$0.20

Same $2 input. Same $0.20 cache. Gemini costs 20% more on output. That is small next to Opus-class gaps, and it still compounds on output-heavy jobs.

Scenario	Assumed tokens	Est. GPT-5.6 Sol	Est. Gemini 3.1 Pro
Chat turn	1k in + 0.5k out	$0.007	$0.008
Repo / doc review	80k in + 4k out	$0.200	$0.208
Agent loop	200k in (50% cached) + 20k out	$0.420	$0.460

Repo review is almost a tie ($0.200 vs $0.208) because that recipe is input-heavy. The agent loop shows the output wedge ($0.42 vs $0.46). If you need a cheaper third model, Grok 4.6 is $6 output at the same $2 input. See Grok 4.6 vs GPT-5.6 Sol. For subscription math, see AI subscription stack cost.

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Performance by job (not one score)

No invented index numbers for this pair. Cards, modalities, prices, and three live prompts. Re-run on your workload. Method: side-by-side AI comparison.

Coding and agents

OpenAI’s card singles out command-line and multi-step coding for Sol. Google’s card talks enhanced software engineering and agentic reliability for Gemini 3.1 Pro Preview. Our micro-test: both named ZeroDivisionError and wrote if not nums: return 0. Sol added print(average([])). Same guard. Tie on correctness. Use that as a quality-of-life note, not as a championship. For huge multimodal repos (screenshot + video + code), Gemini’s extra modalities matter more than this snippet. For cheap text-only loops, Sol’s $10 output is the small structural edge.

Writing and tone

This is the clearest live split in the pack. Sol (sanitized): name slot, two paragraphs, Finance still out after Friday, move to next Wednesday, update competitive slide with Acme pricing, “Thanks!” Gemini (sanitized): client-name slot, “hope you are having a great week,” same Tuesday/Friday miss with softer “just yet,” Wednesday push, then the capture dies at “we sti…” Sol is send-ready. Gemini is a warmer template with extra cheer the source did not contain, and the snippet never reaches Acme. If your brand hates filler, start Sol.

Research, math, reasoning

No science-QA pack here. False-premise: both refused the green-cheese Moon. Sol listed a practical lunar-resource plan (polar ice, purify/split water, habitat protein, recycle). Gemini said a protein-mining plan is not possible and offered Apollo or Artemis instead. Both pass the refuse bar. Sol is more operational after the refuse. Gemini is stricter about not building a plan on the false premise. For publishable work, still use multi-model hallucination checks.

Multimodal and long context

Windows match for practical purposes: 1,050,000 vs 1,048,576. Gemini lists audio and video. Sol lists text, image, file. That is the routing rule. Text-first long packs can go either way. Recordings go to Gemini. We did not run a vision bake-off, so we will not invent a screenshot winner.

Speed

No tok/s in this pack. Writeups often say Gemini streams quickly. Measure p50 in your region. Preview endpoints can move. Do not ship on a screenshot.

Job	Edge	Why
Hard coding / agents	Split	Micro-test tie. Sol: command-line positioning and $10 output. Gemini: multimodal packs.
Everyday writing	GPT-5.6 Sol	Tighter, complete, less filler in our rewrite.
Long docs / multimodal	Gemini 3.1 Pro for media. Tie for text.	Same-class context. Gemini adds audio/video.
Realtime / conversational	Product-dependent	ChatGPT apps vs Gemini app / Workspace. Not measured here.
Cost at volume	GPT-5.6 Sol, slightly	$10 vs $12 output. Same input and cache.

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Side-by-side test (i10X pack, 2026-08-24)

Three prompts. Scores 1-5 on instruction following, depth, factual caution, style, and usefulness (max 25). No invented extra tests.

Test 1: Client email rewrite

Task: Keep every fact. Warmer. Under 120 words.

GPT-5.6 Sol (excerpt, sanitized): Hi [Name]. Follow-up on the Q3 deck from last Tuesday. Still waiting on Finance after the Friday promise. Move stakeholders to next Wednesday if it works. Update the competitive slide with new Acme pricing. Thanks!

Gemini 3.1 Pro (excerpt, sanitized): Hi [Client Name]. Hope you are having a great week. Quick update on the Q3 deck. Finance expected Friday, “haven’t received them just yet.” Push to next week, Wednesday would be great. Then the snippet cuts at “we sti…”

Edge: Sol, clearly, on this capture. Complete facts, no extra cheer, finished letter. Gemini warmer and unfinished.

Test 2: Empty-list average bug

Both named ZeroDivisionError. Both guard empty input before dividing. Sol includes a print smoke check. Gemini’s explanation of the missing empty check is a bit longer. Same fix. Tie on this micro-task.

Test 3: False premise (Moon cheese)

Sol: silicate rock and metal, no mineable protein, then four resource steps (ice, water split, habitat protein, recycle). Gemini: minerals, dust, basaltic rock, no organics, protein mining plan is not possible, redirect to Apollo or Artemis. Both pass. Sol more useful if you still want a next step. Gemini more strict about not fulfilling the false ask.

Prompt type	GPT-5.6 Sol	Gemini 3.1 Pro	Note
Client email rewrite	24/25	21/25	Sol complete and tight. Gemini filler plus truncated ending.
Bug explain + minimal fix	24/25	24/25	Both catch ZeroDivisionError. Tie.
Logic + false premise	24/25	23/25	Both refuse. Sol adds a resource plan. Gemini refuses to plan on the false premise.
Total	72/75	68/75	Sol on this prose pack. Gemini still wins audio/video.

Four editorial points do not erase Gemini’s modality list. They do mean Sol is the safer default for text-only client work in this pack.

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Ecosystem and where you run them

• GPT-5.6 Sol: OpenAI API. ChatGPT-family apps may wrap different defaults. This page is the GPT-5.6 flagship, not GPT-5.5.
• Gemini 3.1 Pro: Google AI / Gemini app / Workspace adjacency. API preview access. Strength in Docs/Drive/Search worlds and multimodal inputs.
• Both in one place: i10X lets you compare the same prompt without two browser profiles.

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Pros, cons, and failure modes

GPT-5.6 Sol

• Pros: Tighter complete email in our pack. $10 vs $12 output at matched $2 input and $0.20 cache. 1.05M context. Runnable coding snippet with a smoke print. Card aimed at command-line and multi-step coding.
• Cons: No audio/video on this card. False-premise answer still constructs an alternative plan. Not the cheapest flagship (Grok is $6 output).
• Fails when: the input is a meeting recording or product video, and Sol is the only model in the router.

Gemini 3.1 Pro

• Pros: Audio and video on the card. Same-class context. Same input and cache stickers. Clean coding guard. Strict refuse on the false mining plan.
• Cons: $12 vs $10 output. Email filler plus a truncated capture. Preview ID can move.
• Fails when: you need send-ready client prose without an edit pass, or you treat Preview as a frozen production ID without re-checking the card.

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Decision guide: pick one or route both

If you need…	Choose
Send-ready client email	GPT-5.6 Sol
Audio / video / mixed media rooms	Gemini 3.1 Pro
Text-only volume at Pro-class quality	GPT-5.6 Sol (or Grok if you need $6 output)
Google Workspace adjacency	Gemini 3.1 Pro
Mixed week	Keep both. Sol text default. Gemini media.

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Application walkthroughs: where each model is better

1) Customer support email

Better: GPT-5.6 Sol. Complete facts, name slot, no invented week-greeting, finished Acme line. Gemini was warmer and unfinished in our capture. If managers want extra polish, add the greeting by hand on a Sol draft.

2) Long PDF / research pack

Tie on window. 1.05M vs 1.048M will not decide a text pack. Attach audio or video and the job becomes Gemini. Attach only PDFs and you can stay on Sol for the slightly cheaper output.

3) Everyday Python scripting

Tie on the micro-test. Both catch the empty-list crash. Sol’s print check is a small plus. Gemini’s extra modalities help when the bug is in a screenshot or a recorded repro. Do not overclaim from average().

4) Screenshot, UI QA, and video

Gemini 3.1 Pro when the input is video or audio. Both cards list image. We did not run a vision eval in this pack. A/B your actual captures. For a Grok vision note on a related pair, see Grok 4.6 vs Gemini 3.1 Pro, and do not copy those scores onto Sol without a new pull.

5) Output-heavy generation at API scale

Better on cost: GPT-5.6 Sol, slightly. $0.007 vs $0.008 chat. $0.20 vs $0.208 repo. $0.42 vs $0.46 cached agent. If the gap is too small to care, route on modalities instead. If the gap is still too expensive, add Grok 4.6 as the volume lane.

6) False-premise and trust gates

Both pass. Sol for a useful redirect. Gemini for a hard “no plan exists on that premise.” Second-model check publishable claims. See also Claude Opus 5 vs GPT-5.5 if you want the prior OpenAI flagship in a trust bake-off with Opus.

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Consumer plans vs API (do not mix them up)

• API comparison (this article): GPT-5.6 Sol (OpenAI API) vs Gemini 3.1 Pro Preview (Google API).
• Consumer apps: ChatGPT plans vs Google AI Pro / Gemini app may hide cheaper siblings (Flash, mini, nano-style tiers), different tools, and different rate limits.

Phone-app feel is a lived week. Agent IDs are this page.

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Speed notes

No tok/s in this pack. Log p50 and p95 from your API region. Preview Gemini endpoints and Sol effort settings, if you enable them, will move latency more than the $2 input sticker.

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Related comparisons

• GPT-5.5 vs Gemini 3.1 Pro for the prior OpenAI ID.
• Grok 4.6 vs Gemini 3.1 Pro if you want $6 output against Gemini.
• Grok 4.6 vs GPT-5.6 Sol
• Claude Opus 5 vs GPT-5.6 Sol
• Claude Opus 5 vs Gemini 3.1 Pro
• Claude Opus 5 vs GPT-5.5

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Frequently asked questions

Which is better overall, GPT-5.6 Sol or Gemini 3.1 Pro?
Sol won our three-prompt pack (72/75 vs 68/75) on writing tightness. Gemini wins audio/video. Cost is close, with a small Sol edge on output. Pick by job.

Which is better for coding?
Tie on the empty-list guard. Both catch ZeroDivisionError. Sol’s card highlights command-line and multi-step coding. Gemini’s card highlights software engineering and agentic reliability. Run your repo. For code plus video, start Gemini.

Which is better for writing?
GPT-5.6 Sol on this prompt. Complete, tight, no extra week-greeting. Gemini was warmer and truncated. A/B if your brand wants that extra polish.

Which is cheaper?
GPT-5.6 Sol, slightly, at 2026-08-24 list rates: $10 vs $12 output, same $2 input, same $0.20 cache. The gap is small on input-heavy repo review.

Which has the larger context window?
GPT-5.6 Sol (1,050,000) vs Gemini 3.1 Pro Preview (1,048,576). Treat them as the same class.

Do I need both?
If your week mixes send-ready email with meeting recordings, yes. Sol text default, Gemini media.

Are we comparing apps or API models?
API models GPT-5.6 Sol (OpenAI API) and Gemini 3.1 Pro Preview (Google API).

How often should I re-test?
After version bumps, after Preview card changes, monthly in production, and whenever list rates move.

Where can I run them side by side?
i10X. Method: side-by-side AI comparison.

What about hallucinations and trust?
Both refused the Moon-cheese trap. Still ground publishable claims. Multi-model hallucination checks.

Is GPT-5.6 Sol the same as GPT-5.5?
No. Different series and different comparison page. Do not copy GPT-5.5 prices onto Sol.

Should I just use Grok instead of both?
Use Grok if output price is the constraint ($6 vs $10/$12) and 500K context is enough. Keep Sol or Gemini when you need ~1M or audio/video.

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