{"id":500,"date":"2026-08-25T06:32:48","date_gmt":"2026-08-25T06:32:48","guid":{"rendered":"https:\/\/i10x.ai\/blog\/?p=500"},"modified":"2026-08-25T06:33:15","modified_gmt":"2026-08-25T06:33:15","slug":"gpt-5-6-sol-vs-gemini-3-1-pro","status":"publish","type":"post","link":"https:\/\/i10x.ai\/blog\/gpt-5-6-sol-vs-gemini-3-1-pro","title":{"rendered":"GPT-5.6 Sol vs Gemini 3.1 Pro: Benchmarks, Price & Which to Pick (2026)"},"content":{"rendered":"\n
\n\n

Comparison \u00b7 August 2026<\/p>\n\n

\nGPT-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\nmulti-model AI workspace<\/a>\nor on\ni10X<\/a>.\n<\/p>\n\n

\nQuick verdict<\/strong>\n

Pick GPT-5.6 Sol if:<\/strong> you want tighter send-ready email, a slightly cheaper output rate ($10 vs $12), and OpenAI\u2019s flagship positioning for command-line and multi-step coding.<\/p>\n

Pick Gemini 3.1 Pro if:<\/strong> you need native audio and video input, Google-ecosystem fit, or a model that refuses to build a plan on a false premise and redirects to real missions.<\/p>\n

Best default for many teams:<\/strong> Sol for text-first flagship work. Gemini when the file is a recording. Same cache read ($0.20). Do not freeze one ID for every job.<\/p>\n

Data checked: 2026-08-24. Prices and model cards change. Verify live API test and vendor pages.<\/em><\/p>\n<\/div>\n\n

\n\n\n\n\n\n\n

1.05M<\/strong><\/p><\/td>\n

GPT-5.6 Sol context (API)<\/p><\/td>\n<\/tr>\n

1.05M<\/strong><\/p><\/td>\n

Gemini 3.1 Pro Preview context (API)<\/p><\/td>\n<\/tr>\n

$2 \/ $10<\/strong><\/p><\/td>\n

GPT-5.6 Sol input\/output per 1M tokens (API pricing, 2026-08-24)<\/p><\/td>\n<\/tr>\n

$2 \/ $12<\/strong><\/p><\/td>\n

Gemini 3.1 Pro Preview input\/output per 1M tokens (API pricing, 2026-08-24)<\/p><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n\n

\n\"Bar\n
Figure 1.<\/strong> Where each model wins on relative axes (context, multimodal breadth, output cost efficiency, writing tightness vs filler, coding micro-test). Higher is stronger for that axis. Chart: i10X.<\/figcaption>\n<\/figure>\n\n
\n\n

Persona picker<\/h2>\n\n\n\n\n\n\n\n

You are\u2026<\/p><\/th>\n

Start with<\/p><\/th>\n

Why<\/p><\/th>\n<\/tr>\n

Writer \/ marketer<\/p><\/td>\n

GPT-5.6 Sol<\/p><\/td>\n

Sol kept every fact in two tight paragraphs. Gemini added week-greeting filler and truncated in our capture.<\/p><\/td>\n<\/tr>\n

Developer \/ agent builder<\/p><\/td>\n

Sol default. Gemini for multimodal packs.<\/p><\/td>\n

Empty-list bug was a tie. Sol is slightly cheaper on output. Gemini\u2019s card adds audio and video.<\/p><\/td>\n<\/tr>\n

Researcher \/ analyst<\/p><\/td>\n

Gemini if the pack has recordings. Sol for text.<\/p><\/td>\n

Windows are a hair (1,050,000 vs 1,048,576). Modalities are not.<\/p><\/td>\n<\/tr>\n

Budget \/ high volume<\/p><\/td>\n

GPT-5.6 Sol, slightly<\/p><\/td>\n

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.<\/p><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n

\n\n

What we are comparing (exact versions)<\/h2>\n

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\nGPT-5.5 vs Gemini 3.1 Pro<\/a>.\nFor Grok in this lane see\nGrok 4.6 vs Gemini 3.1 Pro<\/a>\nand\nGrok 4.6 vs GPT-5.6 Sol<\/a>.<\/p>\n\n\n\n\n\n\n\n\n

Field<\/p><\/th>\n

GPT-5.6 Sol<\/p><\/th>\n

Gemini 3.1 Pro<\/p><\/th>\n<\/tr>\n

Provider<\/p><\/td>\n

OpenAI<\/p><\/td>\n

Google<\/p><\/td>\n<\/tr>\n

API model<\/p><\/td>\n

GPT-5.6 Sol (OpenAI API)<\/code><\/p><\/td>\n

Gemini 3.1 Pro Preview (Google API)<\/code><\/p><\/td>\n<\/tr>\n

Listed card name<\/p><\/td>\n

OpenAI: GPT-5.6 Sol<\/p><\/td>\n

Google: Gemini 3.1 Pro Preview<\/p><\/td>\n<\/tr>\n

Family \/ tier<\/p><\/td>\n

GPT-5.6 series flagship<\/p><\/td>\n

Gemini Pro-class preview<\/p><\/td>\n<\/tr>\n

App vs API note<\/p><\/td>\n

Also in ChatGPT-family apps. This article uses the API model.<\/p><\/td>\n

Also in Gemini app \/ Google AI Pro. This article uses the API preview model.<\/p><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Preview IDs move. Do not mix Sol prices with GPT-5.5 prices. For routing across many models, see\nAI model routing<\/a>.<\/p>\n\n

\n\n

Spec sheet (API card, 2026-08-24)<\/h2>\n\n\n\n\n\n\n\n\n

Spec<\/p><\/th>\n

GPT-5.6 Sol<\/p><\/th>\n

Gemini 3.1 Pro Preview<\/p><\/th>\n<\/tr>\n

Context window<\/p><\/td>\n

1,050,000 tokens<\/p><\/td>\n

1,048,576 tokens<\/p><\/td>\n<\/tr>\n

Input modalities (card)<\/p><\/td>\n

text, image, file<\/p><\/td>\n

text, image, file, audio, video<\/p><\/td>\n<\/tr>\n

Output<\/p><\/td>\n

text<\/p><\/td>\n

text<\/p><\/td>\n<\/tr>\n

Open weights<\/p><\/td>\n

No<\/p><\/td>\n

No<\/p><\/td>\n<\/tr>\n

Vendor positioning (card)<\/p><\/td>\n

GPT-5.6 flagship for complex reasoning, coding, and agentic workflows. Particularly strong at command-line and multi-step coding.<\/p><\/td>\n

Frontier reasoning. Enhanced software engineering, agentic reliability, efficient token use, multimodal foundation.<\/p><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

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.<\/p>\n\n

\n\n

Pricing and real workload cost<\/h2>\n

Matched input and matched cache. Output is the wedge. Rates as of 2026-08-24<\/strong>. Verify live.<\/strong><\/p>\n\n\n\n\n\n\n

Price<\/p><\/th>\n

GPT-5.6 Sol<\/p><\/th>\n

Gemini 3.1 Pro Preview<\/p><\/th>\n<\/tr>\n

Input \/ 1M tokens<\/p><\/td>\n

$2.00<\/p><\/td>\n

$2.00<\/p><\/td>\n<\/tr>\n

Output \/ 1M tokens<\/p><\/td>\n

$10.00<\/p><\/td>\n

$12.00<\/p><\/td>\n<\/tr>\n

Cache read \/ 1M<\/p><\/td>\n

$0.20<\/p><\/td>\n

$0.20<\/p><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

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.<\/p>\n\n\n\n\n\n\n

Scenario<\/p><\/th>\n

Assumed tokens<\/p><\/th>\n

Est. GPT-5.6 Sol<\/p><\/th>\n

Est. Gemini 3.1 Pro<\/p><\/th>\n<\/tr>\n

Chat turn<\/p><\/td>\n

1k in + 0.5k out<\/p><\/td>\n

$0.007<\/p><\/td>\n

$0.008<\/p><\/td>\n<\/tr>\n

Repo \/ doc review<\/p><\/td>\n

80k in + 4k out<\/p><\/td>\n

$0.200<\/p><\/td>\n

$0.208<\/p><\/td>\n<\/tr>\n

Agent loop<\/p><\/td>\n

200k in (50% cached) + 20k out<\/p><\/td>\n

$0.420<\/p><\/td>\n

$0.460<\/p><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\n\"Bar\n
Figure 2.<\/strong> Estimated USD per run using published API list rates (2026-08-24). Chat is 1k in + 0.5k out. Repo review is 80k in + 4k out. Agent loop is 200k in with 50% cache hits + 20k out. Chart: i10X.<\/figcaption>\n<\/figure>\n

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\nGrok 4.6 vs GPT-5.6 Sol<\/a>.\nFor subscription math, see\nAI subscription stack cost<\/a>.<\/p>\n\n

\n\n

Performance by job (not one score)<\/h2>\n

No invented index numbers for this pair. Cards, modalities, prices, and three live prompts. Re-run on your workload. Method:\nside-by-side AI comparison<\/a>.<\/p>\n\n

Coding and agents<\/h3>\n

OpenAI\u2019s card singles out command-line and multi-step coding for Sol. Google\u2019s card talks enhanced software engineering and agentic reliability for Gemini 3.1 Pro Preview. Our micro-test: both named ZeroDivisionError<\/code> and wrote if not nums: return 0<\/code>. Sol added print(average([]))<\/code>. Same guard. Tie<\/strong> on correctness. Use that as a quality-of-life note, not as a championship. For huge multimodal repos (screenshot + video + code), Gemini\u2019s extra modalities matter more than this snippet. For cheap text-only loops, Sol\u2019s $10 output is the small structural edge.<\/p>\n\n

Writing and tone<\/h3>\n

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, \u201cThanks!\u201d Gemini (sanitized): client-name slot, \u201chope you are having a great week,\u201d same Tuesday\/Friday miss with softer \u201cjust yet,\u201d Wednesday push, then the capture dies at \u201cwe sti\u2026\u201d 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.<\/p>\n\n

Research, math, reasoning<\/h3>\n

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\nmulti-model hallucination checks<\/a>.<\/p>\n\n

Multimodal and long context<\/h3>\n

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.<\/p>\n\n

Speed<\/h3>\n

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.<\/p>\n\n\n\n\n\n\n\n\n\n

Job<\/p><\/th>\n

Edge<\/p><\/th>\n

Why<\/p><\/th>\n<\/tr>\n

Hard coding \/ agents<\/p><\/td>\n

Split<\/p><\/td>\n

Micro-test tie. Sol: command-line positioning and $10 output. Gemini: multimodal packs.<\/p><\/td>\n<\/tr>\n

Everyday writing<\/p><\/td>\n

GPT-5.6 Sol<\/p><\/td>\n

Tighter, complete, less filler in our rewrite.<\/p><\/td>\n<\/tr>\n

Long docs \/ multimodal<\/p><\/td>\n

Gemini 3.1 Pro for media. Tie for text.<\/p><\/td>\n

Same-class context. Gemini adds audio\/video.<\/p><\/td>\n<\/tr>\n

Realtime \/ conversational<\/p><\/td>\n

Product-dependent<\/p><\/td>\n

ChatGPT apps vs Gemini app \/ Workspace. Not measured here.<\/p><\/td>\n<\/tr>\n

Cost at volume<\/p><\/td>\n

GPT-5.6 Sol, slightly<\/p><\/td>\n

$10 vs $12 output. Same input and cache.<\/p><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n

\nHow to read benchmarks<\/strong>\n

When we lack a primary public table for this exact pair, we do not invent one. Card positioning plus a live pack is the honest floor. Re-test on your workload.<\/p>\n<\/div>\n\n

\n\n

Side-by-side test (i10X pack, 2026-08-24)<\/h2>\n

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

Test 1: Client email rewrite<\/h3>\n

Task:<\/strong> Keep every fact. Warmer. Under 120 words.<\/p>\n

GPT-5.6 Sol (excerpt, sanitized):<\/strong> 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!<\/p>\n

Gemini 3.1 Pro (excerpt, sanitized):<\/strong> Hi [Client Name]. Hope you are having a great week. Quick update on the Q3 deck. Finance expected Friday, \u201chaven\u2019t received them just yet.\u201d Push to next week, Wednesday would be great. Then the snippet cuts at \u201cwe sti\u2026\u201d<\/p>\n

Edge:<\/strong> Sol, clearly, on this capture. Complete facts, no extra cheer, finished letter. Gemini warmer and unfinished.<\/p>\n\n

Test 2: Empty-list average bug<\/h3>\n

Both named ZeroDivisionError<\/code>. Both guard empty input before dividing. Sol includes a print smoke check. Gemini\u2019s explanation of the missing empty check is a bit longer. Same fix. Tie<\/strong> on this micro-task.<\/p>\n\n

Test 3: False premise (Moon cheese)<\/h3>\n

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.<\/strong> Sol more useful if you still want a next step. Gemini more strict about not fulfilling the false ask.<\/p>\n\n\n\n\n\n\n\n\n

Prompt type<\/p><\/th>\n

GPT-5.6 Sol<\/p><\/th>\n

Gemini 3.1 Pro<\/p><\/th>\n

Note<\/p><\/th>\n<\/tr>\n

Client email rewrite<\/p><\/td>\n

24\/25<\/p><\/td>\n

21\/25<\/p><\/td>\n

Sol complete and tight. Gemini filler plus truncated ending.<\/p><\/td>\n<\/tr>\n

Bug explain + minimal fix<\/p><\/td>\n

24\/25<\/p><\/td>\n

24\/25<\/p><\/td>\n

Both catch ZeroDivisionError. Tie.<\/p><\/td>\n<\/tr>\n

Logic + false premise<\/p><\/td>\n

24\/25<\/p><\/td>\n

23\/25<\/p><\/td>\n

Both refuse. Sol adds a resource plan. Gemini refuses to plan on the false premise.<\/p><\/td>\n<\/tr>\n

Total<\/strong><\/p><\/td>\n

72\/75<\/strong><\/p><\/td>\n

68\/75<\/strong><\/p><\/td>\n

Sol on this prose pack. Gemini still wins audio\/video.<\/p><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Four editorial points do not erase Gemini\u2019s modality list. They do mean Sol is the safer default for text-only client work in this pack.<\/p>\n\n

\n\n

Ecosystem and where you run them<\/h2>\n