Grok 4.6 vs GPT-5.6 Sol: Benchmarks, Price & Which to Pick (2026)

Comparison · August 2026

Grok 4.6 (xAI API) and GPT-5.6 Sol (OpenAI API) are two flagship chat models teams actually route in 2026. This is a decision guide, not a leaderboard dump: published API rates, three workload cost scenarios, live writing and coding snippets, and a pick matrix you can rerun. If you want both without juggling tabs, use a multi-model AI workspace or start on i10X.

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Persona picker

You are…	Start with	Why
Writer / marketer	GPT-5.6 Sol (often); Grok for terse ops email	In our rewrite, GPT-5.6 Sol was more client-ready (name, two tight paragraphs, all facts). Grok kept every fact with less polish.
Developer / agent builder	Either for small bugs; GPT-5.6 Sol for huge repos	Our empty-list bug fix was a tie. Sol’s 1.05M context and cheaper cache matter more on long agent loops than this micro-test.
Researcher / analyst	GPT-5.6 Sol	About 2× the context (1.05M vs 500K) for long packs. Same text/image/file input set on the cards we pulled.
Budget / high volume	Grok 4.6	Matched $2/M input, $6 vs $10 output. Grok wins every stylized workload we priced, including the cached agent loop.

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What we are comparing (exact versions)

This page compares two specific API models, not vague “Grok vs GPT” brands and not GPT-5.5. See GPT-5.5 vs Gemini 3.1 Pro and Claude Opus 5 vs GPT-5.5.

Field	Grok 4.6	GPT-5.6 Sol
Provider	xAI (listed as SpaceXAI on the API card)	OpenAI
API model	Grok 4.6 (xAI API)	GPT-5.6 Sol (OpenAI API)
Listed card name	SpaceXAI: Grok 4.6	OpenAI: GPT-5.6 Sol
Family / tier	xAI flagship	GPT-5.6 series flagship
App vs API note	Also in xAI / X products; this article uses the API model above	Also in ChatGPT-family apps; this article uses the API model above

If a page still compares Grok 4 or GPT-5.5 as if they were these IDs, treat it as historical. For routing across many models, see AI model routing.

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

Spec	Grok 4.6	GPT-5.6 Sol
Context window	500,000 tokens	1,050,000 tokens
Input modalities (card)	text, image, file	text, image, file
Output	text	text
Open weights	No	No
Vendor positioning (card)	Smartest xAI model; frontier coding, knowledge work, and STEM	GPT-5.6 flagship; complex reasoning, coding, agentic workflows; strong at command-line and multi-step coding

We did not invent max-output, reasoning-mode, or realtime-search rows. Those fields were not on the cards we pulled for this pair. If your product depends on a specific tool or effort switch, confirm it on the live vendor page before you ship.

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Pricing and real workload cost

List prices are easy to game. Workload cost is what you feel. Numbers below use published per-million rates as of 2026-08-24. Verify live before you budget.

Price	Grok 4.6	GPT-5.6 Sol
Input / 1M tokens	$2.00	$2.00
Output / 1M tokens	$6.00	$10.00
Cache read / 1M	$0.50	$0.20

Same input sticker. Grok is cheaper on output ($6 vs $10). Sol is cheaper on cache reads ($0.20 vs $0.50). If your agent stack actually hits cache, that gap matters. If it does not, output price dominates.

Scenario	Assumed tokens	Est. Grok 4.6	Est. GPT-5.6 Sol
Chat turn	1k in + 0.5k out	$0.005	$0.007
Repo / doc review	80k in + 4k out	$0.184	$0.200
Agent loop	200k in (50% cached) + 20k out	$0.370	$0.420

Grok still wins the cached agent loop ($0.37 vs $0.42) because output outweighs Sol’s cheaper cache in this recipe. Re-run the math if you cache harder. For subscription stacks, see AI subscription stack cost.

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Performance by job (not one score)

Public benches disagree by harness, effort mode, and date. We are not inventing index numbers we do not have for this pair. Treat vendor cards as positioning, treat our snippets as a small live pack, and prefer your own side-by-side on your prompts. Method: side-by-side AI comparison.

Coding and agents

xAI’s card calls Grok 4.6 its smartest model for coding, knowledge work, and STEM. OpenAI’s card calls Sol the GPT-5.6 flagship and singles out command-line and multi-step coding. Those are positioning lines, not benches. Our micro-test was a tie: both named ZeroDivisionError and wrote the same empty-list guard. For huge repos, Sol’s 1.05M window is the structural advantage. For volume loops, Grok’s output rate is.

Writing and tone

Grok stayed complete and slightly telegram-like (no name slot, every operational fact). Sol compressed the same facts into a cleaner two-paragraph letter. If your brand wants send-ready client email, Sol was closer. If you hate filler, both beat the warmer Gemini-style templates on other pairs.

Research, math, reasoning

We did not run a science-QA pack, so we will not fake one. Both refused the green-cheese Moon. Grok stopped at “no mining plan exists.” Sol refused, then listed polar ice, water split, habitat protein, and recycle loops. Usefulness split, not a math proof. For publishable work, add multi-model hallucination checks.

Multimodal and long context

Both cards list text, image, and file in, text out. No audio or video in this pull. The live gap is 500K vs 1.05M. Giant packs go to Sol. Short threads can stay on Grok. For audio/video, see Grok 4.6 vs Gemini 3.1 Pro and GPT-5.6 Sol vs Gemini 3.1 Pro.

Speed

No tok/s in this pack. Measure p50 from your API region. Do not ship on a third-party screenshot.

Job	Edge	Why
Hard coding / agents	Split	Micro-test tie. Sol: context + cheaper cache + command-line positioning. Grok: cheaper output.
Everyday writing	GPT-5.6 Sol	Tighter client email in our rewrite. Grok still complete, less polished.
Long docs / multimodal	GPT-5.6 Sol	1.05M vs 500K. Same text/image/file set. Neither is the audio/video specialist.
Realtime / conversational	Product-dependent	Grok family is strong in xAI/X product contexts. Confirm tools in your app. Not measured here.
Cost at volume	Grok 4.6	$6 vs $10 output. Cheaper on chat, repo, and our cached agent recipe.

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

Same three prompts, scored 1-5 on instruction following, depth, factual caution, style, and usefulness (max 25). Writing, coding, and false premise only. No invented extra scores.

Test 1: Client email rewrite

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

Grok 4.6 (excerpt, sanitized): Q3 deck last Tuesday. Finance still missing after Friday. Push stakeholders to next week, perhaps Wednesday. Competitive slide needs new Acme pricing. “Thank you!” No name slot.

GPT-5.6 Sol (excerpt, sanitized): Same facts in two tight paragraphs, [Name] slot, a single Wednesday ask, complete Acme line, “Thanks!”

Edge: Sol for send-ready tightness. Grok for fidelity with zero extra cheer. Neither added Gemini-style week-greeting filler.

Test 2: Empty-list average bug

Both named ZeroDivisionError and proposed if not nums: return 0. Sol added print(average([])). Same fix. Tie.

Test 3: False premise (Moon cheese)

Both refused first. Grok: silicate rock, no protein, no mining plan exists. Sol: same refuse, then polar ice, water split, habitat protein, recycle. Both pass. Grok shorter. Sol more pedagogical.

Prompt type	Grok 4.6	GPT-5.6 Sol	Note
Client email rewrite	22/25	24/25	Sol tighter and more send-ready. Grok complete, less polished.
Bug explain + minimal fix	24/25	24/25	Both catch ZeroDivisionError. Tie.
Logic + false premise	22/25	24/25	Both refuse. Grok shorter. Sol adds a useful redirect.
Total	68/75	72/75	Close. Jobs still split on cost and context.

Sol wins this pack on writing tightness. That does not erase Grok’s output-price win. Route the next step.

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Ecosystem and where you run them

• Grok 4.6: xAI API. Consumer Grok experiences on xAI and X. Strength in product contexts that sit next to the X graph (confirm tools enabled in your app).
• GPT-5.6 Sol: OpenAI API. ChatGPT-family apps may wrap different defaults, rate limits, or bundled models. This page is the API flagship in the GPT-5.6 series, not GPT-5.5.
• Both in one place: Multi-model workspaces (including i10X) let you switch or compare without two native subscriptions for every test.

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Pros, cons, and failure modes

Grok 4.6

• Pros: Cheaper output at matched $2 input. Cheaper on all three workload recipes. Concise factual writing in our rewrite. Solid everyday coding loop on the micro-test. 500K is still a large window.
• Cons: Half the context of Sol. More expensive cache reads ($0.50 vs $0.20). Writing was complete but less client-ready. Card does not list audio/video.
• Fails when: you shove million-token packs into it as the only model, or you need a send-ready client letter without an edit pass.

GPT-5.6 Sol

• Pros: 1.05M context. Cheaper cache. Tighter client email in our pack. Vendor card aimed at command-line and multi-step coding. Same text/image/file input set as Grok.
• Cons: $10 vs $6 output. Slightly higher cost on chat, repo, and our cached agent recipe. Still not the audio/video specialist.
• Fails when: you optimize purely for output-token burn at scale, or you assume ChatGPT app behavior matches this API ID.

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Decision guide: pick one or route both

If you need…	Choose
Output-cheap high volume text	Grok 4.6
Long PDF / giant repo packs	GPT-5.6 Sol
Send-ready client email	GPT-5.6 Sol first. A/B Grok if you want less polish.
Cache-heavy agent loops	Re-price. Sol cache is cheaper. Grok still won our 50% cache recipe on output.
Mixed week (docs + code + volume)	Keep both. Route long context to Sol. Route volume text to Grok.

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Application walkthroughs: where each model is better

1) Customer support email

Better often: GPT-5.6 Sol when the letter has to go out with light editing. Sol used a name slot and two readable paragraphs. Grok kept the same facts and read more like an internal ping. Switch to Grok if your voice is terse, or if thousands of similar notes make the $4/M output gap compound.

2) Long PDF / research pack

Better: GPT-5.6 Sol. 1.05M vs 500K. Start Sol on diligence rooms. Use Grok as a cheap second-pass critic.

3) Everyday Python scripting

Tie on the micro-test. Both caught the empty-list crash. Sol added a print check. Huge doc-plus-code packs favor Sol’s window. Cheap iterative loops favor Grok’s output rate.

4) Screenshot and UI QA

Both cards list image input. We did not run a vision eval, so we will not invent a winner. A/B your actual captures. For video or audio, see Grok 4.6 vs Gemini 3.1 Pro.

5) Output-heavy generation at API scale

Better on cost: Grok 4.6. Chat $0.005 vs $0.007. Repo $0.184 vs $0.200. Cached agent $0.370 vs $0.420.

6) False-premise and trust gates

Both pass. Grok is the stricter short refuse. Sol is the better teacher. For publishable claims, run a second model and a source check.

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Consumer plans vs API (do not mix them up)

SERP pages often blur ChatGPT-style subscriptions with API model IDs. Keep them separate:

• API comparison (this article): Grok 4.6 (xAI API) vs GPT-5.6 Sol (OpenAI API).
• Consumer apps: SuperGrok / X experiences vs ChatGPT plans may expose different tool defaults, rate limits, and bundled models (including cheaper tiers).

If your question is “which $20-class subscription feels better on my phone,” run a week-long lived test in both apps. If your question is “which model should my agent call,” use this API page.

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Speed notes

We did not measure tokens per second for this pair. Writeups in 2026 often disagree by region, batch size, and reasoning settings. For UX, log your own p50 and p95 from the API in the region you actually serve. Time-to-first-token and tokens per second are different feelings. Do not mix them.

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Related comparisons

Nearby pages: Grok 4.6 vs Gemini 3.1 Pro, GPT-5.6 Sol vs Gemini 3.1 Pro, Claude Opus 5 vs Grok 4.6, Claude Opus 5 vs GPT-5.6 Sol, Claude Opus 5 vs GPT-5.5, GPT-5.5 vs Gemini 3.1 Pro.

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Frequently asked questions

Which is better overall, Grok 4.6 or GPT-5.6 Sol?
Neither permanently. Sol won our three-prompt pack (72/75 vs 68/75). Grok wins output price and every workload we estimated. Pick by job.

Which is better for coding?
Tie on the empty-list guard. Both named ZeroDivisionError. Sol’s 1.05M window matters more on huge repos than this snippet.

Which is better for writing?
Lean Sol on this prompt (more client-ready). Grok was complete and slightly more telegram-like. A/B on brand voice.

Which is cheaper?
Input $2/M both (2026-08-24). Output $6 Grok vs $10 Sol. Cache $0.50 vs $0.20. Grok wins our three recipes unless you cache hard and emit little.

Which has the larger context window?
GPT-5.6 Sol (1,050,000) vs Grok 4.6 (500,000).

Do I need both?
If you mix giant packs with volume text, yes. Route long context to Sol and volume to Grok.

Are we comparing apps or API models?
API models Grok 4.6 (xAI API) and GPT-5.6 Sol (OpenAI API). Apps wrap different defaults.

How often should I re-test?
After version bumps. Monthly in production. Re-price when list rates move. Sol is not GPT-5.5. Do not mix their prices.

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

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

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