Grok 4.7 vs GPT-6.1 Sol: Benchmarks, Price & Which to Pick (2026)

Comparison · October 2026

Grok 4.7 (xAI API) and GPT-6.1 Sol (OpenAI API) are two 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	Either; A/B on brand voice	Grok 4.7: All six facts, no name slot, under 120 words, slightly telegram-like. “Thanks so much.” GPT-6.1 Sol: Two tight paragraphs, all facts, no greeting filler, under 120 words.
Developer / agent builder	GPT-6.1 Sol for huge repos; Grok 4.7 for cheap loops	Window 1.05M vs 500K. Micro-test: Named ZeroDivisionError. Guard raises ValueError. Mentions None or 0 as alternatives. / Named ZeroDivisionError. Minimal ValueError guard. Clear empty-list contract.
Researcher / analyst	GPT-6.1 Sol	500K vs 1.05M on the cards we pulled.
Budget / high volume	Grok 4.7	Cheaper on our chat recipe (Grok 4.7 $0.0050 vs GPT-6.1 Sol $0.0070).

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What we are comparing (exact versions)

This page compares two specific API models, not vague brand names and not last quarter’s IDs. Nearby versioned pages: Grok 4.6 vs GPT-5.6 Sol, Grok 4.6 vs GPT-6 Astra, Grok 4.7 vs Claude Opus 5.5, Claude Opus 5.5 vs GPT-6.1 Sol, Claude Sonnet 5.5 vs GPT-6.1 Sol, and GLM 5.3 Prime vs GPT-6.1 Sol.

Field	Grok 4.7	GPT-6.1 Sol
Provider	xAI (listed as SpaceXAI on the API card)	OpenAI
API model	Grok 4.7 (xAI API)	GPT-6.1 Sol (OpenAI API)
Listed card name	SpaceXAI: Grok 4.7	OpenAI: GPT-6.1 Sol
Family / tier	xAI flagship	GPT-6.1 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 older IDs as if they were these cards, treat it as historical. For routing across many models, see AI model routing.

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Spec sheet (API card, 2026-10-12)

Spec	Grok 4.7	GPT-6.1 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)	xAI flagship succeeding Grok 4.6; coding, agentic tasks, knowledge work, long-running software engineering and self-verification	Upgrade to GPT-6 Sol, below Astra in the GPT-6 series; agentic coding, computer use, document-heavy professional work

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 2026-10-12. Verify live before you budget.

Price	Grok 4.7	GPT-6.1 Sol
Input / 1M tokens	$2.00	$2.00
Output / 1M tokens	$6.00	$10.00
Cache read / 1M	$0.50	$0.10

Same input sticker ($2.00). Grok 4.7 is cheaper on output ($6.00 vs $10.00). GPT-6.1 Sol is cheaper on cache reads ($0.10 vs $0.50). If your agent stack actually hits cache, that gap matters.

Scenario	Assumed tokens	Est. Grok 4.7	Est. GPT-6.1 Sol
Chat turn	1k in + 0.5k out	$0.0050	$0.0070
Repo / doc review	80k in + 4k out	$0.184	$0.200
Agent loop	200k in (50% cached) + 20k out	$0.370	$0.410

On the cached agent recipe, Grok 4.7 wins ($0.370 vs $0.410). 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 flagship succeeding Grok 4.6; coding, agentic tasks, knowledge work, long-running software engineering and self-verification. Upgrade to GPT-6 Sol, below Astra in the GPT-6 series; agentic coding, computer use, document-heavy professional work. Those are positioning lines, not benches. Our micro-test: Named ZeroDivisionError. Guard raises ValueError. Mentions None or 0 as alternatives. Named ZeroDivisionError. Minimal ValueError guard. Clear empty-list contract. Window size and cache price matter more on long agent loops than this snippet.

Writing and tone

Grok 4.7 for All six facts, no name slot, under 120 words, slightly telegram-like. “Thanks so much.” GPT-6.1 Sol for Two tight paragraphs, all facts, no greeting filler, under 120 words. If your brand wants send-ready client email, prefer the tighter letter. If you hate filler, prefer the shorter note.

Research, math, reasoning

We did not run a science-QA pack, so we will not fake one. False-premise: Refused first. Silicate rock, no protein, drop the premise, look for ice instead. Short. Refuse, then a four-step bioreactor plan. Protein on the Moon, not cheese mining. For publishable work, add multi-model hallucination checks.

Multimodal and long context

Grok 4.7 lists text, image, file in, text out. GPT-6.1 Sol lists text, image, file in, text out. Context is 500,000 tokens vs 1,050,000 tokens. Giant packs go to the larger window. Audio or video only if the card actually lists it.

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	Named ZeroDivisionError. Guard raises ValueError. Mentions None or 0 as alternatives. Named ZeroDivisionError. Minimal ValueError guard. Clear empty-list contract.
Everyday writing	Split	All six facts, no name slot, under 120 words, slightly telegram-like. “Thanks so much.” Two tight paragraphs, all facts, no greeting filler, under 120 words.
Long docs / multimodal	GPT-6.1 Sol	1.05M vs 500K. Input set: text, image, file vs text, image, file.
Realtime / conversational	Product-dependent	Product-dependent. Confirm tools, voice, and search in the app you actually ship. Not measured here.
Cost at volume	Grok 4.7	Chat Grok 4.7 $0.0050 vs GPT-6.1 Sol $0.0070. Repo $0.184 vs $0.200. Cached agent $0.370 vs $0.410.

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Side-by-side test (i10X pack, 2026-10-12)

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 4.7 (excerpt, sanitized): All six facts, no name slot, under 120 words, slightly telegram-like. “Thanks so much.”

GPT-6.1 Sol (excerpt, sanitized): Two tight paragraphs, all facts, no greeting filler, under 120 words.

Edge: Split. A/B on brand voice. Neither is allowed to drop Q3, Tuesday, Friday, Wednesday, finance, or Acme.

Test 2: Empty-list average bug

Named ZeroDivisionError. Guard raises ValueError. Mentions None or 0 as alternatives. Named ZeroDivisionError. Minimal ValueError guard. Clear empty-list contract. Split.

Test 3: False premise (Moon cheese)

Refused first. Silicate rock, no protein, drop the premise, look for ice instead. Short. Refuse, then a four-step bioreactor plan. Protein on the Moon, not cheese mining. GPT-6.1 Sol.

Prompt type	Grok 4.7	GPT-6.1 Sol	Note
Client email rewrite	23/25	23/25	All six facts, no name slot, under 120 words, slightly telegram-like. “Thanks so much.”
Bug explain + minimal fix	24/25	24/25	Named ZeroDivisionError. Guard raises ValueError. Mentions None or 0 as alternatives.
Logic + false premise	22/25	23/25	Refused first. Silicate rock, no protein, drop the premise, look for ice instead. Short.
Total	69/75	70/75	GPT-6.1 Sol won this three-prompt pack (70/75 vs 69/75). That does not erase the other model’s cost or context edge. Route the next step.

GPT-6.1 Sol won this three-prompt pack (70/75 vs 69/75). That does not erase the other model’s cost or context edge. Route the next step.

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Ecosystem and where you run them

• Grok 4.7: xAI API. Also in xAI / X products; this article uses the API model above.
• GPT-6.1 Sol: OpenAI API. Also in ChatGPT-family apps; this article uses the API model above.
• 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 4.7

• Pros: xAI flagship succeeding Grok 4.6; coding, agentic tasks, knowledge work, long-running software engineering and self-verification. Context 500K. List rates $2.00 / $6.00. Cache $0.50. Input text, image, file.
• Cons: Smaller window than GPT-6.1 Sol. Live writing: All six facts, no name slot, under 120 words, slightly telegram-like. “Thanks so much.”
• Fails when: you treat the card as a bench, skip a false-premise gate, or assume the consumer app matches this API ID.

GPT-6.1 Sol

• Pros: Upgrade to GPT-6 Sol, below Astra in the GPT-6 series; agentic coding, computer use, document-heavy professional work. Context 1.05M. List rates $2.00 / $10.00. Cache $0.10. Input text, image, file.
• Cons: Larger sticker on output than Grok 4.7. Live writing: Two tight paragraphs, all facts, no greeting filler, under 120 words.
• Fails when: you optimize purely for one axis (price, or window, or a single writing sample) and never re-test after a version bump.

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Decision guide: pick one or route both

If you need…	Choose
Output-cheap high volume text	Grok 4.7
Long PDF / giant repo packs	GPT-6.1 Sol
Send-ready client email	A/B both. Voice split in our rewrite.
Cache-heavy agent loops	Re-price. Cache $0.50 vs $0.10. Our 50% cache recipe: $0.370 vs $0.410.
Mixed week (docs + code + volume)	Keep both. Route long context to GPT-6.1 Sol. Route volume text to Grok 4.7.

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Application walkthroughs: where each model is better

1) Customer support email

Better often: Split Both kept the facts. All six facts, no name slot, under 120 words, slightly telegram-like. “Thanks so much.” Two tight paragraphs, all facts, no greeting filler, under 120 words. A/B on brand voice.

2) Long PDF / research pack

Better: GPT-6.1 Sol. 500,000 tokens vs 1,050,000 tokens. Start the larger window on diligence rooms. Use the cheaper model as a second-pass critic.

3) Everyday Python scripting

Tie on the micro-test. Both named ZeroDivisionError and wrote a guard. Named ZeroDivisionError. Guard raises ValueError. Mentions None or 0 as alternatives. Named ZeroDivisionError. Minimal ValueError guard. Clear empty-list contract. Huge doc-plus-code packs favor the larger window. Cheap iterative loops favor the cheaper output rate.

4) Screenshot and UI QA

Cards: Grok 4.7 lists text, image, file. GPT-6.1 Sol lists text, image, file. We did not run a vision eval, so we will not invent a winner. A/B your actual captures.

5) Output-heavy generation at API scale

Better on cost: Grok 4.7. Chat Grok 4.7 $0.0050 vs GPT-6.1 Sol $0.0070. Repo $0.184 vs $0.200. Cached agent $0.370 vs $0.410.

6) False-premise and trust gates

GPT-6.1 Sol. Refused first. Silicate rock, no protein, drop the premise, look for ice instead. Short. Refuse, then a four-step bioreactor plan. Protein on the Moon, not cheese mining. 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 consumer subscriptions with API model IDs. Keep them separate:

• API comparison (this article): Grok 4.7 (xAI API) vs GPT-6.1 Sol (OpenAI API).
• Consumer apps: SuperGrok / X experiences vs ChatGPT-family apps 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 GPT-5.6 Sol, Grok 4.6 vs GPT-6 Astra, Grok 4.7 vs Claude Opus 5.5, Claude Opus 5.5 vs GPT-6.1 Sol, Claude Sonnet 5.5 vs GPT-6.1 Sol, and GLM 5.3 Prime vs GPT-6.1 Sol.

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Frequently asked questions

Which is better overall, Grok 4.7 or GPT-6.1 Sol?
Neither permanently. GPT-6.1 Sol won this three-prompt pack (70/75 vs 69/75). That does not erase the other model’s cost or context edge. Route the next step.

Which is better for coding?
Split. Named ZeroDivisionError. Guard raises ValueError. Mentions None or 0 as alternatives. Named ZeroDivisionError. Minimal ValueError guard. Clear empty-list contract. Window size matters more on huge repos than this snippet.

Which is better for writing?
Split. All six facts, no name slot, under 120 words, slightly telegram-like. “Thanks so much.” Two tight paragraphs, all facts, no greeting filler, under 120 words. A/B on brand voice.

Which is cheaper?
Output $6.00 Grok 4.7 vs $10.00 GPT-6.1 Sol (checked 2026-10-12). Input $2.00 vs $2.00. Cache $0.50 vs $0.10. Workload: chat Grok 4.7 $0.0050 vs GPT-6.1 Sol $0.0070, repo $0.184 vs $0.200, agent $0.370 vs $0.410.

Which has the larger context window?
Grok 4.7 500,000 tokens vs GPT-6.1 Sol 1,050,000 tokens.

Do I need both?
If you mix giant packs with volume text, yes. Route long context to GPT-6.1 Sol and volume to Grok 4.7.

Are we comparing apps or API models?
API models Grok 4.7 (xAI API) and GPT-6.1 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. Do not mix these IDs with last quarter’s cards.

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

What about hallucinations and trust?
Refused first. Silicate rock, no protein, drop the premise, look for ice instead. Short. Refuse, then a four-step bioreactor plan. Protein on the Moon, not cheese mining. Still ground publishable claims. Multi-model hallucination checks.

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