{"id":1012,"date":"2026-10-14T07:28:27","date_gmt":"2026-10-14T07:28:27","guid":{"rendered":"https:\/\/i10x.ai\/blog\/?p=1012"},"modified":"2026-10-14T07:28:49","modified_gmt":"2026-10-14T07:28:49","slug":"grok-4-7-vs-gpt-6-1-sol","status":"publish","type":"post","link":"https:\/\/i10x.ai\/blog\/grok-4-7-vs-gpt-6-1-sol","title":{"rendered":"Grok 4.7 vs GPT-6.1 Sol: Benchmarks, Price & Which to Pick (2026)"},"content":{"rendered":"\n\n\n
\n\n

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

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

\nQuick verdict<\/strong>\n

Pick Grok 4.7 if:<\/strong> you want cheaper output ($6.00 vs $10.00 per 1M).<\/p>\n

Pick GPT-6.1 Sol if:<\/strong> you want the larger window (1.05M vs 500K), cheaper cache reads ($0.10 vs $0.50), and stricter false-premise handling.<\/p>\n

Best default for many teams:<\/strong> route by task and keep both available. See the decision matrix below.<\/p>\n

Data checked: 2026-10-12. Prices and model cards change. Verify live API and vendor pages.<\/em><\/p>\n<\/div>\n\n

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

500K<\/strong><\/p><\/td>\n

Grok 4.7 context (API)<\/p><\/td>\n<\/tr>\n

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

GPT-6.1 Sol context (API)<\/p><\/td>\n<\/tr>\n

$2.00 \/ $6.00<\/strong><\/p><\/td>\n

Grok 4.7 input\/output per 1M tokens (API pricing, 2026-10-12)<\/p><\/td>\n<\/tr>\n

$2.00 \/ $10.00<\/strong><\/p><\/td>\n

GPT-6.1 Sol input\/output per 1M tokens (API pricing, 2026-10-12)<\/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, output cost efficiency, writing tightness, coding micro-test, cache-read price). 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

Either; A\/B on brand voice<\/p><\/td>\n

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

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

GPT-6.1 Sol for huge repos; Grok 4.7 for cheap loops<\/p><\/td>\n

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

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

GPT-6.1 Sol<\/p><\/td>\n

500K vs 1.05M on the cards we pulled.<\/p><\/td>\n<\/tr>\n

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

Grok 4.7<\/p><\/td>\n

Cheaper on our chat recipe (Grok 4.7 $0.0050 vs GPT-6.1 Sol $0.0070).<\/p><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n

\n\n

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

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

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

Grok 4.7<\/p><\/th>\n

GPT-6.1 Sol<\/p><\/th>\n<\/tr>\n

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

xAI (listed as SpaceXAI on the API card)<\/p><\/td>\n

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

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

Grok 4.7 (xAI API)<\/code><\/p><\/td>\n

GPT-6.1 Sol (OpenAI API)<\/code><\/p><\/td>\n<\/tr>\n

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

SpaceXAI: Grok 4.7<\/p><\/td>\n

OpenAI: GPT-6.1 Sol<\/p><\/td>\n<\/tr>\n

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

xAI flagship<\/p><\/td>\n

GPT-6.1 series flagship<\/p><\/td>\n<\/tr>\n

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

Also in xAI \/ X products; this article uses the API model above<\/p><\/td>\n

Also in ChatGPT-family apps; this article uses the API model above<\/p><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

If a page still compares older IDs as if they were these cards, treat it as historical. For routing across many models, see\nAI model routing<\/a>.<\/p>\n\n

\n\n

Spec sheet (API card, 2026-10-12)<\/h2>\n\n\n\n\n\n\n\n\n

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

Grok 4.7<\/p><\/th>\n

GPT-6.1 Sol<\/p><\/th>\n<\/tr>\n

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

500,000 tokens<\/p><\/td>\n

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

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

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

text, image, file<\/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

xAI flagship succeeding Grok 4.6; coding, agentic tasks, knowledge work, long-running software engineering and self-verification<\/p><\/td>\n

Upgrade to GPT-6 Sol, below Astra in the GPT-6 series; agentic coding, computer use, document-heavy professional work<\/p><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

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.<\/p>\n\n

\n\n

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

List prices are easy to game. Workload cost is what you feel. Numbers below use published per-million rates as of 2026-10-12<\/strong>. Verify live<\/strong> before you budget.<\/p>\n\n\n\n\n\n\n

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

Grok 4.7<\/p><\/th>\n

GPT-6.1 Sol<\/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

$6.00<\/p><\/td>\n

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

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

$0.50<\/p><\/td>\n

$0.10<\/p><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

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

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

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

Est. Grok 4.7<\/p><\/th>\n

Est. GPT-6.1 Sol<\/p><\/th>\n<\/tr>\n

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

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

$0.0050<\/p><\/td>\n

$0.0070<\/p><\/td>\n<\/tr>\n

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

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

$0.184<\/p><\/td>\n

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

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

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

$0.370<\/p><\/td>\n

$0.410<\/p><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\n\"Bar\n
Figure 2.<\/strong> Estimated USD per run using published API list rates (2026-10-12). 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

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\nAI subscription stack cost<\/a>.<\/p>\n\n

\n\n

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

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:\nside-by-side AI comparison<\/a>.<\/p>\n\n

Coding and agents<\/h3>\n

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.<\/p>\n\n

Writing and tone<\/h3>\n

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.<\/p>\n\n

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

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

Multimodal and long context<\/h3>\n

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.<\/p>\n\n

Speed<\/h3>\n

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

Named ZeroDivisionError. Guard raises ValueError. Mentions None or 0 as alternatives. Named ZeroDivisionError. Minimal ValueError guard. Clear empty-list contract.<\/p><\/td>\n<\/tr>\n

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

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

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

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

GPT-6.1 Sol<\/p><\/td>\n

1.05M vs 500K. Input set: text, image, file vs text, image, file.<\/p><\/td>\n<\/tr>\n

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

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

Product-dependent. Confirm tools, voice, and search in the app you actually ship. Not measured here.<\/p><\/td>\n<\/tr>\n

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

Grok 4.7<\/p><\/td>\n

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

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

Leaderboards mix harnesses, tool settings, and effort modes. When we do not have a primary table for a pair, we do not invent one. Re-test on your workload.<\/p>\n<\/div>\n\n

\n\n

Side-by-side test (i10X pack, 2026-10-12)<\/h2>\n

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.<\/p>\n\n

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

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

Grok 4.7 (excerpt, sanitized):<\/strong> All six facts, no name slot, under 120 words, slightly telegram-like. “Thanks so much.”<\/p>\n

GPT-6.1 Sol (excerpt, sanitized):<\/strong> Two tight paragraphs, all facts, no greeting filler, under 120 words.<\/p>\n

Edge:<\/strong> Split. A\/B on brand voice. Neither is allowed to drop Q3, Tuesday, Friday, Wednesday, finance, or Acme.<\/p>\n\n

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

Named ZeroDivisionError. Guard raises ValueError. Mentions None or 0 as alternatives. Named ZeroDivisionError. Minimal ValueError guard. Clear empty-list contract. Split.<\/strong><\/p>\n\n

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

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

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

Grok 4.7<\/p><\/th>\n

GPT-6.1 Sol<\/p><\/th>\n

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

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

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

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

All six facts, no name slot, under 120 words, slightly telegram-like. “Thanks so much.”<\/p><\/td>\n<\/tr>\n

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

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

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

Named ZeroDivisionError. Guard raises ValueError. Mentions None or 0 as alternatives.<\/p><\/td>\n<\/tr>\n

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

22\/25<\/p><\/td>\n

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

Refused first. Silicate rock, no protein, drop the premise, look for ice instead. Short.<\/p><\/td>\n<\/tr>\n

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

69\/75<\/strong><\/p><\/td>\n

70\/75<\/strong><\/p><\/td>\n

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

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.<\/p>\n\n

\n\n

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