# Grok 4.7 and the GPT-6 Family: What Changed This Fall > Source: > Published: 2026-10-19 12:32:52+00:00 Two AI companies updated their flagship chatbots within eight days of each other this fall, and the result is the messiest version of the Grok vs ChatGPT debate yet. xAI shipped Grok 4.7 on September 21, 2026. OpenAI’s GPT-6 family, including GPT-6 Astra and GPT-6.1 Sol, now powers the ChatGPT experience across its paid tiers. Pull up Artificial Analysis today and you will see a 46-to-53 point gap in favor of OpenAI’s top configuration, yet xAI’s own published benchmarks tell a more complicated story about where each model actually wins. This comparison pulls exact pricing, context window figures, and benchmark scores from xAI’s official release notes, Artificial Analysis’s head-to-head model comparison tool, and third-party benchmark trackers including Lindy and NeuralTrust. It also covers where each model shows up in the real world, from Tesla dashboards to federal government contracts, and closes with a migration path for developers who want to test both APIs without rewriting their entire codebase. The timing matters as much as the numbers. Grok 4.7 landed on September 21, GPT-6.1 Sol followed roughly a week later, and Artificial Analysis has already logged multiple conflicting Intelligence Index snapshots for both models in the weeks since. Anyone searching “grok vs chatgpt” right now is going to run into stale screenshots and half-updated leaderboards faster than they find a clean side-by-side. This piece is built to cut through that by sourcing every figure directly and flagging the handful of numbers that still carry genuine uncertainty. Don't miss new tech stories on Google Add Shattered once in the Google app and our stories show up in your news suggestions. [Add now](https://www.google.com/preferences/source?hl=en&q=https%3A%2F%2Fshattered.io%2F) ## Grok 4.7 and the GPT-6 Family: What Changed This Fall xAI replaced Grok 4.6 with Grok 4.7 on September 21, 2026, and the [official release notes from x.ai](https://x.ai/news/grok-4-7) frame the update around coding and agentic task performance rather than a wholesale architecture change. The company published ten separate benchmark results alongside the launch, a practice xAI has leaned on since Grok 4 to differentiate itself from rivals that disclose fewer third-party scores. OpenAI’s side of the ledger is less tidy. GPT-6 now anchors the standard ChatGPT Plus experience, according to OpenAI’s own plan copy, while GPT-6 Astra sits above it as the higher-effort reasoning model generally associated with the Pro tier. GPT-6.1 Sol, meanwhile, functions primarily as an API-facing model name rather than a consumer-facing ChatGPT toggle. That three-way naming split, Astra for reasoning depth, Sol for API efficiency, and a plain GPT-6 for everyday Plus usage, makes “ChatGPT” a moving target when you try to pin down exactly which model you are testing against Grok. For this comparison, Grok 4.7 lines up against both GPT-6 Astra (OpenAI’s higher-capability configuration) and GPT-6.1 Sol (the closer price match), since neither one alone represents the full ChatGPT picture in October 2026. ## GPT-6 Astra vs GPT-6.1 Sol: Two Different Bets Inside One Family It helps to understand why OpenAI even has two separate names to compare against a single Grok release. GPT-6 Astra is positioned as the higher-effort reasoning model, the one associated with ChatGPT’s Pro tier and the one that shows up with the stronger Terminal-Bench and Intelligence Index scores in this comparison. GPT-6.1 Sol trades some of that reasoning depth for speed and cost, and its pricing reflects that trade directly: $2 per million input tokens and $10 per million output tokens, against Astra’s $10 and $50. That split is OpenAI’s answer to a problem every frontier lab faces. Push too hard on raw benchmark scores and the API bill balloons for anyone running the model at scale. Price too aggressively and the flagship product stops looking like a flagship. Splitting the GPT-6 family into Astra and Sol lets OpenAI compete with Grok 4.7 on cost through Sol while still fielding a higher-capability option in Astra for customers who will pay for the extra points on Terminal-Bench. The downside, at least from a buyer’s perspective, is that “ChatGPT” now describes at least three different cost and capability tiers rather than one clear product, which is exactly the kind of fragmentation that makes a direct Grok vs ChatGPT comparison harder to pin down than it looks on paper. ## Grok vs ChatGPT: Full Specifications Table The table below lines up the hard numbers from xAI’s official documentation against the figures Artificial Analysis and Lindy have logged for OpenAI’s GPT-6 family. Where a spec has not been publicly disclosed, that is noted rather than estimated. | Spec | Grok 4.7 | GPT-6 Astra | GPT-6.1 Sol | |---|---|---|---| | Developer | xAI | OpenAI | OpenAI | | Release window | September 21, 2026 | Rolled into Pro-tier ChatGPT in 2026 | Late September 2026 (API) | | Context window | 500,000 tokens | Not publicly disclosed | Not publicly disclosed | | Standard input price | $2 per million tokens | $10 per million tokens | $2 per million tokens | | Standard output price | $6 per million tokens | $50 per million tokens | $10 per million tokens | | Cached input price | $0.50 per million tokens | Not publicly disclosed | Not publicly disclosed | | Long-prompt pricing (200K+ tokens) | $4 input / $1 cached / $12 output per million | Not applicable (no 500K+ tier published) | Not applicable | | Artificial Analysis Intelligence Index | 46 | 52-53 (Max/Xhigh configs) | 50-52 (High/Max configs) | | Terminal-Bench 4.0 | 37.6% (xAI figure) | 57.9% (Lindy figure) | Not published | | Input modalities | Text, image | Not fully itemized in public specs | Not fully itemized in public specs | | Output modality | Text only | Text | Text | | Reasoning effort tiers | Low, medium, high, xhigh | Referenced as Max/Xhigh configurations | Referenced as Max/High configurations | | Fast/discount variant | Grok 4.7 Fast, 2x standard price | None published | None published | Two things jump out immediately. First, Grok’s long-context pricing tier only kicks in above 200,000 tokens, while its base 500,000-token window is itself smaller than the 1-million-token windows that Anthropic and Google have been shipping this year. Second, the price gap between Grok 4.7 and GPT-6 Astra on output tokens is not small. At $50 per million output tokens, GPT-6 Astra costs more than eight times what Grok 4.7 charges for the same volume of generated text. ## Benchmark Results: Artificial Analysis, Terminal-Bench, and the Rest Benchmark comparisons for this pairing come from three independent sources, which matters because xAI, Artificial Analysis, and third-party trackers do not always agree on configuration details. [Artificial Analysis’s own head-to-head comparison tool](https://artificialanalysis.ai/models/comparisons/gpt-6-1-sol-high-vs-gpt-6-astra-xhigh) lists GPT-6.1 Sol in its High configuration against GPT-6 Astra in Xhigh, putting Sol at 50 and Astra at 52 on the Intelligence Index. A separate Artificial Analysis snapshot cited by [NeuralTrust’s Grok vs ChatGPT benchmark breakdown](https://neuraltrust.ai/blog/grok-vs-chatgpt-benchmark) puts Astra at 53 against Grok 4.7’s 46, a seven-point gap that holds up across multiple configuration snapshots even as the exact numbers shift by a point here and there. On Terminal-Bench 4.0, a benchmark both companies report on, the gap widens considerably. xAI’s own release notes put Grok 4.7 at 37.6%, an improvement over Grok 4.6’s 20.3% but still well short of the 57.9% that [Lindy’s pricing and benchmark comparison](https://www.lindy.ai/blog/grok-4-7) attributes to GPT-6 Astra. That is a 20-point spread on a benchmark designed to measure how well a model completes multi-step command-line tasks, which matters a lot if your use case leans toward coding agents or DevOps automation. Grok 4.7 does better on benchmarks xAI chose to spotlight in its own announcement. The model scored 71.0% on DeepSWE v1.1, 64.0% on EEBench, and 96.7% on HackerBench v0.3, which measures safe refusal behavior in adversarial prompts. It also posted a GDPval Elo score of 1,695 and an AA Briefcase v1.1 score of 1,657, both metrics aimed at office and knowledge-work tasks rather than pure coding. Where Grok 4.7 clearly struggles is the Harvey Legal Agent Benchmark, where it scored just 19.6%, a result xAI published itself rather than burying. No source in this research turned up a public SWE-bench Verified score for either Grok 4.7 or GPT-6.1 Sol. Lindy’s comparison explicitly flags that GPT-6.1 Sol’s Terminal-Bench result “was not published,” and xAI’s own benchmark table skips SWE-bench entirely in favor of its DeepSWE and CursorBench substitutes. Treat any SWE-bench Verified number you see attributed to either model with skepticism until a primary source confirms it. ### Grok 4.6’s Baseline, For Context Grok 4.7’s 37.6% Terminal-Bench 4.0 score only means something once you know what it replaced. xAI’s own comparison data puts Grok 4.6 at 20.3% on the same benchmark, which makes the jump to 4.7 a genuine near-doubling rather than an incremental bump. That pace of improvement is worth keeping in mind before writing Grok off against GPT-6 Astra’s 57.9%. A model that nearly doubled one benchmark score in a single release cycle is not necessarily going to sit at a 20-point deficit for long, even if it trails today. Whether xAI closes that specific gap with Grok 5 or whatever comes next is a different question, but the trend line argues against treating October 2026’s scores as a settled verdict. ### Why the Benchmark Gap Does Not Tell the Whole Story Average task cost is where Grok claws back ground. NeuralTrust’s comparison estimates Grok 4.7 costs roughly $3.74 per completed task against $3.26 for GPT-6 Astra, numbers close enough that the benchmark gap starts to look more expensive to close than it looks on a leaderboard. If GPT-6 Astra needs fewer retries and shorter follow-up prompts to hit the same outcome, its higher per-token price can still land close to Grok’s bill by the time a task actually finishes. That $0.48 gap in estimated task cost is a reminder that per-token pricing and per-task cost are not the same measurement, and vendors rarely advertise the second one. A model that charges less per million tokens but needs three extra follow-up exchanges to land a correct answer can easily cost more per completed task than a pricier model that gets it right on the first try. Anyone budgeting a production deployment around the headline $2/$6 versus $10/$50 numbers alone is working from an incomplete picture until they measure actual task completion cost on their own prompts. ## Pricing Breakdown: API Costs and Consumer Plans API pricing is the cleanest comparison point because both companies publish exact per-token rates. Consumer subscription pricing is messier, particularly on the xAI side, where reporting on 2026 tier names and prices has been inconsistent across secondary sources. The table below separates confirmed figures from reported ones. | Tier | Grok / xAI | ChatGPT / OpenAI | |---|---|---| | Free tier | $0, limited usage | $0, limited usage | | Entry paid consumer tier | Reportedly $8/month | Historically $20/month (Plus) | | Mid consumer tier | Reportedly $30/month (Premium/SuperGrok) | Reported restructuring around $100-$200 tiers as of September 2026 | | Top consumer tier | Reportedly $100-$200/month (Super/Ultra) | Pro tier, historically $200/month; one report says the $200 option closed to new signups September 10, 2026 | | Team/Business seat | Not confirmed in public pricing | $25/user/month monthly, $20/user/month annual | | Enterprise | Custom; GSA deal at $0.42/agency over 18 months | Custom; ChatGPT Gov via GSA OneGov at $1 through September 2026 | | API standard input | $2 per million tokens | $10/M (Astra) or $2/M (Sol) | | API standard output | $6 per million tokens | $50/M (Astra) or $10/M (Sol) | Where OpenAI pricing is locked down with certainty, it is at the business end. The Business plan runs $25 per user per month billed monthly, or $20 per user per month billed annually, and Enterprise pricing stays custom-quoted. On the consumer side, the picture is genuinely murky this fall. One report pegs a shift away from a flat $200 Pro tier and toward a two-rung $100/$200 structure, with the $200 option reportedly closed to new signups as of September 10, 2026. Until OpenAI publishes a clean pricing page update, that figure should be read as a signal of change rather than a confirmed current price. xAI’s consumer tiers carry the same caveat in reverse. Secondary sources describe an “X Subscription” ladder running from $8 up through a $200 Ultra tier, sometimes with a $300 SuperGrok Heavy option layered on top, but no single xAI pricing page in this research confirmed all five numbers at once. The API pricing, by contrast, is unambiguous and documented directly on x.ai: $2 per million input tokens and $6 per million output tokens for standard Grok 4.7 requests, doubling for the Fast variant. ### Why You Should Budget With a Buffer This Quarter Both companies have shown they will move prices and tier structures with little warning this year. OpenAI’s reported shift away from a flat $200 Pro plan happened mid-quarter, not at a predictable annual pricing review, and xAI’s own consumer tiers have been renamed and reshuffled enough times that outside trackers cannot agree on a final list. If you are building a budget around either product for the next two quarters, add a 15 to 20 percent buffer on top of whatever price you lock in today. That is not a hedge against bad math, it is a hedge against the fact that both vendors have changed consumer pricing structures at least once already in the second half of 2026, and nothing in the public record suggests that pace is slowing down. ## Context Windows and Long-Prompt Handling Grok 4.7’s 500,000-token context window is the one context figure either company has actually published for these specific models. Neither GPT-6 Astra nor GPT-6.1 Sol has a disclosed context window in the sources checked for this comparison, which is notable given how aggressively OpenAI has marketed context length in past releases. That silence could mean the figure has not changed from earlier GPT-6-era models, or it could mean OpenAI is holding the number back for a later announcement. Either way, it means buyers comparing long-document use cases cannot make an apples-to-apples claim about GPT-6 Astra’s context ceiling the way they can for Grok 4.7. What is clear is how Grok prices around its own context limit. Prompts under 200,000 tokens run at the standard $2 input rate, while anything at or above that threshold jumps to $4 per million input tokens, $1 per million for cached input, and $12 per million output tokens. That is effectively a built-in tax for using the back half of Grok’s context window, a structure neither xAI’s competitors nor its own earlier Grok 4.6 pricing applied in quite the same tiered way. ## Multimodal Capabilities and Reasoning Effort Settings Grok 4.7 accepts text and image input and returns text-only output, according to xAI’s documentation. It does not currently advertise video understanding, native voice interaction, or image generation as part of the core model, though xAI has shipped separate products for some of those capabilities in the past. The model also exposes four reasoning effort settings, low, medium, high, and xhigh, letting developers trade latency for depth on a per-request basis rather than committing to one fixed reasoning budget. OpenAI’s GPT-6 Astra and GPT-6.1 Sol reference similar configuration tiers, Max and Xhigh for Astra, Max and High for Sol, in the benchmark tables Artificial Analysis publishes, but neither xAI nor OpenAI’s public documentation fully itemizes which input or output modalities apply to each configuration. That gap is worth flagging precisely because OpenAI has historically been more forthcoming about multimodal specs for ChatGPT than it has been this cycle for the GPT-6 API-facing models. ## Real-World Adoption: Where Grok and ChatGPT Actually Run Benchmark scores matter less than where a model actually gets deployed, and both companies have a growing list of integrations outside their own chat apps. - **Grok inside X.** xAI’s chatbot has been natively built into the X platform since 2023, giving it direct access to real-time trending topics and post data that neither ChatGPT nor most other chatbots can match without a separate search integration. - **Grok inside Tesla vehicles.** Tesla’s own support documentation confirms Grok is available on compatible vehicles running software version 2025.26 or later, provided the car has an AMD processor and either Premium Connectivity or Wi-Fi. Drivers can launch it from the center touchscreen or the steering-wheel microphone. - **xAI’s Telegram integration.** xAI and Telegram reportedly agreed in May 2025 to bring Grok into the messaging app, with xAI said to be paying roughly $300 million in cash and equity and Telegram taking a cut of resulting Grok subscription revenue. These terms come from secondary reporting rather than a joint company statement, so treat the dollar figure as reported rather than confirmed. - **xAI’s GSA OneGov deal.** The US General Services Administration announced its OneGov agreement with xAI on September 25, 2025, making Grok 4 and Grok 4 Fast available to federal agencies for $0.42 per agency over an 18-month term running through March 2027. - **ChatGPT Enterprise’s customer base.** OpenAI has reported more than one million business customers for ChatGPT Enterprise, with the company describing AI as increasingly embedded into internal workflows and products across that customer base. - **ChatGPT Gov through GSA OneGov.** OpenAI’s own government-facing page describes eligible federal agencies getting access to ChatGPT Enterprise through the same GSA OneGov channel for $1 through September 2026, with ChatGPT Gov also deployable through Azure OpenAI. - **ChatGPT for Microsoft Intune.** OpenAI shipped a dedicated ChatGPT app for Microsoft Intune to the Apple App Store, aimed at ChatGPT Enterprise organizations that manage devices through Intune and Microsoft Entra. Both companies have also landed federal government contracts through the same GSA OneGov program, just with very different headline prices, $0.42 per agency for Grok versus $1 for ChatGPT Gov. Those numbers are not directly comparable since contract scope and agency count details were not fully itemized in the available sources, but the fact that both landed government-wide deals within roughly a year of each other says something about how aggressively both companies are chasing public-sector adoption. ## What the CEOs Are Saying About Each Other’s Models The Grok vs ChatGPT comparison has not stayed confined to spec sheets. Elon Musk and Sam Altman have traded public jabs about each other’s products for months, and some of that back-and-forth has spilled into legal filings. Musk posted a blunt warning on X, writing, “Don’t let your loved ones use ChatGPT,” as [The Cool Down reported](https://www.thecooldown.com/green-business/elon-musk-sam-altman-openai-chatgpt-grok-feud/) in its coverage of the ongoing standoff between the two executives. The dispute escalated further in a legal filing. According to a deposition cited by Beeble, Musk claimed, “Nobody has committed suicide because of Grok, but apparently they have because of ChatGPT.” That statement was made as part of Musk’s broader legal battle with OpenAI and should be read in that context, as a contested claim inside an active dispute rather than an independently verified finding about either product’s safety record. Altman has pushed back in kind. Responding to Musk’s criticism of ChatGPT’s handling of vulnerable users, Altman wrote, “Sometimes you complain about ChatGPT being too restrictive, and then in cases like this, you claim it’s too relaxed,” according to Reality Tea’s reporting on the exchange. Altman added a pointed jab of his own: “I won’t even start on some of the Grok decisions.” Neither executive’s claims settle the safety question on their own, and neither company has published an independent, third-party safety audit that directly compares the two models head to head. For buyers, the practical takeaway is to treat both companies’ public statements about each other’s safety record as marketing in a high-stakes rivalry, not as neutral evidence. ## Safety, Content Moderation, and the Ongoing Rivalry Beyond the public feud, xAI’s own benchmark disclosure gives a partial window into how Grok 4.7 handles adversarial prompts. The model scored 96.7% on HackerBench v0.3, a benchmark measuring safe refusal behavior, a number xAI chose to publish alongside its capability scores rather than keep private. That is a meaningfully transparent move compared to OpenAI’s current practice, which has not published an equivalent refusal-rate figure for GPT-6 Astra or GPT-6.1 Sol in the sources reviewed here. That transparency gap cuts both ways, though. xAI has faced its own share of content moderation controversies with earlier Grok versions, and a single refusal-rate benchmark does not capture the full range of edge cases a production deployment will encounter. Buyers evaluating either model for a regulated industry, healthcare, legal, or financial services, should run their own adversarial testing rather than relying on either company’s self-reported safety numbers alone. ## Migrating From the ChatGPT API to Grok’s API xAI built its API to be broadly compatible with the OpenAI client libraries that most developers already have installed, which makes testing Grok 4.7 against an existing ChatGPT integration a relatively low-friction exercise. Here is the general pattern for pointing an existing OpenAI SDK setup at Grok instead. ``` python from openai import OpenAI # Existing ChatGPT setup client = OpenAI( api_key="YOUR_OPENAI_KEY", ) response = client.chat.completions.create( model="gpt-6.1-sol", messages=[{"role": "user", "content": "Summarize this changelog."}] ) # Pointed at Grok 4.7 instead grok_client = OpenAI( api_key="YOUR_XAI_KEY", base_url="https://api.x.ai/v1", ) response = grok_client.chat.completions.create( model="grok-4.7", messages=[{"role": "user", "content": "Summarize this changelog."}] ) ``` Five steps cover most migrations in practice. First, request an xAI API key separately since it is not interchangeable with an OpenAI key. Second, swap the base_url parameter to point at api.x.ai rather than the default OpenAI endpoint. Third, update the model string to grok-4.7 or grok-4.7-fast depending on which latency tier you need. Fourth, re-run your existing prompt test suite against both endpoints side by side, since reasoning-effort settings and refusal behavior differ enough between the two models that identical prompts can produce meaningfully different outputs. Fifth, recalculate your expected monthly spend using Grok’s tiered long-context pricing if any of your prompts regularly cross the 200,000-token threshold, since that tier carries a different rate than the headline $2/$6 pricing. Teams running cost-sensitive, high-volume workloads tend to see the clearest win from this migration, given Grok’s lower standard output price. Teams relying on advanced reasoning depth or Terminal-Bench-style coding agent tasks should hold off and benchmark carefully first, since GPT-6 Astra’s published scores suggest a real capability gap on exactly those tasks. ## Use Cases: When to Pick Grok and When to Pick ChatGPT Neither model wins across the board, so the right pick depends heavily on what you are actually building. - **Real-time social and trending-topic analysis:** Grok’s native integration with X gives it a structural edge for monitoring live conversation and breaking news that a general-purpose chatbot without that data pipe cannot easily replicate. - **Enterprise document workflows tied to Microsoft 365:** ChatGPT’s Intune and Entra integration, plus its Business and Enterprise tier infrastructure, make it the more natural fit for organizations already standardized on Microsoft’s device management stack. - **Cost-sensitive, high-volume API automation:** Grok 4.7’s $2/$6 standard pricing undercuts GPT-6 Astra by a wide margin and roughly matches GPT-6.1 Sol on input cost while beating it on output cost, making it worth a serious look for high-token-volume pipelines. - **In-vehicle voice assistance:** Tesla owners with compatible hardware and software already have Grok built into the dashboard, which is a convenience ChatGPT does not currently offer inside the vehicle itself. - **Complex agentic coding tasks:** GPT-6 Astra’s 57.9% Terminal-Bench 4.0 score against Grok’s 37.6% suggests OpenAI’s higher-effort model handles multi-step command-line and coding agent tasks meaningfully better, at a meaningfully higher price. - **Regulated government workloads:** Both companies have GSA OneGov agreements in place, so the deciding factor here is likely to come down to specific agency security requirements and existing vendor relationships rather than a universal winner. - **Legal document review and agentic legal tasks:** Grok’s own published 19.6% score on the Harvey Legal Agent Benchmark is a weak result that xAI did not hide, and it is a strong signal to test any legal-adjacent workload carefully before committing to either vendor. ## Grok 4.7: Pros and Cons Grok 4.7’s biggest selling point is price. At $2 per million input tokens and $6 per million output tokens, it undercuts GPT-6 Astra by a wide margin, and its cached-input discount to $0.50 per million tokens rewards workloads that repeat similar context across requests. xAI’s native X integration and Tesla vehicle deployment also give it reach into two large existing user bases that ChatGPT cannot directly tap. The company’s willingness to publish ten separate benchmark scores, including an unflattering 19.6% legal-agent result, is a transparency practice worth crediting even when the numbers are not flattering. On the downside, Grok 4.7 trails GPT-6 Astra by roughly seven points on the Artificial Analysis Intelligence Index and by a full 20 points on Terminal-Bench 4.0, a meaningful gap for teams building coding agents. Its 500,000-token context window also lags the 1-million-token windows some rivals now ship as standard. Consumer subscription pricing for Grok remains inconsistently reported across secondary sources, making it harder for everyday users to know exactly what they will pay compared to OpenAI’s more clearly published Business and Enterprise rates. ## ChatGPT and the GPT-6 Family: Pros and Cons GPT-6 Astra’s benchmark lead is the clearest argument for choosing OpenAI here. A roughly seven-point edge on the Artificial Analysis Intelligence Index and a 20-point lead on Terminal-Bench 4.0 both point toward stronger raw reasoning and coding-agent performance. OpenAI’s enterprise infrastructure is also more mature on paper, with a confirmed Business tier at $25 per user per month, a GSA OneGov government deal, and direct integration into Microsoft’s device management tools through Intune and Entra. The more than one million business customers OpenAI has reported for ChatGPT Enterprise suggest the ecosystem of integrations and support around the product runs deeper than Grok’s. The clearest drawback is price at the high end. GPT-6 Astra’s $50 per million output token rate is more than eight times Grok’s $6 rate, a gap that adds up fast for any workload generating long-form output at scale. GPT-6.1 Sol closes some of that gap on the API side, but its published benchmark scores trail Astra’s, and no Terminal-Bench 4.0 figure for Sol has been published at all. Consumer pricing has also been in visible flux this fall, with reports of the $200 Pro tier closing to new signups, which makes it harder to budget confidently around ChatGPT’s top consumer tier right now compared to its more stable Business and Enterprise pricing. ## The Verdict: Which Should You Use in October 2026 There is no single winner in the Grok vs ChatGPT comparison this October, and the data makes a clean case for picking based on budget and workload rather than brand loyalty. If raw benchmark performance on coding and reasoning tasks is the priority and the budget can absorb GPT-6 Astra’s premium pricing, OpenAI’s top-tier model has the numbers to back up the higher bill, with a 20-point Terminal-Bench 4.0 lead that is hard to argue with. If cost efficiency, X-platform integration, or in-vehicle deployment through Tesla matter more than squeezing out the last few points on a reasoning benchmark, Grok 4.7’s $2/$6 pricing and transparent benchmark disclosure make it the more practical daily driver for a lot of teams. GPT-6.1 Sol occupies a useful middle ground worth testing before committing either direction. Its input pricing matches Grok 4.7 exactly at $2 per million tokens, and its output price sits closer to Grok’s than Astra’s premium rate does, even though its benchmark scores have not been as thoroughly published as either rival’s. Given how much both Grok and ChatGPT pricing and tier structures have shifted in just the past month, the safest approach for any team evaluating this decision is to run both APIs against your own actual workload for two weeks before locking in a vendor, rather than trusting any single benchmark snapshot to settle the question. ## Frequently Asked Questions **Is Grok 4.7 better than ChatGPT in 2026?** It depends on which ChatGPT model you mean. GPT-6 Astra outscores Grok 4.7 on the Artificial Analysis Intelligence Index, 52-53 versus 46, and on Terminal-Bench 4.0, 57.9% versus 37.6%. GPT-6.1 Sol is closer in price to Grok but has fewer published benchmark scores to compare directly. **How much does Grok 4.7 cost compared to ChatGPT?** Grok 4.7’s API pricing is $2 per million input tokens and $6 per million output tokens. GPT-6.1 Sol matches Grok’s input price at $2 per million tokens but charges $10 per million for output. GPT-6 Astra costs significantly more at $10 per million input and $50 per million output tokens. **What is the context window for Grok 4.7 versus GPT-6 Astra?** Grok 4.7 has a published 500,000-token context window. Neither GPT-6 Astra nor GPT-6.1 Sol has a publicly disclosed context window figure in official OpenAI documentation as of this comparison. **Can I use Grok 4.7 with my existing OpenAI API code?** Largely yes. xAI’s API is designed to work with the standard OpenAI Python client library. Developers typically only need to change the base_url to api.x.ai and update the model name to grok-4.7, then re-test prompts since output behavior differs between the two models. **Does Grok work inside Tesla vehicles?** Yes. Tesla’s support documentation confirms Grok is available in compatible vehicles running software version 2025.26 or later, provided the car has an AMD processor and either Premium Connectivity or Wi-Fi access. **Which model scores higher on Artificial Analysis benchmarks?** GPT-6 Astra scores higher, landing at 52-53 on the Intelligence Index across different configuration snapshots, compared to Grok 4.7’s 46. GPT-6.1 Sol falls in between at roughly 50-52 depending on configuration. **Does the US government use Grok or ChatGPT?** Both. The GSA’s OneGov program covers a Grok 4 and Grok 4 Fast deal for federal agencies at $0.42 per agency over 18 months, announced September 25, 2025. A separate OneGov arrangement gives eligible federal agencies access to ChatGPT Enterprise for $1 through September 2026. **What is the Musk-Altman dispute about regarding AI safety?** Elon Musk and Sam Altman have publicly criticized each other’s chatbots over safety and content moderation, with the disagreement surfacing in both social media posts and legal filings tied to Musk’s broader litigation against OpenAI. Neither company has published an independent third-party audit directly comparing the two models’ safety records, so the public statements from both executives should be read as part of an active business rivalry rather than settled fact.