SpaceXAI claims its released Grok 4.7 improves long-running coding and knowledge work at unchanged $2-per-million input and $6-per-million output token pricing, potentially providing frontier-comparable agent performance at substantially lower cost than competing models.

state: watchingheat: highuncertainty: highknownscott: mediumfrontier-models model-pricing agent-evaluationSpaceXAI

Surfaced 2026-09-21T20:59:41Z — Announces Grok 4.7 availability through Cursor, Grok Build, and the API; claims improved multi-hour task performance and frontier price-perf — The purported independent analysis adds no usable benchmark results: its only supplied excerpt quotes implausible zero-dollar pricing, so it cannot corroborate the price-performance thesis. Attention nevertheless merits high heat given strong HN and Reddit spread and an additional analysis thread; the retrieved launch page also contradicts the cached grounding's claim that release and pricing remain undocumented.

What is this?

Grok is SpaceXAI/xAI’s model family for coding, agentic tasks, and knowledge work; the supplied official snippets document Grok 4.5’s launch and describe Grok 4.6 as focused on long-running agents. They do not establish the case’s claimed Grok 4.7 release: third-party snippets describe 4.7 as forthcoming or unreleased, with unpublished pricing and conflicting specifications. The official Grok 4.5 announcement lists $2 per million input tokens and $6 per million output tokens and claims superior token efficiency; reporting on Grok 4.6 gives the same starting rates but says they double for prompts reaching 200,000 tokens. These snippets therefore support an existing agent-model price/performance pitch, not verified Grok 4.7 availability, unchanged pricing, or frontier-comparable multi-hour performance.

Why it matters to Scott

The supported price/performance pitch adds no established position beyond Scott’s AI Unit Economics and Model-Plus-Harness Benchmark Unit: compare cost per successful task under a disclosed harness, not token rates alone; no supplied radar page already tracks this exact release. This warrants verification because Ask terminal agent already uses a `grok → smart → cheap` alternate routing chain, but the grounding does not establish Grok 4.7 availability, pricing or performance, so it supplies neither a justified model switch nor credible convergence with his long-running-agent architecture.

ip:concept.ai-unit-economicsip:concept.model-plus-harness-benchmark-unitdev:project.askradar:hidden-reasoning-real-task-costsradar:concept.long-running-agentsradar:concept.coding-agent-evaluation

queries asked of Scott's wikis

coding agent harness model selection and switching
long-running autonomous agents reliability evaluation
cost per completed task versus token pricing
context compaction caching long-context inference costs
knowledge-work agents repository-specific benchmarks

Measured heat

now 0 pts/hpeak 13 pts/hcomments 0/hpeers p14momentum: steady3 platformsage 506h

points/hour across evidence · reading as of 2026-10-12 02:59:37.977291+11:00 · deterministic, not a model opinion

How the heat travelled

09-20 14:00	⭐ origin echo-reconstructed	Announces Grok 4.7 availability through Cursor, Grok Build, and the API; claims improved multi-hour task performance and frontier price-perf SpaceXAI on blog (echo) · attributed from reddit.post.1wmgudm, hn.story.49788838	—
09-21 15:50	first on hacker news · published · +25.8h	Grok 4.7 meetpateltech	—
09-21 15:58	first on r/singularity · published · +26.0h	Introducing Grok 4.7 AMBNNJ	—
09-26 19:51	first on r/ClaudeAI · published · +149.8h	Elon Musk admits Grok isn’t as good as Anthropic’s Claude ross2000	—
09-21 15:50	amplified on hacker news 👑	hn.story.49788838 meetpateltech	peak 609 · 491 comments · 58% of case engagement
09-21 15:58	amplified on r/singularity	reddit.post.1wmgudm AMBNNJ	peak 389 · 113 comments · 15% of case engagement
09-21 16:36	amplified on hacker news	hn.story.49789558 theanonymousone	peak 13 · 1 comments · 1% of case engagement
09-26 19:51	amplified on r/ClaudeAI	reddit.post.1wqzu96 ross2000	peak 769 · 124 comments · 26% of case engagement
09-21 16:20	our radar first saw it · +26.3h	discovery anchor: reddit.post.1wmgudm	—
09-21 20:59	reached heat=high · +31.0h · via ledger	—	—

pace: p96 vs 1032 stories at the 336h mark (now 506h old) — ahead of heretic-model-unrestriction-tooling (1.0x), behind sonnet-55-release-economics (1.0x)

Evidence (5) — ⭐ canonical anchor

source	object	author	score	comments
🟠 reddit	Introducing Grok 4.7 singularity Retrieved article excerpt Open article · Retrieved 2026-09-21T16:23:38.283904+00:00 [Back to news](https://x.ai/news)Sep 21, 2026 # Introducing Grok 4.7 SpaceXAI's most powerful model for coding and knowledge work. Twice as fast, at half the price of comparable models. [Try for free](https://x.ai/build?utm_source=website&utm_medium=referral&utm_campaign=grok-4-7-blog&utm_content=build-cta)[Start building](https://console.x.ai?utm_source=website&utm_medium=referral&utm_campaign=grok-4-7-blog&utm_content=build-cta) Grok 4.7 is our most capable model for coding and knowledge work. It works longer on difficult tasks, checks its own work more carefully, and comes with our best-calibrated safeguards to date. Served at the same price and speed as [Grok 4.6](https://x.ai/news/grok-4-6), it is highly competitive in its class. A scatter and line chart comparing Fable 5.1, Opus 5, Grok 4.7, GPT-5.6 Sol, and Sonnet 5 scores against average cost per task.55%CursorBench 4.0 score50%45%40%35%30%25%20%$18$15$12$9$6$3$0Average cost per taskFable 5.1Opus 5GPT-5.6 SolSonnet 5Grok 4.7 CostTokensSteps On CursorBench 4.0, which stresses longer-running coding tasks, Grok 4.7 is at the frontier in price-performance. ## [Model Improvements](https://x.ai/news/grok-4-7#model-improvements) Grok 4.7 uses a new, larger base model compared to [Grok 4.6](https://x.ai/news/grok-4-6). It was trained with a longer reinforcement learning run on a harder mix of tasks, weighted toward problems that take many hours to complete. The model is better at verifying its own work and managing longer context. We also trained Grok 4.7 to natively understand the [Grok Bot](https://x.ai/bot) harness, making it better at conversational tasks and general knowledge work. Grok 4.7 xHigh Grok 4.6 High GPT-5.6 Sol Max Fable 5.1 Max Input token price, $ per million $2 $2 $4 $10 Output token price, $ per million $6 $6 $20 $50 Software engineeringCursorBench 4.0 46.3% 40.4% 41.7% 51.8% Software engineeringDeepSWE v1.1 71.0%\* 65.2% 72.7% 70.0% Electrical engineeringEEBench 64.0% 53.0% 39.4% 56.4% Multi-hour office workAA Briefcase v1.1 1,657 1,546 1,487 1,678 Multi-hour terminal workTerminal-Bench 4.0 38.0% 20.3% 37.3% 57.9% Legal workHarvey Legal Agent Benchmark 19.6% 15.8% 2.5% 6.7% Clinical reasoningHealthBench Professional 56.7% 48.5% 60.5% 62.1% \* high effort Token prices and benchmark scores for Grok 4.7, Grok 4.6, GPT-5.6 Sol, and Fable 5.1. Benchmarks are CursorBench 4.0, DeepSWE v1.1, EEBench, AA Briefcase v1.1, Terminal-Bench 4.0, Harvey Legal Agent Benchmark, and HealthBench Professional. An asterisk on Grok 4.7 DeepSWE marks a high-effort score. Grok 4.7 is better at creating documents and presentations. In GDPval and AA Briefcase, AI is asked to work on tasks done by professionals such as lawyers, nurses, and financial analysts. Grok 4.7 improves upon Grok 4.6 on both benchmarks and performs comparably to other frontier models. Professional knowledge workMulti-hour office workElectrical engineering Professional knowledge work GDPval 050010001500Elo score1735Fable 5.1 (max)1695Grok 4.7 (xhigh)1605Grok 4.6 (high)1542GPT-6 Astra (max) GDPval, AA Briefcase, and EEBench scores comparing Grok 4.7 with Grok 4.6, Fable 5.1, and GPT-6 Astra. ## [Safety & Cybersecurity](https://x.ai/news/grok-4-7#safety--cybersecurity) Grok 4.7 was built with an entirely new safeguard stack. It is the strongest model we’ve tested on refusals and jailbreak resistance. In dual-use domains like cybersecurity and biological work, it leads on both utility for benign tasks and safe refusal on dangerous ones, topping LatchBio’s biosafety benchmark at 62.4%. Grok 4.7 balances strong cyber defense capabilities with low refusal rates for legitimate use. It shows the highest safety on HackerBench v0.3, our benchmark for risky and malicious cyber tasks, allowing only 3.3% of risky dual-use prompts through while rarely blocking legitimate security work. We’ve also started giving select cybersecurity partners invite-only access to Grok 4.7’s red-team capabilities for defense research. ## [Pricing and availability](https://x.ai/news/grok-4-7#pricing-and-availability) Grok 4.7 is available today in [Cursor](https://cursor.com) and [Grok Build](https://x.ai/build). It is also available through the [Grok API](https://console.x.ai?campaign=grok-4-7-blog&utm_source=website&utm_medium=referral&utm_campaign=grok-4-7-blog), third-party coding harnesses, and model routers and cloud platforms. The model is priced starting at $2 per million input tokens and $6 per million output tokens. We also serve a fast variant with twice the output speed at twice the price. [Console Create an API key](https://console.x.ai/team/default/api-keys?campaign=grok-4-7-blog&utm_source=website&utm_medium=referral&utm_campaign=grok-4-7-blog)[docs.x.ai Read the docs](https://docs.x.ai) ### Try it in Grok Build for free Get started today at [x.ai/build](https://x.ai/build). `$ curl -fsSL https://x.ai/cli/install.sh \| bash`	AMBNNJ	389	113
🟧 hn	Grok 4.7 Retrieved article excerpt Open article · Retrieved 2026-09-21T16:23:39.204306+00:00 [Back to news](https://x.ai/news)Sep 21, 2026 # Introducing Grok 4.7 SpaceXAI's most powerful model for coding and knowledge work. Twice as fast, at half the price of comparable models. [Try for free](https://x.ai/build?utm_source=website&utm_medium=referral&utm_campaign=grok-4-7-blog&utm_content=build-cta)[Start building](https://console.x.ai?utm_source=website&utm_medium=referral&utm_campaign=grok-4-7-blog&utm_content=build-cta) Grok 4.7 is our most capable model for coding and knowledge work. It works longer on difficult tasks, checks its own work more carefully, and comes with our best-calibrated safeguards to date. Served at the same price and speed as [Grok 4.6](https://x.ai/news/grok-4-6), it is highly competitive in its class. A scatter and line chart comparing Fable 5.1, Opus 5, Grok 4.7, GPT-5.6 Sol, and Sonnet 5 scores against average cost per task.55%CursorBench 4.0 score50%45%40%35%30%25%20%$18$15$12$9$6$3$0Average cost per taskFable 5.1Opus 5GPT-5.6 SolSonnet 5Grok 4.7 CostTokensSteps On CursorBench 4.0, which stresses longer-running coding tasks, Grok 4.7 is at the frontier in price-performance. ## [Model Improvements](https://x.ai/news/grok-4-7#model-improvements) Grok 4.7 uses a new, larger base model compared to [Grok 4.6](https://x.ai/news/grok-4-6). It was trained with a longer reinforcement learning run on a harder mix of tasks, weighted toward problems that take many hours to complete. The model is better at verifying its own work and managing longer context. We also trained Grok 4.7 to natively understand the [Grok Bot](https://x.ai/bot) harness, making it better at conversational tasks and general knowledge work. Grok 4.7 xHigh Grok 4.6 High GPT-5.6 Sol Max Fable 5.1 Max Input token price, $ per million $2 $2 $4 $10 Output token price, $ per million $6 $6 $20 $50 Software engineeringCursorBench 4.0 46.3% 40.4% 41.7% 51.8% Software engineeringDeepSWE v1.1 71.0%\* 65.2% 72.7% 70.0% Electrical engineeringEEBench 64.0% 53.0% 39.4% 56.4% Multi-hour office workAA Briefcase v1.1 1,657 1,546 1,487 1,678 Multi-hour terminal workTerminal-Bench 4.0 38.0% 20.3% 37.3% 57.9% Legal workHarvey Legal Agent Benchmark 19.6% 15.8% 2.5% 6.7% Clinical reasoningHealthBench Professional 56.7% 48.5% 60.5% 62.1% \* high effort Token prices and benchmark scores for Grok 4.7, Grok 4.6, GPT-5.6 Sol, and Fable 5.1. Benchmarks are CursorBench 4.0, DeepSWE v1.1, EEBench, AA Briefcase v1.1, Terminal-Bench 4.0, Harvey Legal Agent Benchmark, and HealthBench Professional. An asterisk on Grok 4.7 DeepSWE marks a high-effort score. Grok 4.7 is better at creating documents and presentations. In GDPval and AA Briefcase, AI is asked to work on tasks done by professionals such as lawyers, nurses, and financial analysts. Grok 4.7 improves upon Grok 4.6 on both benchmarks and performs comparably to other frontier models. Professional knowledge workMulti-hour office workElectrical engineering Professional knowledge work GDPval 050010001500Elo score1735Fable 5.1 (max)1695Grok 4.7 (xhigh)1605Grok 4.6 (high)1542GPT-6 Astra (max) GDPval, AA Briefcase, and EEBench scores comparing Grok 4.7 with Grok 4.6, Fable 5.1, and GPT-6 Astra. ## [Safety & Cybersecurity](https://x.ai/news/grok-4-7#safety--cybersecurity) Grok 4.7 was built with an entirely new safeguard stack. It is the strongest model we’ve tested on refusals and jailbreak resistance. In dual-use domains like cybersecurity and biological work, it leads on both utility for benign tasks and safe refusal on dangerous ones, topping LatchBio’s biosafety benchmark at 62.4%. Grok 4.7 balances strong cyber defense capabilities with low refusal rates for legitimate use. It shows the highest safety on HackerBench v0.3, our benchmark for risky and malicious cyber tasks, allowing only 3.3% of risky dual-use prompts through while rarely blocking legitimate security work. We’ve also started giving select cybersecurity partners invite-only access to Grok 4.7’s red-team capabilities for defense research. ## [Pricing and availability](https://x.ai/news/grok-4-7#pricing-and-availability) Grok 4.7 is available today in [Cursor](https://cursor.com) and [Grok Build](https://x.ai/build). It is also available through the [Grok API](https://console.x.ai?campaign=grok-4-7-blog&utm_source=website&utm_medium=referral&utm_campaign=grok-4-7-blog), third-party coding harnesses, and model routers and cloud platforms. The model is priced starting at $2 per million input tokens and $6 per million output tokens. We also serve a fast variant with twice the output speed at twice the price. [Console Create an API key](https://console.x.ai/team/default/api-keys?campaign=grok-4-7-blog&utm_source=website&utm_medium=referral&utm_campaign=grok-4-7-blog)[docs.x.ai Read the docs](https://docs.x.ai) ### Try it in Grok Build for free Get started today at [x.ai/build](https://x.ai/build). `$ curl -fsSL https://x.ai/cli/install.sh \| bash`	meetpateltech	609	491
🟧 echo.blog ⭐	Announces Grok 4.7 availability through Cursor, Grok Build, and the API; claims improved multi-hour task performance and frontier price-perf	SpaceXAI	—	—
🟧 hn	Grok 4.7 Intelligence, Performance and Price Analysis	theanonymousone	13	1
🟠 reddit	Elon Musk admits Grok isn’t as good as Anthropic’s Claude ClaudeAI	ross2000	769	117

Interpretation history

2026-09-26T20:44:19Z
magnitude valve eligible (multi-platform, top-decile engagement) and never alerted; deterministic escalation to deliver
2026-09-26T20:26:30Z
evidence attached: reddit.post.1wqzu96 — First-party admission by Musk that Grok trails Claude undercuts the case's frontier-comparable-performance claim.
2026-09-21T20:59:41Z
The purported independent analysis adds no usable benchmark results: its only supplied excerpt quotes implausible zero-dollar pricing, so it cannot corroborate the price-performance thesis. Attention nevertheless merits high heat given strong HN and Reddit spread and an additional analysis thread; the retrieved launch page also contradicts the cached grounding's claim that release and pricing remain undocumented.
2026-09-21T20:23:25Z
evidence attached: hn.story.49789558 — Independent Artificial Analysis benchmarking materially contextualizes Grok 4.7's claimed intelligence, performance, and price advantage.
2026-09-21T16:27:40Z
grounded: known/medium — The supported price/performance pitch adds no established position beyond Scott’s AI Unit Economics and Model-Plus-Harness Benchmark Unit: compare cost per succ
2026-09-21T16:24:08Z
case created — Both observations echo one available model release with concrete pricing and owner-reported benchmarks, warranting a single case rather than separate capability and release episodes.

Decision trace

10-11 21:09drop_targetsquiet through full ladder or over cap 8
10-01 20:45drop_targetsquiet through full ladder or over cap 8
09-28 08:53review_screenjev screen: no material development (noul=0.09)
09-28 06:21sensor_dirtycomment_update
09-27 06:44repriceThe launch wave is over: current velocity is ~4 pts/h against a 377 peak, and the magnitude-valve spread reading reflects launch-day cumulatives rather than ongoing reach — the only new item in five d
09-27 06:26attachFirst-party admission by Musk that Grok trails Claude undercuts the case's frontier-comparable-performance claim.
09-27 06:24propose_attachFirst-party admission by Musk that Grok trails Claude undercuts the case's frontier-comparable-performance claim.
09-25 01:45review_screenjev screen: no material development (noul=0.08)
09-22 12:20sensor_dirtycomment_update
09-22 07:20sensor_dirtycomment_update
09-22 06:59repriceThe purported independent analysis adds no usable benchmark results: its only supplied excerpt quotes implausible zero-dollar pricing, so it cannot corroborate the price-performance thesis. Attention
09-22 06:59push_suppresseddaily alert ceiling (6/day) spent
09-22 06:59alert_routeAnnounces Grok 4.7 availability through Cursor, Grok Build, and the API; claims improved multi-hour task performance and frontier price-perf — The purported independent analysis adds no usable benchma
09-22 06:23attachIndependent Artificial Analysis benchmarking materially contextualizes Grok 4.7's claimed intelligence, performance, and price advantage.
09-22 06:23propose_attachIndependent Artificial Analysis benchmarking materially contextualizes Grok 4.7's claimed intelligence, performance, and price advantage.
09-22 03:23sensor_dirtycomment_update
09-22 03:23sensor_dirtyvelocity_spike
09-22 02:27groundThe supported price/performance pitch adds no established position beyond Scott’s AI Unit Economics and Model-Plus-Harness Benchmark Unit: compare cost per successful task under a disclosed harness, n
09-22 02:24createBoth observations echo one available model release with concrete pricing and owner-reported benchmarks, warranting a single case rather than separate capability and release episodes.