Grok 4.7 landed on September 21, 2026 — and if you follow AI model releases closely, you already know the drill: a big announcement, impressive self-reported benchmarks, and then the independent evaluators arriving with more nuanced data. This grok 4.7 review benchmarks 2026 cuts through that noise. The question isn’t whether Grok 4.7 is better than Grok 4.6 (it clearly is). The real question is whether it changes anything about your current model stack — specifically if you’re running Claude Fable 5.1 or considering GPT-6 Astra.
What Actually Shipped: Grok 4.7 Specs and the SpaceX Angle
Grok 4.7 was released on September 21, 2026, with model ID grok-4.7 on the Grok API, priced at $2 per million input tokens, $0.50 cached, and $6 per million output tokens under 200k prompt tokens. Above the 200k threshold, pricing doubles to $4/$1/$12.
Grok 4.7 runs on a new, larger base model than its predecessor. According to Elon Musk, it ships with 2.1 trillion parameters — a 40% increase over Grok 4.6’s 1.5 trillion. That’s not an incremental tweak; it’s a structural rebuild.
xAI says Grok 4.7 uses a new, larger base model, a longer reinforcement learning run, and training that puts more weight on difficult tasks that can take hours to complete. It also improves self-verification and long-context management — two areas that matter much more in real workflows than simply answering short prompts.
The training data angle is where things get strategically interesting. xAI supplemented its training dataset with internal engineering records from SpaceX, including Starlink satellite telemetry, manufacturing logs, and failure analysis data. SpaceXAI doesn’t just own an AI lab — it owns an aerospace company generating petabytes of engineering telemetry, sensor data, and internal documentation. Feeding that into a frontier model creates a training corpus that no competitor can replicate.
Context window sits at 500,000 tokens. Pretraining cutoff is June 2026, with supplemental training through August 2026. It is available through the xAI API as grok-4.7, and at launch xAI also made the model available through Grok Build and Cursor. GitHub began rolling Grok 4.7 out to GitHub Copilot users.
The Independent Benchmark Picture: Where Grok 4.7 Actually Stands
SpaceXAI’s own launch table shows Grok 4.7 winning on several metrics. Independent evaluators tell a more layered story. This is the section that matters most for your grok 4.7 review benchmarks 2026 decision.
The Composite Intelligence Index: Mid-Pack, Not Frontier
On the independent Artificial Analysis Intelligence Index (v4.3.2), which combines ten benchmarks, Grok 4.7 scores 46 and lands mid-pack. Claude Fable 5.1 and GPT-6 lead with 53 each. That score places it well above average among other reasoning models in a similar price tier, where the median is 24. So context matters: mid-pack at the frontier is still impressive, but the gap to the leaders is real and consistent.
Agentic Coding: A Meaningful Leap, But Still Behind
Grok 4.7 (xhigh) with Grok Build scores 56 on the Artificial Analysis Coding Agent Index, up +9 points from Grok 4.6 (xhigh). Among models in their native harnesses, Grok 4.7 + Grok Build now ranks 4th, behind only Claude Fable 5.1, GPT-6 Astra, and Claude Opus 5.
Grok Build with Grok 4.7 (xhigh) scores 56 on the Artificial Analysis Coding Agent Index, up from 47 with Grok 4.6 (xhigh). It improves across all three components: DeepSWE v1.1 rises from 65% to 73%, Terminal-Bench 4.0 from 18% to 33%, and SWE-Atlas-QnA from 58% to 63%.
The Terminal-Bench number is where the gap becomes impossible to ignore. On Terminal-Bench 4.0, Grok 4.7 hits just 26 percent, versus 60 percent for GPT-6 Astra and 55 percent for Claude Fable 5.1. Even the cheaper DeepSeek V4.1 Flash edges past it at 27 percent. Note that xAI’s own harness reports 38% on this same benchmark — different harnesses, reasoning settings, tool configurations, token budgets, and evaluation environments can move these scores around considerably, as was seen after GPT-6 Astra launched.
Where Grok 4.7 Genuinely Wins
The benchmark story isn’t all bad. There are specific domains where this model is legitimately competitive or dominant.
The headline that matters for practitioners is the Harvey Legal Agent Benchmark, where Grok 4.7 posts 19.6% — more than 7x GPT-5.6 Sol’s 2.5% and nearly 3x Fable 5.1’s 6.7%, a gap wide enough that legal-adjacent agentic work is a genuine reason to consider the switch.
On EEBench, covering electrical engineering, SpaceXAI reports 64.0% for Grok 4.7, versus 53.0% for Grok 4.6, 39.4% for GPT-5.6 Sol, and 56.4% for Fable 5.1. This is the top score in the table — likely a direct result of SpaceX engineering data in training.
On DeepSWE v1.1 at high effort, Grok 4.7 reached 71.0%, up from 65.2% on Grok 4.6. For coding workloads on CursorBench 4.0, it posted 46.3% accuracy, outperforming GPT-5.6 Sol Max (41.7%) while trailing Anthropic’s Claude Fable 5.1 (51.8%).
On AA-Briefcase, the private benchmark for long-horizon agentic knowledge work, Grok 4.7 gains +111 Elo over Grok 4.6 (high), scoring 1657 Elo and placing it just behind Claude Opus 5 and Claude Fable 5.1 at the frontier. On GDPval-AA, it scores 1695 Elo, +90 ahead of Grok 4.6 (high).
The Token-Cost Trap You Need to Know About
Pricing at $2/$6 sounds aggressive, but per-token cost is not the same as per-task cost. Grok 4.7 xhigh uses approximately 81K output tokens per task versus approximately 27K for GPT-6 Astra, eroding the cost advantage at production scale. When evaluating the Intelligence Index, it generated 200M tokens, which is very verbose in comparison to the median of 94M. If your workload involves high-volume, short-output tasks, the cost math still favors Grok. For multi-step agentic workflows, run your own numbers before committing.
Should You Switch From Claude Fable 5.1? A Workload-by-Workload Framework
This is the question this grok 4.7 benchmarks 2026 analysis is really about. The honest answer isn’t binary — it depends entirely on which tasks you’re running at scale.
Switch to Grok 4.7 If Your Workload Fits These Patterns
Legal-adjacent agentic tasks. The Harvey Legal Agent Benchmark result — 19.6% versus Fable 5.1’s 6.7% — is more than 7x GPT-5.6 Sol’s 2.5% and nearly 3x Fable 5.1’s 6.7%, a gap wide enough that legal-adjacent agentic work is a genuine reason to route specific workflows through Grok 4.7 rather than Claude.
Electrical engineering and chip design tasks. The model handily outperformed Fable 5.1 on the Harvey Legal Agent Benchmark and EEBench, which contain legal and chip design tasks, respectively. If you’re building tooling for hardware teams, this gap is material.
Budget-sensitive, mid-complexity coding. Grok 4.7 is a price-performance leader rather than an outright capability leader. It beats GPT-5.6 Sol on most coding and knowledge benchmarks while charging less than a third of Sol’s output price, but Fable 5.1 still edges it on absolute coding scores.
Long-horizon knowledge work with Grok Build. Grok 4.7 gains +111 Elo over Grok 4.6 (high) on AA-Briefcase, placing it just behind Claude Opus 5 and Claude Fable 5.1 at the frontier. If you’re already embedded in the Grok Build or Cursor ecosystem, the upgrade from 4.6 is worth taking immediately.
Don’t Switch If Your Workload Looks Like This
Terminal-heavy agentic coding. On Terminal-Bench 4.0, Grok 4.7 places behind GPT-6 Astra (60%) and Claude Fable 5.1 (55%), and even slightly behind the cheaper DeepSeek V4.1 Flash (27%). If terminal agent work is your core workload, the frontier models still decisively win on raw capability.
Clinical reasoning applications. On HealthBench Professional, a clinical reasoning evaluation, the reported figures are 56.7% for Grok 4.7 versus 60.5% for GPT-5.6 Sol and 62.1% for Fable 5.1. Claude’s edge here is consistent and significant.
Maximum composite performance, cost notwithstanding. GPT-6 Astra leads on the hardest agentic benchmark by a wide margin. Claude Fable 5.1 sits close behind GPT-6 Astra on the composite index and comfortably ahead of Grok 4.7 on Terminal-Bench, while pricing itself at the top of the market. For teams where quality ceiling matters more than price-performance ratio, Fable 5.1 remains the stronger choice.
The Real Strategic Play: Hybrid Routing, Not a Full Migration
The framing of “switching from Claude” misses what experienced AI-enthusiasts already know: no production stack in 2026 should be single-model. The one benchmark where Grok 4.7 leads everyone by a wide margin is legal agent work. On CursorBench 4.0, which stresses longer-running coding tasks, Grok 4.7 scores 46.3%. That pattern — domain-specific dominance alongside general mid-pack placement — is the clearest signal for how to use it.
A rational routing strategy based on the confirmed benchmark data from this grok 4.7 review benchmarks 2026:
- Route to Grok 4.7: Legal document analysis agents, electrical engineering and hardware design tasks, mid-complexity SWE tasks where CursorBench performance matters, and any long-horizon knowledge work inside Grok Build or Cursor.
- Keep on Claude Fable 5.1: Terminal-heavy agentic pipelines, clinical reasoning workflows, tasks requiring top composite reasoning scores, and any workload where token verbosity makes Grok 4.7’s xhigh mode cost-inefficient.
Shortlist Grok 4.7 for repository work and long-running agents, then measure its completion rate on your own jobs. Start with high reasoning effort and compare it with xhigh before paying for extra thinking on every request.
What We Still Don’t Know
Scores from the model card are self-reported. Independent coverage from Artificial Analysis is already live and confirms the broad strokes, but deeper task-specific evaluations across longer agentic runs are still emerging. The Terminal-Bench number differs between xAI’s own result and Artificial Analysis’s measurement. Welcome to benchmarking AI agents in 2026 — different harnesses, reasoning settings, tool configurations, token budgets, and evaluation environments can move these scores around considerably.
Also worth flagging: with Elon Musk recently touting the upcoming Grok 4.9 as equivalent to Fable-class models, the expectations around Grok 4.7 were not high to begin with. The model that actually challenges Fable 5.1 across the board may still be coming. For now, Grok 4.7 is an excellent price-performance option for specific domains — and a clear upgrade from 4.6 — but not a wholesale replacement for the current Claude generation. Revisiting this grok 4.7 benchmarks 2026 assessment in 30 days, once more independent evaluations accumulate, remains the prudent move.
For teams already evaluating the Claude competitive landscape, our deep-dives on Claude Fable 5.1 and the Fable 5.1 vs GPT-6 benchmark comparison provide the baseline context for understanding where Grok 4.7 fits in the current frontier hierarchy.