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xAI Proprietary Released Sep 21, 2026 Updated

Grok 4.7

ToolsGuide Scores, rankings, test results and price.

Model summary

  • Text #90 / 416

    399 / 1,000

    ToolsGuide Score· votes only

  • Vision #58 / 167

    440 / 1,000

    ToolsGuide Score· votes only

  • Coding #16 / 147

    496 / 1,000

    ToolsGuide Score· votes 483, tests 516

  • Agents #19 / 53

    490 / 1,000

    ToolsGuide Score· votes only

  • Price per 1M tokens

    In $2.00· Out $6.00

    $2.00

    Input · median coding model $0.75

Summary

Grok 4.7 is xAI's model, released Sep 21, 2026. It's ranked in 4 categories and does best at coding: #16 of 147, with a ToolsGuide Score of 496 against a median of 316.

It also ranks #90 of 416 for text (399), #58 of 167 for vision (440), #19 of 53 for agents (490).

Its text and vision and agents score uses votes only, because it has published fewer than two of the tests used for those categories.

It costs $2.00 per million input tokens and $6.00 per million output tokens, about 2.7× the median coding model ($0.75).

It has published results on 23 tests and has the top score on 15 of them, including Harvey's Legal Agent Benchmark and Harvey LAB (Vals).

Specifications

Creator
xAI
Licence
Proprietary
Released
Sep 21, 2026
Context window
500K tokens
Input price
$2.00 / 1M
Output price
$6.00 / 1M
Tests reported
23
Settings ranked
grok-4.7-xhigh, Grok 4.7 (xHigh)

Model comparison

Against the ten best coding models.

Coding score

ToolsGuide Score out of 1,000 · Higher is better

Text score

ToolsGuide Score out of 1,000 · Higher is better

Input price

USD per 1M input tokens · Lower is better

Leaderboards

Where Grok 4.7 sits among the top 20 in each category.

Text

#90 of 416 · ToolsGuide Score out of 1,000, where 1,000 is a flawless model

Full text leaderboard →

Vision

#58 of 167 · ToolsGuide Score out of 1,000, where 1,000 is a flawless model

Full vision leaderboard →

Coding

#16 of 147 · ToolsGuide Score out of 1,000, where 1,000 is a flawless model

Full coding leaderboard →

Agents

#19 of 53 · ToolsGuide Score out of 1,000, where 1,000 is a flawless model

Full agents leaderboard →

By task

Scored from votes on each kind of prompt alone, on the same 1,000-point scale.

Score against price

Coding · the 10 priced models ranked closest · up and to the left is better value

Against its nearest rivals

Text prompts by kind · ToolsGuide Score from votes · hover for values

Text

grok-4.7-xhigh · hover a bar for its rank

Vision

Grok 4.7 (xHigh) · hover a bar for its rank

Coding

Grok 4.7 (xHigh) · hover a bar for its rank

Test results

Every test Grok 4.7 has a published result on, out of 100%, with its rank among the models that took it.

  • DeepSWE 1.1

    #17 / 50

    DeepSWE 1.1 evaluates software engineering agents using the mini-swe-agent harness.

    71.0%

    Self-reported · In the coding score

  • Terminal-Bench 4.0

    #15 / 28

    Terminal-Bench 4.0 evaluates AI agents on real-world work in terminal and command-line containerized environments across 66 tasks, with emphasis on science-adjacent and frontier engineering problems. Relative to earlier Terminal-Bench releases, 4.0 increases timeouts and adaptively raises RAM/CPU on selected tasks to reduce harness and resource confounds.

    38.0%

    Self-reported · In the coding score· In the agents score

  • CyberGym

    #12 / 21

    CyberGym is a benchmark for evaluating AI agents on cybersecurity tasks, testing their ability to identify vulnerabilities, perform security analysis, and complete security-related challenges in a controlled environment.

    80.3%

    Self-reported

  • HealthBench Professional

    #15 / 19

    HealthBench Professional evaluates model capability and safety for clinician use cases using real clinician-style chats and physician-authored grading rubrics.

    56.7%

    Self-reported

  • SWE-Marathon

    #5 / 10

    SWE-Marathon is an ultra-long-horizon software engineering benchmark covering tasks such as building compilers, optimizing kernels, and developing production-grade services. It measures whether agents can sustain quality across extremely long engineering trajectories.

    46.0%

    Self-reported

  • AA-Briefcase v1.1

    #3 / 5

    AA-Briefcase v1.1 evaluates multi-hour professional office work and reports Elo scores. Kept separate from unversioned AA-Briefcase results.

    55.2%

    Self-reported

  • FrontierSWE V2

    #5 / 5

    FrontierSWE V2 evaluates agents on open-ended technical projects and reports mean@5. Kept separate from FrontierSWE V1 dominance-score results, which are not comparable.

    29.0%

    Self-reported

  • Harvey's Legal Agent Benchmark

    #1 / 4

    Harvey's Legal Agent Benchmark evaluates AI agents on complex legal workflows and reports the all-pass rate.

    19.6%

    Self-reported

  • CursorBench 4.0

    #3 / 3

    CursorBench 4.0 evaluates coding agents on long-horizon coding tasks from real Cursor sessions. Version 4.0 adds longer-horizon tasks; scores are not comparable with CursorBench 3.2.

    46.3%

    Self-reported

  • Harvey LAB (Vals)

    #1 / 2

    Harvey LAB (Vals) is a professional legal-work evaluation of AI systems on complex law-firm style tasks, reported by Vals.

    19.6%

    Unverified

  • ProtocolQA Open-Ended

    #1 / 2

    ProtocolQA Open-Ended evaluates free-form answers on troubleshooting failed experimental outcomes from common biological laboratory protocols. Kept separate from the multiple-choice ProtocolQA split.

    70.4%

    Unverified

  • Virology Capabilities Test

    #1 / 2

    Virology Capabilities Test (VCT) is an expert-level multiple-choice benchmark measuring the capability to troubleshoot complex virology laboratory protocols. It evaluates dual-use biological knowledge relevant to bioweapons development.

    63.0%

    Unverified

  • BixBench MCQ

    #1 / 1

    BixBench zero-shot multiple-choice accuracy on bioinformatics questions. Kept separate from the agentic BixBench workflow evaluation that requires code execution.

    88.4%

    Unverified

  • CADGenBench

    #1 / 1

    CADGenBench evaluates agents on CAD model construction from design prompts. The generation split requires producing CAD geometry graded for executability and geometric correctness. Distinct from BenchCAD.

    44.4%

    Unverified

  • CVE-Bench

    #1 / 1

    CVE-Bench evaluates agents on exploiting real-world web-application CVEs in sandboxed environments that mimic production services, typically in unrestricted / egress-controlled settings as a cyber capability probe.

    36.6%

    Unverified

  • CathedralBench

    #1 / 1

    CathedralBench is a third-party red-team cyber evaluation on highly difficult, multiple-exploit-chain tasks in egress-secure sandboxes. Accuracy is commonly reported on the hard subset of tasks in an unrestricted configuration.

    29.0%

    Unverified

  • EEBench

    #1 / 1

    EEBench is an electrical engineering and chip design benchmark: models design circuits and other hardware that are graded for physical correctness and functionality.

    66.0%

    Unverified

  • GDPval (Elo)

    #1 / 1

    GDPval professional knowledge-work results reported as Elo in xAI's Grok 4.7 announcement. The source does not identify this as GDPval-AA v2; kept separate from that evaluation and percentage-based GDPval scores.

    56.5%

    Unverified

  • LAB-Bench Practical

    #1 / 1

    LAB-Bench practical is a public multiple-choice evaluation of everyday wet-lab and research skills, covering protocol troubleshooting, sequence reasoning, and cloning scenarios. Distinct from labbench2.

    76.8%

    Unverified

  • LatchBio Capabilities v1.0

    #1 / 1

    LatchBio Capabilities v1.0 is a cross-benchmark evaluation of agentic biological data analysis. The overall score is the equally weighted mean of observed scores across 11 capability benchmarks.

    44.5%

    Unverified

  • WMDP-Bio

    #1 / 1

    Biology subset of WMDP (Weapons of Mass Destruction Proxy). Multiple-choice questions measuring dual-use biology knowledge relevant to enabling malicious actors to design, synthesize, acquire, or use biological weapons.

    88.1%

    Unverified

  • WMDP-Chem

    #1 / 1

    Chemistry subset of WMDP (Weapons of Mass Destruction Proxy). Multiple-choice questions measuring dual-use chemistry knowledge relevant to enabling malicious actors to design, synthesize, acquire, or use chemical weapons.

    84.9%

    Unverified

  • WMDP-Cyber

    #1 / 1

    Cybersecurity subset of WMDP (Weapons of Mass Destruction Proxy). Multiple-choice questions measuring dual-use cyber knowledge relevant to enabling malicious actors to engage in offensive cyber operations.

    88.1%

    Unverified