GLM 5.3 Flash vs Grok 4.7
Full profiles: GLM 5.3 Flash (Zhipu AI) and Grok 4.7 (SpaceXAI): every benchmark, price and rank.
Updated · Data from 12 sources
As of 6 Nov 2026, GLM 5.3 Flash and Grok 4.7 are neck and neck on quality (56.8 vs 58.3 on the BenchLeader Index, inside the ±5.2 margin), and GLM 5.3 Flash is 13× cheaper at $0.238 vs $3.00 per 1M tokens blended. Choose GLM 5.3 Flash for maths (69 vs 56), multimodal (64 vs 56), and human preference (67 vs 62); choose Grok 4.7 for fast first answers (55.1 s vs 99.0 s) and knowledge (61 vs 46), reasoning (56 vs 49), and coding (62 vs 57).
Key facts (as of 6 Nov 2026)
- GLM 5.3 Flash scores 56.8 on the BenchLeader Index and Grok 4.7 scores 58.3 (BenchLeader, 6 Nov 2026).
- GLM 5.3 Flash costs $0.238 per 1M tokens blended (list price, 6 Nov 2026).
- Grok 4.7 costs $3.00 per 1M tokens blended (list price, 6 Nov 2026).
- Of the 47 benchmarks both models have, Grok 4.7 leads 32 (BenchLeader, 6 Nov 2026).
- On Arena WebDev, GLM 5.3 Flash is rated 1607 and Grok 4.7 1638 (LMArena, as published by 6 Nov 2026).
GLM 5.3 Flash benchmarks 
Grok 4.7 benchmarks Which to pick for…
The pick's numbers come first. Category scores on the BenchLeader scale (50 is the average model, 15 points one standard deviation). High confidence means a lead of half a standard deviation or more; under one point is called either.
| Use case | Pick | Why | Confidence |
|---|---|---|---|
| Coding | Grok 4.7 | 62 vs 57 category score; Arena WebDev 1638 vs 1607 | Medium |
| Agents & tool use | GLM 5.3 Flash | 60 vs 57 category score; Arena Agent -2.4 vs 2.7 | Medium |
| Maths | GLM 5.3 Flash | 69 vs 56 category score; Arena Maths 1503 vs 1443 | High |
| Reasoning | Grok 4.7 | 56 vs 49 category score; HLE-Diamond (AA) 23.2% vs 18.2% | Medium |
| Knowledge | Grok 4.7 | 61 vs 46 category score; AA-Omniscience v1.1 31.2 vs 0.7 | High |
| Long documents | GLM 5.3 Flash | 65 vs 63 category score; AA-LCR v1.1 80.0% vs 76.7% | Medium |
| Images and other media | GLM 5.3 Flash | 64 vs 56 category score; Arena Vision 1294 vs 1231 | High |
| Chat quality (human preference) | GLM 5.3 Flash | 67 vs 62 on Arena votes | Medium |
| Lowest cost | GLM 5.3 Flash | $0.238 vs $3.00 per 1M blended; agentic coding session $0.011 vs $0.144 | – |
| Fastest first answer | Grok 4.7 | 55.1 s (Grok 4.7 (xhigh)) vs 99.0 s (GLM 5.3 Flash) to the first answer token | – |
| High volume on a budget | Neither flagship | A smaller model is usually the better fit: Cheapest good LLMs, Fastest LLMs | – |
Key differences
- GLM 5.3 Flash and Grok 4.7 (xhigh) are neck and neck on quality (56.8 vs 58.3, within the ±5.2 margin).
- GLM 5.3 Flash is stronger in agents & tools, composite, human preference, long context, maths, multimodal.
- Grok 4.7 (xhigh) is stronger in coding, knowledge, reasoning.
- GLM 5.3 Flash is 13× cheaper ($0.238 vs $3.00 per 1M blended).
At a glance
| Spec | GLM 5.3 Flash | Grok 4.7 |
|---|---|---|
| Developer | Zhipu AI | SpaceXAI |
| Released | 20 Aug 2026 | 21 Sep 2026 |
| Context window (tokens) | 1,000,000 | 500,000 |
| Compared at | GLM 5.3 Flash | Grok 4.7 (xhigh) |
| Open weights | Yes | No |
| Price in / out / cached input per 1M | $0.150 / $0.500 / $0.030 | $2.00 / $6.00 / $0.500 |
Category by category
Category scores on the BenchLeader scale: 50 is the average evaluated model, 15 points is one standard deviation. A gap under one point is called level.
| Category | GLM 5.3 Flash | Grok 4.7 (xhigh) | Leader |
|---|---|---|---|
| Reasoning | 49.1 | 56.4 | Grok 4.7 |
| Coding | 57.4 | 61.5 | Grok 4.7 |
| Agents & tools | 59.7 | 56.9 | GLM 5.3 Flash |
| Maths | 68.5 | 55.9 | GLM 5.3 Flash |
| Knowledge | 46.0 | 61.1 | Grok 4.7 |
| Human preference | 66.6 | 62.3 | GLM 5.3 Flash |
| Multimodal | 63.8 | 55.7 | GLM 5.3 Flash |
| Long context | 64.8 | 63.1 | GLM 5.3 Flash |
| Composite | 45.1 | – | not comparable |
On one chart
Each domain on the index's own scale, where 50 is an average model. Click a domain to see the benchmarks behind it. Pick up to 5 models from the list.
Not drawn, measured for fewer than two of these models: Instruction following.
Where sources disagree
Across the 47 benchmarks both have, GLM 5.3 Flash leads 14, Grok 4.7 leads 32 and 1 is a tie. Independent sources split: GLM 5.3 Flash leads on Arena Text; Grok 4.7 leads on AA Intelligence Index v5.0 and Vals Index.
| Overall index | GLM 5.3 Flash | Grok 4.7 (xhigh) | Leader |
|---|---|---|---|
| BenchLeader Index | 56.8 | 58.3 | neck and neck |
| AA Intelligence Index v5.0 | 27.8 | 35.5 | Grok 4.7 |
| Vals Index | 50.9† | 58.6 | Grok 4.7 |
| Arena Text | 1477 | 1441 | GLM 5.3 Flash |
Each publisher runs its own tasks, harnesses and effort settings, so their overall verdicts can differ; BenchLeader reconciles them on one scale. † measured at another effort setting of the same model (the publisher did not test the one compared here).
Price, speed and latency
List prices blended at three input tokens per output token. Per-task prices use the token counts on the methodology page. Cost, tokens and time per benchmark task are measured: Artificial Analysis’ averages over its whole Intelligence Index run.
| Measure | GLM 5.3 Flash | Grok 4.7 (xhigh) |
|---|---|---|
| Blended price per 1M tokens | $0.238 | $3.00 |
| Input / output per 1M | $0.150 / $0.500 | $2.00 / $6.00 |
| Cached input per 1M | $0.030 | $0.500 |
| Price per task: chat reply | $0.0002 | $0.0026 |
| Price per task: summarize a 30-page report | $0.0021 | $0.028 |
| Price per task: code edit | $0.0017 | $0.021 |
| Price per task: agentic coding session | $0.011 | $0.144 |
| Price per task: structured extraction | $0.0004 | $0.0052 |
| Agentic coding session, input mostly cached | $0.0056 | $0.076 |
| Cost per benchmark task (AA Index) | $0.583 | $7.77 |
| Output tokens per task (AA Index) | 134k | 105k |
| Of which reasoning | 103k | 69k |
| Time per task (AA Index) | 40 min | 24 min |
| Output speed | 56 tok/s | 71 tok/s |
| Time to first answer | 99.0 s | 55.1 s |
| Time to a complete answer | 218.1 s | 147.2 s |
Per token is not per task: an average task of Artificial Analysis' Intelligence Index cost $0.583 on GLM 5.3 Flash and $7.77 on Grok 4.7 (xhigh), and GLM 5.3 Flash wrote 1.3× as many output tokens for the same work.
Each model is compared at its best-ranked reasoning-effort setting. GLM 5.3 Flash scores 56.8 and takes 99 s to its first answer token; GLM 5.3 Flash (max) scores 54.2 in 99 s. Grok 4.7 (xhigh) scores 58.3 and takes 55 s to its first answer token; Grok 4.7 (high) scores 57.7 in 31 s, Grok 4.7 (low) scores 56.0 in 9 s. Higher effort means more thinking before the answer: better scores, longer waits and more tokens billed. How reasoning effort changes scores and cost.
Every benchmark
137 benchmarks, grouped by category; each name links to the board and its leaders. † measured at another effort setting of the same model, shown for reference and not counted as a win.
| Metric | Publisher | GLM 5.3 Flash | Grok 4.7 (xhigh) |
|---|---|---|---|
| BenchLeader Index | BenchLeader | 56.8 | 58.3 |
| Agents & tools score | BenchLeader | 59.7 | 56.9 |
| Coding score | BenchLeader | 57.4 | 61.5 |
| Composite score | BenchLeader | 45.1 | – |
| Human preference score | BenchLeader | 66.6 | 62.3 |
| Knowledge score | BenchLeader | 46.0 | 61.1 |
| Long context score | BenchLeader | 64.8 | 63.1 |
| Maths score | BenchLeader | 68.5 | 55.9 |
| Multimodal score | BenchLeader | 63.8 | 55.7 |
| Reasoning score | BenchLeader | 49.1 | 56.4 |
| Blended price $/M | BenchLeader | $0.238 | $3.00 |
| Output speed | BenchLeader | 56 tok/s | 71 tok/s |
| Time to first answer | BenchLeader | 99.0 s | 55.1 s |
| Context window | BenchLeader | 1,000,000 tokens | 500,000 tokens |
| Reasoning | |||
| GPQA Diamond | Epoch AI Benchmarking Hub | 90.2%† | 92.7% |
| Arena Hard Prompts | Arena (LMArena) | 1502 | 1463 |
| LiveBench 2.0 Reasoning | LiveBench | 77.6% | 82.7%† |
| LiveBench 1.0 Reasoning | LiveBench | 77.6% | 82.7% |
| GPQA Diamond (AA) | Artificial Analysis | 91.2% | – |
| Humanity's Last Exam (AA) | Artificial Analysis | 39.9% | 43.1% |
| HLE-Diamond (AA) | Artificial Analysis | 18.2% | 23.2% |
| GPQA Diamond (Vals) | Vals AI | 86.4%† | – |
| ARC-AGI-1 | ARC Prize | 91.0%† | 89.5% |
| ARC-AGI-2 | ARC Prize | 65.8%† | 61.4% |
| ARC-AGI-3 | ARC Prize | – | 7.0% |
| CritPt | Artificial Analysis | 15.4% | 17.7% |
| CritPt v2 hard subset (AA) | Artificial Analysis | 24.5% | 33.5% |
| MysteryMechanism | Vals AI | – | 25.2% |
| Chess Puzzles | Epoch AI Benchmarking Hub | 21.0%† | 41.0% |
| Mystery Game Puzzles | Epoch AI Benchmarking Hub | 8.0%† | 29.0% |
| LMCA | Epoch AI Benchmarking Hub | – | 49.4% |
| DTBench | Epoch AI Benchmarking Hub | – | 96.0% |
| BTF-3 | Epoch AI Benchmarking Hub | 14.9% | – |
| Coding | |||
| SciCode | SciCode | 51.6% | 57.4% |
| FrontierCode | Cognition | 31.8%† | 47.6%† |
| Arena Coding | Arena (LMArena) | 1526 | 1494 |
| Arena WebDev | Arena (LMArena) | 1607 | 1638 |
| LiveBench 2.0 Coding | LiveBench | 80.6% | 84.5%† |
| LiveBench 1.0 Coding | LiveBench | 79.0% | 77.2% |
Show all 137 benchmarks
| Metric | Publisher | GLM 5.3 Flash | Grok 4.7 (xhigh) |
|---|---|---|---|
| Coding | |||
| LiveCodeBench | Vals AI | 80.5%† | – |
| IOI | Vals AI | 52.5%† | 57.7% |
| SWE-bench (Vals) | Vals AI | 92.0%† | – |
| Code Migration | Vals AI | 20.5%† | 44.8% |
| Code Migration v1.1 | Vals AI | 51.6%† | 53.2% |
| ProgramBench | Vals AI | 0.0%† | 0.5% |
| SWE-bench Multimodal | Vals AI | – | 42.9% |
| Vibe Code Bench 1-100 | Vals AI | 16.0%† | – |
| Vibe Code Bench v1.1 | Vals AI | 30.8%† | 86.2% |
| Surface Evolver Bench | Epoch AI Benchmarking Hub | 52.5%† | – |
| DeepSWE v1.1 | Epoch AI Benchmarking Hub | 63.4%† | – |
| CursorBench | Cursor | 36.8%† | 46.3% |
| ALE-Bench | Epoch AI Benchmarking Hub | 303.6† | – |
| FrontierSWE | Epoch AI Benchmarking Hub | 18.1%† | 29.5% |
| Terminal-Bench 4.0 (AA) | Artificial Analysis | 32.8% | 25.8% |
| Terminal-Bench 2.1 (AA) | Artificial Analysis | 84.3% | – |
| Startrise Frontend | Startrise | – | 75.9%† |
| GameBench 2 Overall | DuelLab GameBench 2 | 55.2 | 63.4† |
| GameBench 2 by reasoning setting | DuelLab GameBench 2 | 57.5† | 71.5 |
| FrontierCode 1.1 (AA) | Artificial Analysis | 41.0% | 33.8% |
| FrontierCode 2.0 (AA) | Artificial Analysis | 17.6% | 28.7% |
| Agents & tools | |||
| Terminal-Bench | Terminal-Bench | 35.8%† | 37.6% |
| APEX-Agents | Mercor | 52.8% | 54.6%† |
| Arena Agent | Arena (LMArena) | -2.4 | 2.7 |
| LiveBench Long Agentic | LiveBench | 19.0% | 46.1%† |
| LiveBench Browser | LiveBench | 59.8% | 49.3%† |
| LiveBench Agentic Coding | LiveBench | 56.8% | 54.0% |
| Terminal-Bench 2.1 (Vals) | Vals AI | 62.9%† | 73.4% |
| GDPval-AA v2.1, normalised score | Artificial Analysis | 57.1% | 60.7% |
| GDPval-AA v2.1 | Artificial Analysis | 1649 | 1718 |
| τ³-Banking (AA) | Artificial Analysis | 47.2% | – |
| ITBench SRE (AA) | Artificial Analysis | 51.2% | 42.1% |
| Analyst Agent (AA) | Artificial Analysis | 25.0% | 52.5% |
| CyberBench | Vals AI | 67.9%† | 69.5% |
| Finance Agent v2 | Vals AI | 57.9%† | 52.3% |
| Finance Agent v2.1 | Vals AI | 60.6%† | 60.6% |
| Harvey's Legal Agent Benchmark v1.1 | Vals AI | 10.4%† | 18.3% |
| Harvey's Legal Agent Benchmark v1 | Vals AI | 6.7%† | 12.5% |
| Legal Research Bench | Vals AI | 45.2%† | 47.1% |
| Robo-bench | Vals AI | – | 0.2% |
| SkillsBench | Vals AI | 40.2%† | – |
| SREBench | Vals AI | 0.8%† | 3.8% |
| Tax Agent Bench | Vals AI | 31.6%† | 34.2% |
| Terminal-Bench 4.0 (Vals) | Vals AI | 37.4%† | 28.8% |
| Terminal-Bench Science | Vals AI | 2.9%† | 10.0% |
| Vending-Bench 2 | Andon Labs | – | 10536.8† |
| AutomationBench | Artificial Analysis | 60.4% | 65.6% |
| GDP.pdf (AA) | Artificial Analysis | 15.4% | 20.0% |
| Harvey LAB-AA v1.1 | Harvey | 0.8% | 9.4% |
| EnterpriseOps-Gym | Artificial Analysis | 33.2% | – |
| AA-Briefcase v1.1 | Artificial Analysis | 1451 | 1637 |
| GDPx | GDPx by SemiAnalysis | – | 3.9% |
| Terminal-Bench-Science 0.1 (AA) | Artificial Analysis | 4.8% | 11.4% |
| CWE-Bench (AA) | Artificial Analysis | 55.8% | 68.3% |
| DeepSec-Bench (AA) | Artificial Analysis | 19.9% | 26.9% |
| CyberGym end-to-end (AA) | Artificial Analysis | 74.0% | 74.0% |
| Maths | |||
| FrontierMath Tiers 1–3 | Epoch AI Benchmarking Hub | 55.8%† | 53.0% |
| FrontierMath Tier 4 | Epoch AI Benchmarking Hub | 17.1%† | 17.1% |
| OTIS Mock AIME | Epoch AI Benchmarking Hub | 93.9%† | 98.1% |
| ProofBench | Vals AI | 21.0%† | 26.0%† |
| LiveBench Mathematics | LiveBench | 81.2% | 95.7% |
| Arena Maths | Arena (LMArena) | 1503 | 1443 |
| Knowledge | |||
| SimpleQA Verified | Epoch AI Benchmarking Hub | – | 56.0% |
| LiveBench 2.0 Data Analysis | LiveBench | 76.4% | 76.9%† |
| LiveBench Research | LiveBench | 70.1% | 86.4%† |
| LiveBench 1.0 Data Analysis | LiveBench | 76.4% | 76.9% |
| AA-Omniscience v1.1 | Artificial Analysis | 0.7 | 31.2 |
| MMLU-Pro | Vals AI | 86.1%† | – |
| LegalBench | Vals AI | 83.9%† | 84.4% |
| TaxEval | Vals AI | 75.6%† | – |
| PRBench Legal | Scale AI SEAL | – | 47.6% |
| BioMysteryBench | Vals AI | – | 69.3% |
| Excel Modeling Benchmark | Vals AI | 55.9%† | 67.0% |
| Excel Modeling Benchmark v1.1 | Vals AI | 66.3%† | 71.5% |
| MedCode | Vals AI | – | 49.5% |
| MedScribe | Vals AI | 88.9%† | 89.4% |
| Public Benefits Bench v1.1 | Vals AI | – | 65.6% |
| GDP.pdf | Epoch AI Benchmarking Hub | 14.0%† | 22.8% |
| AA-Omniscience v1.1: accuracy | Artificial Analysis | 28.2% | 42.7% |
| AA-Omniscience v1.1: non-hallucination | Artificial Analysis | 61.6% | 80.0% |
| HealthBench Professional (AA) | OpenAI | – | 55.8% |
| Instruction following | |||
| LiveBench Language | LiveBench | 77.3% | 80.1% |
| LiveBench Instruction Following | LiveBench | 52.8% | 75.3% |
| Arena Instruction Following | Arena (LMArena) | 1474 | 1438 |
| Human preference | |||
| Arena Text | Arena (LMArena) | 1477 | 1441 |
| Arena Creative Writing | Arena (LMArena) | 1434 | 1419 |
| Arena Multi-turn | Arena (LMArena) | 1476 | 1432 |
| Arena Longer Queries | Arena (LMArena) | 1482 | 1452 |
| Multimodal | |||
| Arena Vision | Arena (LMArena) | 1294 | 1231 |
| LiveBench Design | LiveBench | 77.2% | 78.0%† |
| MMMU-Pro | Artificial Analysis | – | 78.2%† |
| MMMU-Pro (Vals) | Vals AI | 86.0%† | – |
| SAGE | Vals AI | 89.3%† | 88.7% |
| Blueprint-Bench 2 | Epoch AI Benchmarking Hub | – | 32.5%† |
| Code2Video-AA | Artificial Analysis | 975 | 1127 |
| AA-3D | Artificial Analysis | 937 | 995 |
| Long context | |||
| AA-LCR v1.1 | Artificial Analysis | 80.0% | 76.7% |
| MLCR | Artificial Analysis | 11.7% | 20.0% |
| Composite | |||
| Epoch Capabilities Index | Epoch AI Benchmarking Hub | 153.6 | 156.1† |
| LiveBench 2.0 | LiveBench | 62.1% | 70.1%† |
| LiveBench 1.0 | LiveBench | 71.6% | 77.4% |
| AA Intelligence Index v5.0 | Artificial Analysis | 27.8 | 35.5 |
| AA Intelligence Index v4.3.2 | Artificial Analysis | 41.8 | 46.5 |
| AA Progress Index v1 | Artificial Analysis | 318.6 | 322.7 |
| Vals Index | Vals AI | 50.9† | 58.6 |
| Vals Finance Index | Vals AI | 55.8%† | 58.5% |
| Vals RSI Index | Vals AI | – | 20.2% |
| Vals Science Index | Vals AI | – | 34.8% |
| Vals Router Index | Vals AI | 50.9% | 58.6%† |
| AA Cyber Index | Artificial Analysis | 49.9 | 56.4 |
| Safety & honesty | |||
| FORTRESS | Scale AI SEAL | 26.7% | – |
| Metadata | |||
| AA Openness Index | Artificial Analysis | 44.4 | – |
Data as of 2026-11-06. Best configuration of each model; every score links to its source on the model pages.
DuelLab GameBench 2, release gb2-20261103-09b2218cbd85 (https://benchmarks.duellab.org/releases/gb2-20261103-09b2218cbd85/), CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). Scores mapped to BenchLeader model names; not endorsed by DuelLab.
What changed
- GLM 5.3 Flash: 1 new result (FORTRESS).
- GLM 5.3 Flash: 2 score revisions; GLM 5.3 Flash cached input price moved from $0.034/M to $0.030/M (13% down).
- Grok 4.7 (xhigh): 2 score revisions.
- GLM 5.3 Flash: GLM 5.3 Flash cached input price moved from $0.030/M to $0.034/M (15% up).
- Grok 4.7 (xhigh): 2 score revisions.
- GLM 5.3 Flash: GLM 5.3 Flash cached input price moved from $0.034/M to $0.030/M (13% down).
- GLM 5.3 Flash: GLM 5.3 Flash cached input price moved from $0.030/M to $0.034/M (15% up).
- GLM 5.3 Flash: BenchLeader Index 57.6 → 56.7.
- GLM 5.3 Flash: 2 new results (AA Intelligence Index v5.0, FrontierCode 2.0 (AA)).
- GLM 5.3 Flash: 1 new result (CritPt v2 hard subset (AA)); 1 score revision.
Related comparisons
- GLM 5.3 Flash vs GPT-6.1 Sol
- GLM 5.3 Flash vs Gemini 4 Argon
- GLM 5.3 Flash vs Claude Sonnet 5.5
- Grok 4.7 vs Gemini 4 Argon
- Grok 4.7 vs GPT-6.1 Terra
- Grok 4.7 vs Claude Opus 4.7
- Grok 4.7 vs GPT-5.3-Codex
- Grok 4.7 vs Muse Spark 1.3
Rankings: Best LLM overall · Best LLM for agents · Best cheap LLMs
GLM 5.3 Flash vs Grok 4.7: questions
- Is GLM 5.3 Flash better than Grok 4.7?
- GLM 5.3 Flash and Grok 4.7 (xhigh) are neck and neck on quality (56.8 vs 58.3, within the ±5.2 margin). The BenchLeader Index combines every independent quality benchmark; the two are within the margin of error as of 6 Nov 2026, so check the category scores for your use.
- GLM 5.3 Flash vs Grok 4.7: which is cheaper, and will that change?
- GLM 5.3 Flash is cheaper today: $0.238 against $3.00 per million tokens, blended at three input tokens per output token. No price change has been announced for either.
- Is GLM 5.3 Flash or Grok 4.7 better for coding?
- Grok 4.7 scores higher in coding (62 vs 57 on the category index, where 50 is average). On Arena WebDev, the top shared coding benchmark, it is 1607 for GLM 5.3 Flash against 1638 for Grok 4.7.
- Which is faster, GLM 5.3 Flash or Grok 4.7?
- Grok 4.7 streams faster (71 vs 56 output tokens per second, Artificial Analysis 7-day median).
- Is GLM 5.3 Flash or Grok 4.7 better for agents and tool use?
- GLM 5.3 Flash scores higher in agentic tasks (60 vs 57 on the category index, where 50 is average). On Arena Agent, the top shared agents & tools benchmark, it is -2.4 for GLM 5.3 Flash against 2.7 for Grok 4.7.
More questions (4)
- Which is better for long documents?
- GLM 5.3 Flash scores higher on long-context benchmarks (65 vs 63). GLM 5.3 Flash accepts more context: 1,000,000 against 500,000 tokens for Grok 4.7.
- Which has lower latency?
- Grok 4.7 answers first: 55.1 s against 99.0 s to the first answer token, as Artificial Analysis measures it. Reasoning effort drives most of this: a higher setting thinks longer before it answers.
- Do independent benchmarks agree on GLM 5.3 Flash vs Grok 4.7?
- Across the 47 benchmarks both have, GLM 5.3 Flash leads 14, Grok 4.7 leads 32 and 1 is a tie. Independent sources split: GLM 5.3 Flash leads on Arena Text; Grok 4.7 leads on AA Intelligence Index v5.0 and Vals Index.
- When was Grok 4.7 released?
- Grok 4.7 was released on 21 Sep 2026.