Model comparison
GPT-5.4 vs Grok 4.7
GPT-5.4 is the stronger model overall, scoring 59.5 to 46.6 on the Noometry Index. Grok 4.7 costs 1.9× less per token, which makes it the better buy when GPT-5.4's lead doesn't matter for your workload.
Last verified . 19 shared benchmarks.
Summary
- They share 19 benchmarks with published results for both. GPT-5.4 scores higher in 8 categories and Grok 4.7 in 1 category; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5.4 leads 73.3 to 41.1.
- The biggest single-benchmark swing is ProofBench: 56% for GPT-5.4 and 34% for Grok 4.7.
- Grok 4.7 is cheaper at $2 / $6 per million input/output tokens, against $2.50 / $15 for GPT-5.4.
- GPT-5.4 accepts more context: 1.05M tokens versus 500K.
Side by side
| GPT-5.4 | Grok 4.7 | |
|---|---|---|
| Provider | OpenAI | xAI |
| Noometry Index | 59.5 | 46.6 |
| Released | 2026-03-05 | 2026-09-21 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 500K |
| Max output | 128K | 500K |
| Input $ / M tokens | $2.50 | $2 |
| Output $ / M tokens | $15 | $6 |
| Results tracked | 68 | 21 |
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Category by category
Coding Grok 4.7 leads
GPT-5.4: 52.8 (#28), Grok 4.7: 55.0 (#23)
| Benchmark | GPT-5.4 | Grok 4.7 |
|---|---|---|
| LMArena WebDev | 1465 | 1636 |
| SciCode | 56.6% | 57.4% |
| LMArena Coding | 1497 | 1423 |
| SWE-bench Verified | 76.9% | — |
| DeepSWE | 51.8% | — |
| CursorBench | — | 46.3% |
| FrontierSWE | — | 29.5% |
| GSO | 31.4% | — |
| WeirdML | 77.7% | — |
| MirrorCode | 15.6% | — |
| ALE-Bench | 1,607 | — |
| AlgoTune | 1.85 | — |
Agentic & Tool Use Not comparable
GPT-5.4: 46.5 (#12), Grok 4.7: —
| Benchmark | GPT-5.4 | Grok 4.7 |
|---|---|---|
| Terminal-Bench | 81.8% | — |
| APEX-Agents | 52.4% | — |
| τ²-bench Banking | 39.4% | — |
| DeepResearch Bench | 35.1% | — |
| PostTrainBench | 19% | — |
| GBAEval | 45.1% | — |
| LMArena Search | 1197 | — |
| METR Time Horizons | 74.3% | — |
| Vending-Bench 2 | 6,144 | — |
Reasoning GPT-5.4 leads
GPT-5.4: 61.7 (#17), Grok 4.7: 40.1 (#49)
| Benchmark | GPT-5.4 | Grok 4.7 |
|---|---|---|
| NYT Connections (extended) | 91.3% | 76.8% |
| CritPt | 23.4% | 17.7% |
| LMArena Hard Prompts | 1485 | 1409 |
| ARC-AGI-2 | 74% | — |
| Kagi LLM Benchmark | 63.8% | — |
| ARC-AGI-1 | 93.7% | — |
| Chess Puzzles | 44% | — |
| EnigmaEval | 16% | — |
| Thematic Generalization | 80% | — |
| EBR-Bench | 25.4% | — |
| Mystery Game Puzzles | 37% | — |
| DTBench | 94.4% | — |
| LMCA | 52% | — |
| Epoch Capabilities Index | 156.92 | — |
| ForecastBench | 59.5 | — |
Math GPT-5.4 leads
GPT-5.4: 73.3 (#14), Grok 4.7: 41.1 (#73)
| Benchmark | GPT-5.4 | Grok 4.7 |
|---|---|---|
| ProofBench | 56% | 34% |
| LMArena Math | 1488 | 1393 |
| FrontierMath (Tiers 1-3) | 78.6% | — |
| FrontierMath Tier 4 | 49% | — |
| MathArena Final-Answer Competitions | 83.1% | — |
| OTIS Mock AIME 2024-2025 | 97.8% | — |
| FrontierMath (Feb 2025 set) | 47.6% | — |
| FrontierMath Tier 4 (v1) | 27.1% | — |
Knowledge GPT-5.4 leads
GPT-5.4: 65.3 (#13), Grok 4.7: 38.7 (#130)
| Benchmark | GPT-5.4 | Grok 4.7 |
|---|---|---|
| LMArena Expert | 1507 | 1413 |
| GPQA Diamond | 93.3% | — |
| Humanity's Last Exam | 36.2% | — |
| SimpleQA Verified | 45.1% | — |
| Vectara Hallucination Rate | 7% | — |
Multimodal GPT-5.4 leads
GPT-5.4: 43.8 (#19), Grok 4.7: 28.8 (#107)
| Benchmark | GPT-5.4 | Grok 4.7 |
|---|---|---|
| Furniture Assembly | 37.5% | 20.8% |
| LMArena Vision | 1302 | — |
| Blueprint-Bench 2 | 27.1% | — |
| LMArena Document | 1471 | — |
Multilingual GPT-5.4 leads
GPT-5.4: 56.4 (#22), Grok 4.7: 51.2 (#108)
| Benchmark | GPT-5.4 | Grok 4.7 |
|---|---|---|
| LMArena Non-English | 1465 | 1392 |
| LMArena Chinese | 1520 | 1476 |
| LMArena Russian | 1480 | 1396 |
| LMArena French | 1493 | — |
| LMArena German | 1472 | — |
| LMArena Japanese | 1484 | — |
| LMArena Korean | 1449 | — |
| LMArena Spanish | 1453 | — |
Instruction Following GPT-5.4 leads
GPT-5.4: 77.3 (#25), Grok 4.7: 74.3 (#98)
| Benchmark | GPT-5.4 | Grok 4.7 |
|---|---|---|
| LMArena Instruction Following | 1469 | 1406 |
Long Context GPT-5.4 leads
GPT-5.4: 50.3 (#8), Grok 4.7: 43.2 (#97)
| Benchmark | GPT-5.4 | Grok 4.7 |
|---|---|---|
| LMArena Longer Query | 1474 | 1416 |
| CL-bench | 27.9% | — |
| CL-bench Life | 21.7% | — |
Writing & Preference GPT-5.4 leads
GPT-5.4: 72.1 (#18), Grok 4.7: 70.1 (#23)
| Benchmark | GPT-5.4 | Grok 4.7 |
|---|---|---|
| LMArena Text | 1469 | 1397 |
| LMArena Creative Writing | 1439 | 1391 |
| EQ-Bench Creative Writing | 1840 | 2007 |
| LMArena Multi-Turn | 1482 | 1389 |
| EQ-Bench 4 | 1272 | — |
Frequently asked questions
Is GPT-5.4 better than Grok 4.7?
GPT-5.4 is the stronger model overall, scoring 59.5 to 46.6 on the Noometry Index. Grok 4.7 costs 1.9× less per token, which makes it the better buy when GPT-5.4's lead doesn't matter for your workload.
Which is cheaper, GPT-5.4 or Grok 4.7?
Grok 4.7 is cheaper. It lists at $2 per million input tokens and $6 per million output tokens; GPT-5.4 lists at $2.50 and $15.
Is GPT-5.4 or Grok 4.7 better for coding?
Grok 4.7 scores higher on coding benchmarks: 55.0 versus 52.8 in the Noometry coding category.
Which has the bigger context window?
GPT-5.4 does, with 1.05M tokens against 500K.
How many benchmarks do GPT-5.4 and Grok 4.7 share?
19 benchmarks have published results for both models. GPT-5.4 has 68 scored results on Noometry and Grok 4.7 has 21.