Model comparison
GPT-5.2 vs Grok 4.1 Fast
GPT-5.2 is the stronger model overall, scoring 54.1 to 40.9 on the Noometry Index. Grok 4.1 Fast costs 18× less per token, which makes it the better buy when GPT-5.2's lead doesn't matter for your workload.
Last verified . 32 shared benchmarks.
Summary
- They share 32 benchmarks with published results for both. GPT-5.2 scores higher in 10 categories and Grok 4.1 Fast in 0 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5.2 leads 59.8 to 30.9.
- The biggest single-benchmark swing is τ²-bench Banking: 32.2% for GPT-5.2 and 13.1% for Grok 4.1 Fast.
- Grok 4.1 Fast is cheaper at $0.20 / $0.50 per million input/output tokens, against $1.75 / $14 for GPT-5.2.
- GPT-5.2 accepts more context: 400K tokens versus 128K.
Side by side
| GPT-5.2 | Grok 4.1 Fast | |
|---|---|---|
| Provider | OpenAI | xAI |
| Noometry Index | 54.1 | 40.9 |
| Released | 2025-12-11 | 2025-06-27 |
| Weights | Proprietary | Proprietary |
| Context window | 400K | 128K |
| Max output | 128K | 30K |
| Input $ / M tokens | $1.75 | $0.20 |
| Output $ / M tokens | $14 | $0.50 |
| Results tracked | 67 | 32 |
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Category by category
Coding GPT-5.2 leads
GPT-5.2: 52.2 (#32), Grok 4.1 Fast: 33.8 (#236)
| Benchmark | GPT-5.2 | Grok 4.1 Fast |
|---|---|---|
| LMArena WebDev | 1415 | 1241 |
| LMArena Coding | 1447 | 1411 |
| ALE-Bench | 1,294 | 394.93 |
| SWE-bench Verified | 73.8% | — |
| SWE-bench Verified (bash only) | 72.8% | — |
| SWE-bench Multilingual | 66.7% | — |
| GSO | 27.4% | — |
| WeirdML | 72.2% | — |
| AlgoTune | 2.05 | — |
Agentic & Tool Use GPT-5.2 leads
GPT-5.2: 40.0 (#24), Grok 4.1 Fast: 36.1 (#35)
| Benchmark | GPT-5.2 | Grok 4.1 Fast |
|---|---|---|
| Berkeley Function Calling Leaderboard | 55.9% | 69.6% |
| τ²-bench Banking | 32.2% | 13.1% |
| LMArena Search | 1207 | 1171 |
| Vending-Bench 2 | 3,591 | 1,107 |
| Terminal-Bench | 64.9% | — |
| GDPval | 49.7% | — |
| Remote Labor Index | 2.5% | — |
| τ²-bench Airline | 83% | — |
| τ²-bench Retail | 81.6% | — |
| τ²-bench Telecom | 89.7% | — |
| DeepResearch Bench | 41.1% | — |
| METR Time Horizons | 75.3% | — |
Reasoning GPT-5.2 leads
GPT-5.2: 50.1 (#33), Grok 4.1 Fast: 42.3 (#45)
| Benchmark | GPT-5.2 | Grok 4.1 Fast |
|---|---|---|
| SimpleBench | 45.8% | 56% |
| NYT Connections (extended) | 83.6% | 87.4% |
| LMArena Hard Prompts | 1445 | 1407 |
| DTBench | 90.9% | 87.7% |
| ForecastBench | 60.1 | 61 |
| ARC-AGI-2 | 52.9% | — |
| Kagi LLM Benchmark | 73.3% | — |
| ARC-AGI-1 | 86.2% | — |
| Chess Puzzles | 49% | — |
| EnigmaEval | 10.4% | — |
| EBR-Bench | 23% | — |
| Mystery Game Puzzles | 23% | — |
| LMCA | 43.9% | — |
| Epoch Capabilities Index | 153.45 | — |
Math GPT-5.2 leads
GPT-5.2: 59.8 (#32), Grok 4.1 Fast: 30.9 (#201)
| Benchmark | GPT-5.2 | Grok 4.1 Fast |
|---|---|---|
| MathArena Final-Answer Competitions | 72% | 60.9% |
| ProofBench | 15% | 4% |
| LMArena Math | 1439 | 1408 |
| FrontierMath (Tiers 1-3) | 67.4% | — |
| FrontierMath Tier 4 | 31.7% | — |
| OTIS Mock AIME 2024-2025 | 96.1% | — |
| FrontierMath (Feb 2025 set) | 40.7% | — |
| FrontierMath Tier 4 (v1) | 18.8% | — |
Knowledge GPT-5.2 leads
GPT-5.2: 59.2 (#29), Grok 4.1 Fast: 32.6 (#203)
| Benchmark | GPT-5.2 | Grok 4.1 Fast |
|---|---|---|
| Vectara Hallucination Rate | 8.4% | 17.8% |
| LMArena Expert | 1445 | 1398 |
| GPQA Diamond | 91.4% | — |
| Humanity's Last Exam | 27.8% | — |
| SimpleQA Verified | 37.1% | — |
Multimodal GPT-5.2 leads
GPT-5.2: 50.9 (#7), Grok 4.1 Fast: 36.3 (#71)
| Benchmark | GPT-5.2 | Grok 4.1 Fast |
|---|---|---|
| LMArena Vision | 1268 | 1201 |
| VPCT | 84% | — |
| Furniture Assembly | 38.3% | — |
| LMArena Document | 1405 | — |
Multilingual GPT-5.2 leads
GPT-5.2: 53.6 (#63), Grok 4.1 Fast: 51.1 (#110)
| Benchmark | GPT-5.2 | Grok 4.1 Fast |
|---|---|---|
| LMArena Non-English | 1425 | 1391 |
| LMArena Chinese | 1460 | 1441 |
| LMArena French | 1456 | 1416 |
| LMArena German | 1448 | 1404 |
| LMArena Japanese | 1421 | 1347 |
| LMArena Korean | 1390 | 1361 |
| LMArena Russian | 1440 | 1387 |
| LMArena Spanish | 1433 | 1411 |
Instruction Following GPT-5.2 leads
GPT-5.2: 74.9 (#83), Grok 4.1 Fast: 72.8 (#127)
| Benchmark | GPT-5.2 | Grok 4.1 Fast |
|---|---|---|
| LMArena Instruction Following | 1417 | 1376 |
Long Context GPT-5.2 leads
GPT-5.2: 44.0 (#74), Grok 4.1 Fast: 42.4 (#121)
| Benchmark | GPT-5.2 | Grok 4.1 Fast |
|---|---|---|
| LMArena Longer Query | 1428 | 1390 |
| CL-bench | 18.2% | — |
Writing & Preference GPT-5.2 leads
GPT-5.2: 67.0 (#30), Grok 4.1 Fast: 57.4 (#126)
| Benchmark | GPT-5.2 | Grok 4.1 Fast |
|---|---|---|
| LMArena Text | 1439 | 1408 |
| LMArena Creative Writing | 1402 | 1394 |
| EQ-Bench Creative Writing | 1703 | 1327 |
| LMArena Multi-Turn | 1458 | 1389 |
Frequently asked questions
Is GPT-5.2 better than Grok 4.1 Fast?
GPT-5.2 is the stronger model overall, scoring 54.1 to 40.9 on the Noometry Index. Grok 4.1 Fast costs 18× less per token, which makes it the better buy when GPT-5.2's lead doesn't matter for your workload.
Which is cheaper, GPT-5.2 or Grok 4.1 Fast?
Grok 4.1 Fast is cheaper. It lists at $0.20 per million input tokens and $0.50 per million output tokens; GPT-5.2 lists at $1.75 and $14.
Is GPT-5.2 or Grok 4.1 Fast better for coding?
GPT-5.2 scores higher on coding benchmarks: 52.2 versus 33.8 in the Noometry coding category.
Which has the bigger context window?
GPT-5.2 does, with 400K tokens against 128K.
How many benchmarks do GPT-5.2 and Grok 4.1 Fast share?
32 benchmarks have published results for both models. GPT-5.2 has 67 scored results on Noometry and Grok 4.1 Fast has 32.