Model comparison
GPT-5.1 vs Grok 4.20 Multi-Agent
GPT-5.1 is the stronger model overall, scoring 49.0 to 46.2 on the Noometry Index. Grok 4.20 Multi-Agent costs 2.2× less per token, which makes it the better buy when GPT-5.1's lead doesn't matter for your workload.
Last verified . 19 shared benchmarks.
Summary
- They share 19 benchmarks with published results for both. GPT-5.1 scores higher in 7 categories and Grok 4.20 Multi-Agent in 2 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5.1 leads 52.2 to 39.4.
- Grok 4.20 Multi-Agent is cheaper at $1.25 / $2.50 per million input/output tokens, against $1.25 / $10 for GPT-5.1.
- Grok 4.20 Multi-Agent accepts more context: 1M tokens versus 400K.
Side by side
| GPT-5.1 | Grok 4.20 Multi-Agent | |
|---|---|---|
| Provider | OpenAI | xAI |
| Noometry Index | 49.0 | 46.2 |
| Released | 2025-11-13 | 2026-03-09 |
| Weights | Proprietary | Proprietary |
| Context window | 400K | 1M |
| Max output | 128K | 30K |
| Input $ / M tokens | $1.25 | $1.25 |
| Output $ / M tokens | $10 | $2.50 |
| Results tracked | 63 | 20 |
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Category by category
Coding GPT-5.1 leads
GPT-5.1: 46.4 (#66), Grok 4.20 Multi-Agent: 43.0 (#92)
| Benchmark | GPT-5.1 | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Coding | 1454 | 1457 |
| SWE-bench Verified | 68% | — |
| SWE-bench Verified (bash only) | 66% | — |
| LMArena WebDev | 1395 | — |
| SciCode | 43.3% | — |
| GSO | 13.7% | — |
| WeirdML | 60.8% | — |
| LiveBench Coding | 72.5% | — |
| ALE-Bench | 1,192 | — |
Agentic & Tool Use Not comparable
GPT-5.1: 32.7 (#60), Grok 4.20 Multi-Agent: —
| Benchmark | GPT-5.1 | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Search | 1199 | 1204 |
| Terminal-Bench | 47.6% | — |
| DeepResearch Bench | 42.8% | — |
| Vending-Bench 2 | 1,473 | — |
Reasoning Grok 4.20 Multi-Agent leads
GPT-5.1: 39.8 (#58), Grok 4.20 Multi-Agent: 43.9 (#48)
| Benchmark | GPT-5.1 | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Hard Prompts | 1457 | 1448 |
| ARC-AGI-2 | 17.6% | — |
| SimpleBench | 53.2% | — |
| NYT Connections (extended) | — | 89.6% |
| ARC-AGI-1 | 72.8% | — |
| CritPt | 4.9% | — |
| Chess Puzzles | 32% | — |
| EnigmaEval | 11.2% | — |
| LiveBench Reasoning | 95.8% | — |
| Mystery Game Puzzles | 19% | — |
| DTBench | 90.1% | — |
| LiveBench Data Analysis | 72.1% | — |
| LMCA | 43.9% | — |
| Epoch Capabilities Index | 149.64 | — |
| ForecastBench | 58.1 | — |
| LiveBench | 78.8% | — |
Math GPT-5.1 leads
GPT-5.1: 52.2 (#51), Grok 4.20 Multi-Agent: 39.4 (#104)
| Benchmark | GPT-5.1 | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Math | 1447 | 1442 |
| OTIS Mock AIME 2024-2025 | 88.6% | — |
| Omni-MATH | 46.4% | — |
| LiveBench Math | 94.5% | — |
| FrontierMath (Feb 2025 set) | 31% | — |
| FrontierMath Tier 4 (v1) | 12.5% | — |
Knowledge GPT-5.1 leads
GPT-5.1: 50.6 (#71), Grok 4.20 Multi-Agent: 40.4 (#119)
| Benchmark | GPT-5.1 | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Expert | 1470 | 1445 |
| GPQA Diamond | 87.6% | — |
| Humanity's Last Exam | 23.7% | — |
| SimpleQA Verified | 48% | — |
| MMLU-Pro | 57.9% | — |
| Vectara Hallucination Rate | 10.9% | — |
| GPQA (HELM) | 44.2% | — |
Multimodal GPT-5.1 leads
GPT-5.1: 44.8 (#19), Grok 4.20 Multi-Agent: 40.5 (#48)
| Benchmark | GPT-5.1 | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Vision | 1250 | 1259 |
| VPCT | 58.7% | — |
| LMArena Document | 1403 | — |
Multilingual Too close to call
GPT-5.1: 53.8 (#56), Grok 4.20 Multi-Agent: 54.4 (#43)
| Benchmark | GPT-5.1 | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Non-English | 1431 | 1440 |
| LMArena Chinese | 1495 | 1475 |
| LMArena French | 1450 | 1466 |
| LMArena German | 1438 | 1456 |
| LMArena Japanese | 1453 | 1405 |
| LMArena Korean | 1401 | 1416 |
| LMArena Russian | 1435 | 1457 |
| LMArena Spanish | 1433 | 1447 |
Instruction Following GPT-5.1 leads
GPT-5.1: 83.9 (#1), Grok 4.20 Multi-Agent: 74.8 (#84)
| Benchmark | GPT-5.1 | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Instruction Following | 1443 | 1420 |
| LiveBench Instruction Following | 93.3% | — |
| IFEval | 93.5% | — |
Long Context GPT-5.1 leads
GPT-5.1: 47.6 (#14), Grok 4.20 Multi-Agent: 43.7 (#88)
| Benchmark | GPT-5.1 | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Longer Query | 1447 | 1431 |
| CL-bench | 23.7% | — |
| CL-bench Life | 17.3% | — |
Writing & Preference Too close to call
GPT-5.1: 64.5 (#55), Grok 4.20 Multi-Agent: 64.0 (#59)
| Benchmark | GPT-5.1 | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Text | 1443 | 1450 |
| LMArena Creative Writing | 1427 | 1436 |
| LMArena Multi-Turn | 1450 | 1452 |
| WildBench | 86.3% | — |
| LiveBench Language | 80.2% | — |
Frequently asked questions
Is GPT-5.1 better than Grok 4.20 Multi-Agent?
GPT-5.1 is the stronger model overall, scoring 49.0 to 46.2 on the Noometry Index. Grok 4.20 Multi-Agent costs 2.2× less per token, which makes it the better buy when GPT-5.1's lead doesn't matter for your workload.
Which is cheaper, GPT-5.1 or Grok 4.20 Multi-Agent?
Grok 4.20 Multi-Agent is cheaper. It lists at $1.25 per million input tokens and $2.50 per million output tokens; GPT-5.1 lists at $1.25 and $10.
Is GPT-5.1 or Grok 4.20 Multi-Agent better for coding?
GPT-5.1 scores higher on coding benchmarks: 46.4 versus 43.0 in the Noometry coding category.
Which has the bigger context window?
Grok 4.20 Multi-Agent does, with 1M tokens against 400K.
How many benchmarks do GPT-5.1 and Grok 4.20 Multi-Agent share?
19 benchmarks have published results for both models. GPT-5.1 has 63 scored results on Noometry and Grok 4.20 Multi-Agent has 20.