# GPT-5 Nano vs Grok 4.20 Multi-Agent

> Grok 4.20 Multi-Agent is the stronger model overall, scoring 46.2 to 33.5 on the Noometry Index. GPT-5 Nano costs 11× less per token, which makes it the better buy when Grok 4.20 Multi-Agent's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/gpt-5-nano-vs-grok-4-20-multi-agent
- Last updated: 2026-10-12
- Shared benchmarks: 17

## Summary

- They share 17 benchmarks with published results for both. GPT-5 Nano scores higher in 1 category and Grok 4.20 Multi-Agent in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Grok 4.20 Multi-Agent leads 43.9 to 16.3.
- GPT-5 Nano is cheaper at $0.05 / $0.40 per million input/output tokens, against $1.25 / $2.50 for Grok 4.20 Multi-Agent.
- Grok 4.20 Multi-Agent accepts more context: 1M tokens versus 400K.

## Snapshot

| | GPT-5 Nano | Grok 4.20 Multi-Agent |
|---|---|---|
| Provider | OpenAI | xAI |
| Noometry Index | 33.5 | 46.2 |
| Rank | 241 | 65 |
| Context | 400K | 1M |
| Input $/M | $0.05 | $1.25 |
| Output $/M | $0.40 | $2.50 |
| Weights | Proprietary | Proprietary |

## Coding

- GPT-5 Nano: 33.6 (#254)
- Grok 4.20 Multi-Agent: 43.0 (#92)

| Benchmark | GPT-5 Nano | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Coding | 1351 | 1457 |
| SWE-bench Verified (bash only) | 34.8% | — |
| WeirdML | 38.1% | — |
| ALE-Bench | 718.67 | — |

## Agentic & Tool Use

- GPT-5 Nano: 25.8 (#106)
- Grok 4.20 Multi-Agent: —

| Benchmark | GPT-5 Nano | Grok 4.20 Multi-Agent |
|---|---|---|
| Terminal-Bench | 21.8% | — |
| Berkeley Function Calling Leaderboard | 51.5% | — |
| LMArena Search | — | 1204 |

## Reasoning

- GPT-5 Nano: 16.3 (#306)
- Grok 4.20 Multi-Agent: 43.9 (#48)

| Benchmark | GPT-5 Nano | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Hard Prompts | 1328 | 1448 |
| ARC-AGI-2 | 2.6% | — |
| Kagi LLM Benchmark | 62.2% | — |
| NYT Connections (extended) | — | 89.6% |
| ARC-AGI-1 | 20.7% | — |
| Chess Puzzles | 27% | — |
| Mystery Game Puzzles | 9% | — |
| DTBench | 62.7% | — |
| LMCA | 7.9% | — |
| Epoch Capabilities Index | 139.38 | — |
| ForecastBench | 59.1 | — |

## Math

- GPT-5 Nano: 29.4 (#241)
- Grok 4.20 Multi-Agent: 39.4 (#104)

| Benchmark | GPT-5 Nano | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Math | 1317 | 1442 |
| FrontierMath (Tiers 1-3) | 20% | — |
| FrontierMath Tier 4 | 2.4% | — |
| OTIS Mock AIME 2024-2025 | 81.1% | — |
| ProofBench | 12% | — |
| Omni-MATH | 54.6% | — |
| MATH Level 5 | 95.2% | — |
| FrontierMath (Feb 2025 set) | 8.3% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |

## Knowledge

- GPT-5 Nano: 35.9 (#178)
- Grok 4.20 Multi-Agent: 40.4 (#119)

| Benchmark | GPT-5 Nano | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Expert | 1321 | 1445 |
| GPQA Diamond | 69.4% | — |
| SimpleQA Verified | 11.7% | — |
| MMLU-Pro | 77.8% | — |
| Vectara Hallucination Rate | 10.5% | — |
| GPQA (HELM) | 67.9% | — |

## Multimodal

- GPT-5 Nano: 31.3 (#108)
- Grok 4.20 Multi-Agent: 40.5 (#48)

| Benchmark | GPT-5 Nano | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Vision | 1159 | 1259 |
| VPCT | 37.2% | — |

## Multilingual

- GPT-5 Nano: 45.3 (#172)
- Grok 4.20 Multi-Agent: 54.4 (#43)

| Benchmark | GPT-5 Nano | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Non-English | 1313 | 1440 |
| LMArena Chinese | 1356 | 1475 |
| LMArena German | 1327 | 1456 |
| LMArena Japanese | 1226 | 1405 |
| LMArena Korean | 1269 | 1416 |
| LMArena Russian | 1296 | 1457 |
| LMArena Spanish | 1360 | 1447 |
| LMArena French | — | 1466 |

## Instruction Following

- GPT-5 Nano: 75.0 (#79)
- Grok 4.20 Multi-Agent: 74.8 (#84)

| Benchmark | GPT-5 Nano | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Instruction Following | 1306 | 1420 |
| IFEval | 93.2% | — |

## Long Context

- GPT-5 Nano: 31.3 (#281)
- Grok 4.20 Multi-Agent: 43.7 (#88)

| Benchmark | GPT-5 Nano | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Longer Query | 1312 | 1431 |
| Fiction.LiveBench | 44.4% | — |

## Writing & Preference

- GPT-5 Nano: 39.1 (#249)
- Grok 4.20 Multi-Agent: 64.0 (#59)

| Benchmark | GPT-5 Nano | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Text | 1320 | 1450 |
| LMArena Creative Writing | 1249 | 1436 |
| LMArena Multi-Turn | 1311 | 1452 |
| EQ-Bench Creative Writing | 705 | — |
| WildBench | 80.6% | — |

## FAQ

### Is GPT-5 Nano better than Grok 4.20 Multi-Agent?

Grok 4.20 Multi-Agent is the stronger model overall, scoring 46.2 to 33.5 on the Noometry Index. GPT-5 Nano costs 11× less per token, which makes it the better buy when Grok 4.20 Multi-Agent's lead doesn't matter for your workload.

### Which is cheaper, GPT-5 Nano or Grok 4.20 Multi-Agent?

GPT-5 Nano is cheaper. It lists at $0.05 per million input tokens and $0.40 per million output tokens; Grok 4.20 Multi-Agent lists at $1.25 and $2.50.

### Is GPT-5 Nano or Grok 4.20 Multi-Agent better for coding?

Grok 4.20 Multi-Agent scores higher on coding benchmarks: 43.0 versus 33.6 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 Nano and Grok 4.20 Multi-Agent share?

17 benchmarks have published results for both models. GPT-5 Nano has 49 scored results on Noometry and Grok 4.20 Multi-Agent has 20.