Model comparison
GPT-5 Nano vs Grok 4.20 Multi-Agent
Grok 4.20 Multi-Agent is the stronger model overall, scoring 45.5 to 33.4 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.
Last verified . 16 shared benchmarks.
Summary
- They share 16 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 42.4 to 16.4.
- 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.
Side by side
| GPT-5 Nano | Grok 4.20 Multi-Agent | |
|---|---|---|
| Provider | OpenAI | xAI |
| Noometry Index | 33.4 | 45.5 |
| Released | 2025-08-07 | 2026-03-09 |
| Weights | Proprietary | Proprietary |
| Context window | 400K | 1M |
| Max output | 128K | 30K |
| Input $ / M tokens | $0.05 | $1.25 |
| Output $ / M tokens | $0.40 | $2.50 |
| Results tracked | 48 | 20 |
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Category by category
Coding Grok 4.20 Multi-Agent leads
GPT-5 Nano: 33.3 (#248), Grok 4.20 Multi-Agent: 42.4 (#91)
| Benchmark | GPT-5 Nano | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Coding | 1351 | 1458 |
| SWE-bench Verified (bash only) | 34.8% | — |
| WeirdML | 38.1% | — |
| ALE-Bench | 718.67 | — |
Agentic & Tool Use Not comparable
GPT-5 Nano: 25.6 (#99), 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 Grok 4.20 Multi-Agent leads
GPT-5 Nano: 16.4 (#291), Grok 4.20 Multi-Agent: 42.4 (#44)
| Benchmark | GPT-5 Nano | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Hard Prompts | 1329 | 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 | 139.39 | — |
| ForecastBench | 59.1 | — |
Math Grok 4.20 Multi-Agent leads
GPT-5 Nano: 29.1 (#221), Grok 4.20 Multi-Agent: 36.6 (#106)
| Benchmark | GPT-5 Nano | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Math | 1318 | 1441 |
| 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 Grok 4.20 Multi-Agent leads
GPT-5 Nano: 35.8 (#166), Grok 4.20 Multi-Agent: 39.7 (#116)
| 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 Grok 4.20 Multi-Agent leads
GPT-5 Nano: 30.7 (#102), Grok 4.20 Multi-Agent: 39.8 (#44)
| Benchmark | GPT-5 Nano | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Vision | 1159 | 1259 |
| VPCT | 37.2% | — |
Multilingual Grok 4.20 Multi-Agent leads
GPT-5 Nano: 45.5 (#167), Grok 4.20 Multi-Agent: 54.6 (#40)
| Benchmark | GPT-5 Nano | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Non-English | 1313 | 1440 |
| LMArena Chinese | 1355 | 1475 |
| LMArena German | 1329 | 1456 |
| LMArena Korean | 1269 | 1416 |
| LMArena Russian | 1296 | 1457 |
| LMArena Spanish | 1360 | 1447 |
| LMArena French | — | 1467 |
| LMArena Japanese | — | 1405 |
Instruction Following Too close to call
GPT-5 Nano: 75.2 (#72), Grok 4.20 Multi-Agent: 75.0 (#80)
| Benchmark | GPT-5 Nano | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Instruction Following | 1306 | 1420 |
| IFEval | 93.2% | — |
Long Context Grok 4.20 Multi-Agent leads
GPT-5 Nano: 31.3 (#275), Grok 4.20 Multi-Agent: 43.7 (#84)
| Benchmark | GPT-5 Nano | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Longer Query | 1313 | 1430 |
| Fiction.LiveBench | 44.4% | — |
Writing & Preference Grok 4.20 Multi-Agent leads
GPT-5 Nano: 39.4 (#244), Grok 4.20 Multi-Agent: 64.1 (#57)
| Benchmark | GPT-5 Nano | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Text | 1320 | 1450 |
| LMArena Creative Writing | 1250 | 1435 |
| LMArena Multi-Turn | 1311 | 1451 |
| EQ-Bench Creative Writing | 705 | — |
| WildBench | 80.6% | — |
Frequently asked questions
Is GPT-5 Nano better than Grok 4.20 Multi-Agent?
Grok 4.20 Multi-Agent is the stronger model overall, scoring 45.5 to 33.4 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: 42.4 versus 33.3 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?
16 benchmarks have published results for both models. GPT-5 Nano has 48 scored results on Noometry and Grok 4.20 Multi-Agent has 20.