Model comparison
GPT-4.1 nano vs Grok 4.5
Grok 4.5 is the stronger model overall, scoring 55.0 to 27.7 on the Noometry Index. GPT-4.1 nano costs 17× less per token, which makes it the better buy when Grok 4.5's lead doesn't matter for your workload.
Last verified . 28 shared benchmarks.
Summary
- They share 28 benchmarks with published results for both. GPT-4.1 nano scores higher in 0 categories and Grok 4.5 in 10 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Grok 4.5 leads 56.0 to 8.6.
- The biggest single-benchmark swing is ARC-AGI-1: 0% for GPT-4.1 nano and 87.2% for Grok 4.5.
- GPT-4.1 nano is cheaper at $0.10 / $0.40 per million input/output tokens, against $2 / $6 for Grok 4.5.
- GPT-4.1 nano accepts more context: 1.05M tokens versus 500K.
Side by side
| GPT-4.1 nano | Grok 4.5 | |
|---|---|---|
| Provider | OpenAI | xAI |
| Noometry Index | 27.7 | 55.0 |
| Released | 2025-04-14 | 2026-07-08 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 500K |
| Max output | 33K | 500K |
| Input $ / M tokens | $0.10 | $2 |
| Output $ / M tokens | $0.40 | $6 |
| Results tracked | 38 | 52 |
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Category by category
Coding Grok 4.5 leads
GPT-4.1 nano: 23.8 (#325), Grok 4.5: 51.7 (#34)
| Benchmark | GPT-4.1 nano | Grok 4.5 |
|---|---|---|
| SciCode | 25.9% | 54.1% |
| WeirdML | 19% | 46.4% |
| LMArena Coding | 1306 | 1473 |
| DeepSWE | — | 53.8% |
| FrontierCode | — | 42.4% |
| Aider Polyglot | 8.9% | — |
| LMArena WebDev | — | 1552 |
| ALE-Bench | — | 1,309 |
Agentic & Tool Use Grok 4.5 leads
GPT-4.1 nano: 26.3 (#98), Grok 4.5: 44.4 (#15)
| Benchmark | GPT-4.1 nano | Grok 4.5 |
|---|---|---|
| APEX-Agents | — | 56.2% |
| Berkeley Function Calling Leaderboard | 33% | — |
| τ²-bench Banking | — | 47.9% |
| PostTrainBench | — | 23.4% |
| GBAEval | — | 65.4% |
| GDP.pdf | — | 14% |
| LMArena Search | — | 1213 |
| Vending-Bench 2 | — | 3,887 |
Reasoning Grok 4.5 leads
GPT-4.1 nano: 8.6 (#344), Grok 4.5: 56.0 (#23)
| Benchmark | GPT-4.1 nano | Grok 4.5 |
|---|---|---|
| ARC-AGI-2 | 0% | 52.6% |
| Kagi LLM Benchmark | 33.3% | 83.5% |
| ARC-AGI-1 | 0% | 87.2% |
| CritPt | 0% | 15.4% |
| LMArena Hard Prompts | 1286 | 1462 |
| DTBench | 52.5% | 96.5% |
| LMCA | 5.5% | 45.2% |
| Epoch Capabilities Index | 129.62 | 154.02 |
| SimpleBench | — | 70% |
| NYT Connections (extended) | — | 79.9% |
| Chess Puzzles | — | 36% |
| Surface Evolver Bench | — | 74.4% |
Math Grok 4.5 leads
GPT-4.1 nano: 25.5 (#246), Grok 4.5: 60.7 (#29)
| Benchmark | GPT-4.1 nano | Grok 4.5 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 28.9% | 97.8% |
| LMArena Math | 1274 | 1457 |
| FrontierMath (Tiers 1-3) | — | 57.2% |
| FrontierMath Tier 4 | — | 24.4% |
| ProofBench | — | 31% |
| Omni-MATH | 36.7% | — |
| MATH Level 5 | 70% | — |
| FrontierMath (Feb 2025 set) | 1% | — |
Knowledge Grok 4.5 leads
GPT-4.1 nano: 21.8 (#268), Grok 4.5: 62.3 (#21)
| Benchmark | GPT-4.1 nano | Grok 4.5 |
|---|---|---|
| GPQA Diamond | 48.9% | 93.4% |
| SimpleQA Verified | 6% | 48.3% |
| LMArena Expert | 1272 | 1466 |
| MMLU-Pro | 55% | — |
| GPQA (HELM) | 50.7% | — |
Multimodal Grok 4.5 leads
GPT-4.1 nano: 28.6 (#108), Grok 4.5: 37.8 (#63)
| Benchmark | GPT-4.1 nano | Grok 4.5 |
|---|---|---|
| LMArena Vision | 1063 | 1287 |
| Blueprint-Bench 2 | — | 27.3% |
| Furniture Assembly | — | 22.5% |
| LMArena Document | — | 1452 |
Multilingual Grok 4.5 leads
GPT-4.1 nano: 41.8 (#200), Grok 4.5: 54.5 (#43)
| Benchmark | GPT-4.1 nano | Grok 4.5 |
|---|---|---|
| LMArena Non-English | 1260 | 1439 |
| LMArena Chinese | 1270 | 1497 |
| LMArena German | 1288 | 1448 |
| LMArena Japanese | 1199 | 1425 |
| LMArena Russian | 1261 | 1447 |
| LMArena French | — | 1458 |
| LMArena Korean | — | 1402 |
| LMArena Spanish | — | 1452 |
Instruction Following Grok 4.5 leads
GPT-4.1 nano: 68.0 (#188), Grok 4.5: 76.3 (#45)
| Benchmark | GPT-4.1 nano | Grok 4.5 |
|---|---|---|
| LMArena Instruction Following | 1267 | 1446 |
| IFEval | 84.3% | — |
Long Context Grok 4.5 leads
GPT-4.1 nano: 23.7 (#291), Grok 4.5: 44.8 (#54)
| Benchmark | GPT-4.1 nano | Grok 4.5 |
|---|---|---|
| LMArena Longer Query | 1283 | 1463 |
| Fiction.LiveBench | 25% | — |
Writing & Preference Grok 4.5 leads
GPT-4.1 nano: 40.7 (#238), Grok 4.5: 65.9 (#40)
| Benchmark | GPT-4.1 nano | Grok 4.5 |
|---|---|---|
| LMArena Text | 1285 | 1448 |
| LMArena Creative Writing | 1260 | 1442 |
| EQ-Bench Creative Writing | 946 | 1579 |
| LMArena Multi-Turn | 1277 | 1457 |
| WildBench | 81.2% | — |
Frequently asked questions
Is GPT-4.1 nano better than Grok 4.5?
Grok 4.5 is the stronger model overall, scoring 55.0 to 27.7 on the Noometry Index. GPT-4.1 nano costs 17× less per token, which makes it the better buy when Grok 4.5's lead doesn't matter for your workload.
Which is cheaper, GPT-4.1 nano or Grok 4.5?
GPT-4.1 nano is cheaper. It lists at $0.10 per million input tokens and $0.40 per million output tokens; Grok 4.5 lists at $2 and $6.
Is GPT-4.1 nano or Grok 4.5 better for coding?
Grok 4.5 scores higher on coding benchmarks: 51.7 versus 23.8 in the Noometry coding category.
Which has the bigger context window?
GPT-4.1 nano does, with 1.05M tokens against 500K.
How many benchmarks do GPT-4.1 nano and Grok 4.5 share?
28 benchmarks have published results for both models. GPT-4.1 nano has 38 scored results on Noometry and Grok 4.5 has 52.