Model comparison
GPT-4.1 nano vs Grok 4.6
Grok 4.6 is the stronger model overall, scoring 56.9 to 27.9 on the Noometry Index. GPT-4.1 nano costs 17× less per token, which makes it the better buy when Grok 4.6's lead doesn't matter for your workload.
Last verified . 26 shared benchmarks.
Summary
- They share 26 benchmarks with published results for both. GPT-4.1 nano scores higher in 0 categories and Grok 4.6 in 10 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Grok 4.6 leads 61.4 to 8.5.
- The biggest single-benchmark swing is ARC-AGI-1: 0% for GPT-4.1 nano and 87.5% for Grok 4.6.
- GPT-4.1 nano is cheaper at $0.10 / $0.40 per million input/output tokens, against $2 / $6 for Grok 4.6.
- GPT-4.1 nano accepts more context: 1.05M tokens versus 500K.
Side by side
| GPT-4.1 nano | Grok 4.6 | |
|---|---|---|
| Provider | OpenAI | xAI |
| Noometry Index | 27.9 | 56.9 |
| Released | 2025-04-14 | 2026-08-12 |
| 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 | 49 |
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Category by category
Coding Grok 4.6 leads
GPT-4.1 nano: 24.1 (#330), Grok 4.6: 58.5 (#16)
| Benchmark | GPT-4.1 nano | Grok 4.6 |
|---|---|---|
| SciCode | 25.9% | 56.5% |
| WeirdML | 19% | 67.3% |
| LMArena Coding | 1306 | 1465 |
| DeepSWE | — | 67.5% |
| FrontierCode | — | 48% |
| Aider Polyglot | 8.9% | — |
| CursorBench | — | 41.4% |
| LMArena WebDev | — | 1617 |
| FrontierSWE | — | 25.3% |
| ALE-Bench | — | 1,508 |
Agentic & Tool Use Grok 4.6 leads
GPT-4.1 nano: 26.5 (#104), Grok 4.6: 39.4 (#27)
| Benchmark | GPT-4.1 nano | Grok 4.6 |
|---|---|---|
| APEX-Agents | — | 65.3% |
| Berkeley Function Calling Leaderboard | 33% | — |
| GDP.pdf | — | 17.2% |
| Vending-Bench 2 | — | 9,047 |
Reasoning Grok 4.6 leads
GPT-4.1 nano: 8.5 (#349), Grok 4.6: 61.4 (#20)
| Benchmark | GPT-4.1 nano | Grok 4.6 |
|---|---|---|
| ARC-AGI-2 | 0% | 67.1% |
| ARC-AGI-1 | 0% | 87.5% |
| CritPt | 0% | 19.7% |
| LMArena Hard Prompts | 1286 | 1447 |
| DTBench | 52.5% | 97.3% |
| LMCA | 5.5% | 48.5% |
| Epoch Capabilities Index | 129.62 | 156.44 |
| SimpleBench | — | 75.9% |
| Kagi LLM Benchmark | 33.3% | — |
| NYT Connections (extended) | — | 80% |
| Chess Puzzles | — | 40% |
| EBR-Bench | — | 30.5% |
| Mystery Game Puzzles | — | 34% |
Math Grok 4.6 leads
GPT-4.1 nano: 26.9 (#252), Grok 4.6: 67.0 (#24)
| Benchmark | GPT-4.1 nano | Grok 4.6 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 28.9% | 99.2% |
| LMArena Math | 1274 | 1423 |
| FrontierMath (Tiers 1-3) | — | 66% |
| FrontierMath Tier 4 | — | 31.7% |
| ProofBench | — | 51% |
| Omni-MATH | 36.7% | — |
| MATH Level 5 | 70% | — |
| FrontierMath (Feb 2025 set) | 1% | — |
Knowledge Grok 4.6 leads
GPT-4.1 nano: 21.8 (#273), Grok 4.6: 63.3 (#20)
| Benchmark | GPT-4.1 nano | Grok 4.6 |
|---|---|---|
| GPQA Diamond | 48.9% | 94% |
| SimpleQA Verified | 6% | 49.3% |
| LMArena Expert | 1272 | 1467 |
| MMLU-Pro | 55% | — |
| GPQA (HELM) | 50.7% | — |
Multimodal Grok 4.6 leads
GPT-4.1 nano: 29.2 (#113), Grok 4.6: 43.6 (#23)
| Benchmark | GPT-4.1 nano | Grok 4.6 |
|---|---|---|
| LMArena Vision | 1063 | 1263 |
| Blueprint-Bench 2 | — | 33.2% |
| Furniture Assembly | — | 40% |
| LMArena Document | — | 1452 |
Multilingual Grok 4.6 leads
GPT-4.1 nano: 41.6 (#205), Grok 4.6: 53.0 (#74)
| Benchmark | GPT-4.1 nano | Grok 4.6 |
|---|---|---|
| LMArena Non-English | 1260 | 1420 |
| LMArena Chinese | 1270 | 1480 |
| LMArena German | 1288 | 1431 |
| LMArena Japanese | 1198 | 1376 |
| LMArena Russian | 1261 | 1422 |
| LMArena French | — | 1461 |
| LMArena Korean | — | 1397 |
| LMArena Spanish | — | 1404 |
Instruction Following Grok 4.6 leads
GPT-4.1 nano: 67.8 (#193), Grok 4.6: 75.4 (#63)
| Benchmark | GPT-4.1 nano | Grok 4.6 |
|---|---|---|
| LMArena Instruction Following | 1267 | 1431 |
| IFEval | 84.3% | — |
Long Context Grok 4.6 leads
GPT-4.1 nano: 23.7 (#296), Grok 4.6: 44.5 (#66)
| Benchmark | GPT-4.1 nano | Grok 4.6 |
|---|---|---|
| LMArena Longer Query | 1283 | 1454 |
| Fiction.LiveBench | 25% | — |
Writing & Preference Grok 4.6 leads
GPT-4.1 nano: 40.5 (#243), Grok 4.6: 62.3 (#80)
| Benchmark | GPT-4.1 nano | Grok 4.6 |
|---|---|---|
| LMArena Text | 1285 | 1428 |
| LMArena Creative Writing | 1260 | 1428 |
| LMArena Multi-Turn | 1277 | 1425 |
| EQ-Bench Creative Writing | 946 | — |
| WildBench | 81.2% | — |
Frequently asked questions
Is GPT-4.1 nano better than Grok 4.6?
Grok 4.6 is the stronger model overall, scoring 56.9 to 27.9 on the Noometry Index. GPT-4.1 nano costs 17× less per token, which makes it the better buy when Grok 4.6's lead doesn't matter for your workload.
Which is cheaper, GPT-4.1 nano or Grok 4.6?
GPT-4.1 nano is cheaper. It lists at $0.10 per million input tokens and $0.40 per million output tokens; Grok 4.6 lists at $2 and $6.
Is GPT-4.1 nano or Grok 4.6 better for coding?
Grok 4.6 scores higher on coding benchmarks: 58.5 versus 24.1 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 4.6 share?
26 benchmarks have published results for both models. GPT-4.1 nano has 38 scored results on Noometry and Grok 4.6 has 49.