Model comparison
GPT-5 Nano vs Grok 4.3
Grok 4.3 is the stronger model overall, scoring 43.8 to 33.5 on the Noometry Index. GPT-5 Nano costs 11× less per token, which makes it the better buy when Grok 4.3's lead doesn't matter for your workload.
Last verified . 30 shared benchmarks.
Summary
- They share 30 benchmarks with published results for both. GPT-5 Nano scores higher in 1 category and Grok 4.3 in 9 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Grok 4.3 leads 35.9 to 16.3.
- The biggest single-benchmark swing is LMCA: 7.9% for GPT-5 Nano and 38.3% for Grok 4.3.
- GPT-5 Nano is cheaper at $0.05 / $0.40 per million input/output tokens, against $1.25 / $2.50 for Grok 4.3.
- Grok 4.3 accepts more context: 1M tokens versus 400K.
Side by side
| GPT-5 Nano | Grok 4.3 | |
|---|---|---|
| Provider | OpenAI | xAI |
| Noometry Index | 33.5 | 43.8 |
| Released | 2025-08-07 | 2026-04-17 |
| 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 | 49 | 40 |
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Category by category
Coding Grok 4.3 leads
GPT-5 Nano: 33.6 (#254), Grok 4.3: 41.6 (#121)
| Benchmark | GPT-5 Nano | Grok 4.3 |
|---|---|---|
| WeirdML | 38.1% | 49.9% |
| LMArena Coding | 1351 | 1415 |
| ALE-Bench | 718.67 | 944.17 |
| SWE-bench Verified (bash only) | 34.8% | — |
| LMArena WebDev | — | 1357 |
| SciCode | — | 47.3% |
Agentic & Tool Use Grok 4.3 leads
GPT-5 Nano: 25.8 (#106), Grok 4.3: 27.7 (#99)
| Benchmark | GPT-5 Nano | Grok 4.3 |
|---|---|---|
| Terminal-Bench | 21.8% | — |
| Berkeley Function Calling Leaderboard | 51.5% | — |
| GDP.pdf | — | 8% |
| LMArena Search | — | 1165 |
| Vending-Bench 2 | — | 35.26 |
Reasoning Grok 4.3 leads
GPT-5 Nano: 16.3 (#306), Grok 4.3: 35.9 (#68)
| Benchmark | GPT-5 Nano | Grok 4.3 |
|---|---|---|
| Chess Puzzles | 27% | 25% |
| LMArena Hard Prompts | 1328 | 1396 |
| DTBench | 62.7% | 90.7% |
| LMCA | 7.9% | 38.3% |
| Epoch Capabilities Index | 139.38 | 149.16 |
| ForecastBench | 59.1 | 60.3 |
| ARC-AGI-2 | 2.6% | — |
| Kagi LLM Benchmark | 62.2% | — |
| NYT Connections (extended) | — | 55.2% |
| ARC-AGI-1 | 20.7% | — |
| CritPt | — | 8% |
| Mystery Game Puzzles | 9% | — |
Math Grok 4.3 leads
GPT-5 Nano: 29.4 (#241), Grok 4.3: 46.0 (#74)
| Benchmark | GPT-5 Nano | Grok 4.3 |
|---|---|---|
| FrontierMath (Tiers 1-3) | 20% | 42.8% |
| FrontierMath Tier 4 | 2.4% | 14.6% |
| OTIS Mock AIME 2024-2025 | 81.1% | 93.3% |
| ProofBench | 12% | 11% |
| LMArena Math | 1317 | 1388 |
| Omni-MATH | 54.6% | — |
| MATH Level 5 | 95.2% | — |
| FrontierMath (Feb 2025 set) | 8.3% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |
Knowledge Grok 4.3 leads
GPT-5 Nano: 35.9 (#178), Grok 4.3: 52.5 (#62)
| Benchmark | GPT-5 Nano | Grok 4.3 |
|---|---|---|
| GPQA Diamond | 69.4% | 88.8% |
| SimpleQA Verified | 11.7% | 33.2% |
| LMArena Expert | 1321 | 1385 |
| MMLU-Pro | 77.8% | — |
| Vectara Hallucination Rate | 10.5% | — |
| GPQA (HELM) | 67.9% | — |
Multimodal Too close to call
GPT-5 Nano: 31.3 (#108), Grok 4.3: 31.6 (#104)
| Benchmark | GPT-5 Nano | Grok 4.3 |
|---|---|---|
| LMArena Vision | 1159 | 1229 |
| VPCT | 37.2% | — |
| Blueprint-Bench 2 | — | 0% |
Multilingual Grok 4.3 leads
GPT-5 Nano: 45.3 (#172), Grok 4.3: 50.5 (#120)
| Benchmark | GPT-5 Nano | Grok 4.3 |
|---|---|---|
| LMArena Non-English | 1313 | 1385 |
| LMArena Chinese | 1356 | 1422 |
| LMArena German | 1327 | 1395 |
| LMArena Japanese | 1226 | 1379 |
| LMArena Korean | 1269 | 1356 |
| LMArena Russian | 1296 | 1399 |
| LMArena Spanish | 1360 | 1398 |
| LMArena French | — | 1412 |
Instruction Following GPT-5 Nano leads
GPT-5 Nano: 75.0 (#79), Grok 4.3: 72.1 (#140)
| Benchmark | GPT-5 Nano | Grok 4.3 |
|---|---|---|
| LMArena Instruction Following | 1306 | 1366 |
| IFEval | 93.2% | — |
Long Context Grok 4.3 leads
GPT-5 Nano: 31.3 (#281), Grok 4.3: 42.5 (#123)
| Benchmark | GPT-5 Nano | Grok 4.3 |
|---|---|---|
| LMArena Longer Query | 1312 | 1393 |
| Fiction.LiveBench | 44.4% | — |
Writing & Preference Grok 4.3 leads
GPT-5 Nano: 39.1 (#249), Grok 4.3: 58.5 (#118)
| Benchmark | GPT-5 Nano | Grok 4.3 |
|---|---|---|
| LMArena Text | 1320 | 1397 |
| LMArena Creative Writing | 1249 | 1380 |
| LMArena Multi-Turn | 1311 | 1406 |
| EQ-Bench Creative Writing | 705 | — |
| WildBench | 80.6% | — |
| EQ-Bench 4 | — | 1075 |
Frequently asked questions
Is GPT-5 Nano better than Grok 4.3?
Grok 4.3 is the stronger model overall, scoring 43.8 to 33.5 on the Noometry Index. GPT-5 Nano costs 11× less per token, which makes it the better buy when Grok 4.3's lead doesn't matter for your workload.
Which is cheaper, GPT-5 Nano or Grok 4.3?
GPT-5 Nano is cheaper. It lists at $0.05 per million input tokens and $0.40 per million output tokens; Grok 4.3 lists at $1.25 and $2.50.
Is GPT-5 Nano or Grok 4.3 better for coding?
Grok 4.3 scores higher on coding benchmarks: 41.6 versus 33.6 in the Noometry coding category.
Which has the bigger context window?
Grok 4.3 does, with 1M tokens against 400K.
How many benchmarks do GPT-5 Nano and Grok 4.3 share?
30 benchmarks have published results for both models. GPT-5 Nano has 49 scored results on Noometry and Grok 4.3 has 40.