Model comparison
GPT-5.3 Codex vs Grok 4.5
Grok 4.5 is the stronger model overall, scoring 55.0 to 45.8 on the Noometry Index.
Last verified . 5 shared benchmarks.
Summary
- They share 5 benchmarks with published results for both. GPT-5.3 Codex scores higher in 1 category and Grok 4.5 in 1 category; 2 gaps are clear of the uncertainty.
- The widest gap is in agentic & tool use, where GPT-5.3 Codex leads 48.0 to 44.4.
- The biggest single-benchmark swing is WeirdML: 79.3% for GPT-5.3 Codex and 46.4% for Grok 4.5.
- Grok 4.5 is cheaper at $2 / $6 per million input/output tokens, against $1.75 / $14 for GPT-5.3 Codex.
- Grok 4.5 accepts more context: 500K tokens versus 400K.
Side by side
| GPT-5.3 Codex | Grok 4.5 | |
|---|---|---|
| Provider | OpenAI | xAI |
| Noometry Index | 45.8 | 55.0 |
| Released | 2026-02-05 | 2026-07-08 |
| Weights | Proprietary | Proprietary |
| Context window | 400K | 500K |
| Max output | 128K | 500K |
| Input $ / M tokens | $1.75 | $2 |
| Output $ / M tokens | $14 | $6 |
| Results tracked | 8 | 52 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding Grok 4.5 leads
GPT-5.3 Codex: 48.6 (#56), Grok 4.5: 52.2 (#35)
| Benchmark | GPT-5.3 Codex | Grok 4.5 |
|---|---|---|
| LMArena WebDev | 1409 | 1553 |
| WeirdML | 79.3% | 46.4% |
| ALE-Bench | 1,655 | 1,309 |
| SWE-bench Verified | 74.8% | — |
| DeepSWE | — | 53.8% |
| FrontierCode | — | 42.4% |
| SciCode | — | 54.1% |
| LMArena Coding | — | 1474 |
Agentic & Tool Use GPT-5.3 Codex leads
GPT-5.3 Codex: 48.0 (#9), Grok 4.5: 44.4 (#17)
| Benchmark | GPT-5.3 Codex | Grok 4.5 |
|---|---|---|
| Vending-Bench 2 | 5,940 | 3,887 |
| Terminal-Bench | 78.4% | — |
| APEX-Agents | — | 56.2% |
| τ²-bench Banking | — | 47.9% |
| PostTrainBench | — | 23.4% |
| GBAEval | — | 65.4% |
| GDP.pdf | — | 14% |
| LMArena Search | — | 1213 |
| METR Time Horizons | 74.5% | — |
Reasoning Not comparable
GPT-5.3 Codex: —, Grok 4.5: 56.1 (#25)
| Benchmark | GPT-5.3 Codex | Grok 4.5 |
|---|---|---|
| Epoch Capabilities Index | 156.77 | 153.92 |
| ARC-AGI-2 | — | 52.6% |
| SimpleBench | — | 70% |
| Kagi LLM Benchmark | — | 83.5% |
| NYT Connections (extended) | — | 79.9% |
| ARC-AGI-1 | — | 87.2% |
| CritPt | — | 15.4% |
| Chess Puzzles | — | 36% |
| LMArena Hard Prompts | — | 1462 |
| DTBench | — | 96.5% |
| LMCA | — | 45.2% |
| Surface Evolver Bench | — | 74.4% |
Math Not comparable
GPT-5.3 Codex: —, Grok 4.5: 60.9 (#35)
| Benchmark | GPT-5.3 Codex | Grok 4.5 |
|---|---|---|
| FrontierMath (Tiers 1-3) | — | 57.2% |
| FrontierMath Tier 4 | — | 24.4% |
| OTIS Mock AIME 2024-2025 | — | 97.8% |
| ProofBench | — | 31% |
| LMArena Math | — | 1459 |
Knowledge Not comparable
GPT-5.3 Codex: —, Grok 4.5: 62.3 (#24)
| Benchmark | GPT-5.3 Codex | Grok 4.5 |
|---|---|---|
| GPQA Diamond | — | 93.4% |
| SimpleQA Verified | — | 48.3% |
| LMArena Expert | — | 1466 |
Multimodal Not comparable
GPT-5.3 Codex: —, Grok 4.5: 37.6 (#72)
| Benchmark | GPT-5.3 Codex | Grok 4.5 |
|---|---|---|
| LMArena Vision | — | 1288 |
| Blueprint-Bench 2 | — | 27.3% |
| Furniture Assembly | — | 22.5% |
| LMArena Document | — | 1452 |
Multilingual Not comparable
GPT-5.3 Codex: —, Grok 4.5: 54.4 (#42)
| Benchmark | GPT-5.3 Codex | Grok 4.5 |
|---|---|---|
| LMArena Non-English | — | 1440 |
| LMArena Chinese | — | 1496 |
| LMArena French | — | 1456 |
| LMArena German | — | 1446 |
| LMArena Japanese | — | 1428 |
| LMArena Korean | — | 1404 |
| LMArena Russian | — | 1448 |
| LMArena Spanish | — | 1450 |
Instruction Following Not comparable
GPT-5.3 Codex: —, Grok 4.5: 76.0 (#48)
| Benchmark | GPT-5.3 Codex | Grok 4.5 |
|---|---|---|
| LMArena Instruction Following | — | 1446 |
Long Context Not comparable
GPT-5.3 Codex: —, Grok 4.5: 44.8 (#56)
| Benchmark | GPT-5.3 Codex | Grok 4.5 |
|---|---|---|
| LMArena Longer Query | — | 1463 |
Writing & Preference Not comparable
GPT-5.3 Codex: —, Grok 4.5: 65.8 (#42)
| Benchmark | GPT-5.3 Codex | Grok 4.5 |
|---|---|---|
| LMArena Text | — | 1448 |
| LMArena Creative Writing | — | 1442 |
| EQ-Bench Creative Writing | — | 1579 |
| LMArena Multi-Turn | — | 1456 |
Frequently asked questions
Is GPT-5.3 Codex better than Grok 4.5?
Grok 4.5 is the stronger model overall, scoring 55.0 to 45.8 on the Noometry Index.
Which is cheaper, GPT-5.3 Codex or Grok 4.5?
Grok 4.5 is cheaper. It lists at $2 per million input tokens and $6 per million output tokens; GPT-5.3 Codex lists at $1.75 and $14.
Is GPT-5.3 Codex or Grok 4.5 better for coding?
Grok 4.5 scores higher on coding benchmarks: 52.2 versus 48.6 in the Noometry coding category.
Which has the bigger context window?
Grok 4.5 does, with 500K tokens against 400K.
How many benchmarks do GPT-5.3 Codex and Grok 4.5 share?
5 benchmarks have published results for both models. GPT-5.3 Codex has 8 scored results on Noometry and Grok 4.5 has 52.