Model comparison
Claude Sonnet 4.6 vs GPT-5.3 Codex
Claude Sonnet 4.6 is the stronger model overall, scoring 50.3 to 45.8 on the Noometry Index.
Last verified . 7 shared benchmarks.
Summary
- They share 7 benchmarks with published results for both. Claude Sonnet 4.6 scores higher in 0 categories and GPT-5.3 Codex in 2 categories; 2 gaps are clear of the uncertainty.
- The widest gap is in agentic & tool use, where GPT-5.3 Codex leads 48.0 to 39.1.
- The biggest single-benchmark swing is Terminal-Bench: 53.4% for Claude Sonnet 4.6 and 78.4% for GPT-5.3 Codex.
- GPT-5.3 Codex is cheaper at $1.75 / $14 per million input/output tokens, against $3 / $15 for Claude Sonnet 4.6.
- Claude Sonnet 4.6 accepts more context: 1M tokens versus 400K.
Side by side
| Claude Sonnet 4.6 | GPT-5.3 Codex | |
|---|---|---|
| Provider | Anthropic | OpenAI |
| Noometry Index | 50.3 | 45.8 |
| Released | 2026-02-17 | 2026-02-05 |
| Weights | Proprietary | Proprietary |
| Context window | 1M | 400K |
| Max output | 128K | 128K |
| Input $ / M tokens | $3 | $1.75 |
| Output $ / M tokens | $15 | $14 |
| Results tracked | 57 | 8 |
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Category by category
Coding GPT-5.3 Codex leads
Claude Sonnet 4.6: 46.3 (#67), GPT-5.3 Codex: 48.6 (#56)
| Benchmark | Claude Sonnet 4.6 | GPT-5.3 Codex |
|---|---|---|
| SWE-bench Verified | 75.2% | 74.8% |
| LMArena WebDev | 1522 | 1409 |
| WeirdML | 66.1% | 79.3% |
| ALE-Bench | 1,327 | 1,655 |
| DeepSWE | 29.9% | — |
| FrontierCode | 24.3% | — |
| SciCode | 46.8% | — |
| LMArena Coding | 1504 | — |
Agentic & Tool Use GPT-5.3 Codex leads
Claude Sonnet 4.6: 39.1 (#28), GPT-5.3 Codex: 48.0 (#9)
| Benchmark | Claude Sonnet 4.6 | GPT-5.3 Codex |
|---|---|---|
| Terminal-Bench | 53.4% | 78.4% |
| Vending-Bench 2 | 7,204 | 5,940 |
| APEX-Agents | 43% | — |
| OSWorld 2.0 | 9.3% | — |
| DeepResearch Bench | 54.9% | — |
| OSWorld | 72.1% | — |
| ExploitBench | 23.6% | — |
| GBAEval | 48.8% | — |
| GDP.pdf | 18% | — |
| LMArena Search | 1221 | — |
| METR Time Horizons | — | 74.5% |
Reasoning Not comparable
Claude Sonnet 4.6: 46.1 (#45), GPT-5.3 Codex: —
| Benchmark | Claude Sonnet 4.6 | GPT-5.3 Codex |
|---|---|---|
| Epoch Capabilities Index | 152.24 | 156.77 |
| ARC-AGI-2 | 60.4% | — |
| NYT Connections (extended) | 80.9% | — |
| ARC-AGI-1 | 86.5% | — |
| CritPt | 3.1% | — |
| Chess Puzzles | 13% | — |
| Thematic Generalization | 76.3% | — |
| LMArena Hard Prompts | 1484 | — |
| Mystery Game Puzzles | 16% | — |
| DTBench | 89.9% | — |
| LMCA | 46.5% | — |
| ForecastBench | 62 | — |
Math Not comparable
Claude Sonnet 4.6: 52.9 (#49), GPT-5.3 Codex: —
| Benchmark | Claude Sonnet 4.6 | GPT-5.3 Codex |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 85.8% | — |
| ProofBench | 45% | — |
| LMArena Math | 1462 | — |
| FrontierMath (Feb 2025 set) | 32.4% | — |
| FrontierMath Tier 4 (v1) | 8.3% | — |
Knowledge Not comparable
Claude Sonnet 4.6: 51.7 (#65), GPT-5.3 Codex: —
| Benchmark | Claude Sonnet 4.6 | GPT-5.3 Codex |
|---|---|---|
| GPQA Diamond | 87.4% | — |
| SimpleQA Verified | 35.5% | — |
| Vectara Hallucination Rate | 10.6% | — |
| LMArena Expert | 1500 | — |
Multimodal Not comparable
Claude Sonnet 4.6: 38.0 (#68), GPT-5.3 Codex: —
| Benchmark | Claude Sonnet 4.6 | GPT-5.3 Codex |
|---|---|---|
| LMArena Vision | 1283 | — |
| Blueprint-Bench 2 | 6.7% | — |
| LMArena Document | 1482 | — |
Multilingual Not comparable
Claude Sonnet 4.6: 54.4 (#41), GPT-5.3 Codex: —
| Benchmark | Claude Sonnet 4.6 | GPT-5.3 Codex |
|---|---|---|
| LMArena Non-English | 1440 | — |
| LMArena Chinese | 1491 | — |
| LMArena French | 1465 | — |
| LMArena German | 1428 | — |
| LMArena Japanese | 1420 | — |
| LMArena Korean | 1411 | — |
| LMArena Russian | 1440 | — |
| LMArena Spanish | 1464 | — |
Instruction Following Not comparable
Claude Sonnet 4.6: 77.4 (#25), GPT-5.3 Codex: —
| Benchmark | Claude Sonnet 4.6 | GPT-5.3 Codex |
|---|---|---|
| LMArena Instruction Following | 1475 | — |
Long Context Not comparable
Claude Sonnet 4.6: 45.3 (#44), GPT-5.3 Codex: —
| Benchmark | Claude Sonnet 4.6 | GPT-5.3 Codex |
|---|---|---|
| LMArena Longer Query | 1479 | — |
Writing & Preference Not comparable
Claude Sonnet 4.6: 70.2 (#22), GPT-5.3 Codex: —
| Benchmark | Claude Sonnet 4.6 | GPT-5.3 Codex |
|---|---|---|
| LMArena Text | 1458 | — |
| LMArena Creative Writing | 1435 | — |
| EQ-Bench Creative Writing | 1810 | — |
| EQ-Bench 4 | 1207 | — |
| LMArena Multi-Turn | 1464 | — |
Frequently asked questions
Is Claude Sonnet 4.6 better than GPT-5.3 Codex?
Claude Sonnet 4.6 is the stronger model overall, scoring 50.3 to 45.8 on the Noometry Index.
Which is cheaper, Claude Sonnet 4.6 or GPT-5.3 Codex?
GPT-5.3 Codex is cheaper. It lists at $1.75 per million input tokens and $14 per million output tokens; Claude Sonnet 4.6 lists at $3 and $15.
Is Claude Sonnet 4.6 or GPT-5.3 Codex better for coding?
GPT-5.3 Codex scores higher on coding benchmarks: 48.6 versus 46.3 in the Noometry coding category.
Which has the bigger context window?
Claude Sonnet 4.6 does, with 1M tokens against 400K.
How many benchmarks do Claude Sonnet 4.6 and GPT-5.3 Codex share?
7 benchmarks have published results for both models. Claude Sonnet 4.6 has 57 scored results on Noometry and GPT-5.3 Codex has 8.