Model comparison
DeepSeek-V3.1 vs GPT-5.3 Codex
GPT-5.3 Codex is the stronger model overall, scoring 45.5 to 42.2 on the Noometry Index. DeepSeek-V3.1 costs 11× less per token, which makes it the better buy when GPT-5.3 Codex's lead doesn't matter for your workload.
Last verified . 2 shared benchmarks.
DeepSeekSummary
- They share 2 benchmarks with published results for both. DeepSeek-V3.1 scores higher in 0 categories and GPT-5.3 Codex in 1 category; one gap is clear of the uncertainty.
- The widest gap is in coding, where GPT-5.3 Codex leads 48.5 to 39.8.
- The biggest single-benchmark swing is WeirdML: 38.4% for DeepSeek-V3.1 and 79.3% for GPT-5.3 Codex.
- DeepSeek-V3.1 is cheaper at $0.25 / $0.95 per million input/output tokens, against $1.75 / $14 for GPT-5.3 Codex.
- GPT-5.3 Codex accepts more context: 400K tokens versus 164K.
- DeepSeek-V3.1 has downloadable open weights; the other is API-only.
Side by side
| DeepSeek-V3.1 | GPT-5.3 Codex | |
|---|---|---|
| Provider | DeepSeek | OpenAI |
| Noometry Index | 42.2 | 45.5 |
| Released | 2025-08-21 | 2026-02-05 |
| Weights | Open | Proprietary |
| Context window | 164K | 400K |
| Max output | 8K | 128K |
| Input $ / M tokens | $0.25 | $1.75 |
| Output $ / M tokens | $0.95 | $14 |
| Results tracked | 27 | 8 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding GPT-5.3 Codex leads
DeepSeek-V3.1: 39.8 (#140), GPT-5.3 Codex: 48.5 (#51)
| Benchmark | DeepSeek-V3.1 | GPT-5.3 Codex |
|---|---|---|
| WeirdML | 38.4% | 79.3% |
| SWE-bench Verified | — | 74.8% |
| LMArena WebDev | — | 1408 |
| LMArena Coding | 1417 | — |
| ALE-Bench | — | 1,655 |
Agentic & Tool Use Not comparable
DeepSeek-V3.1: —, GPT-5.3 Codex: 47.8 (#9)
| Benchmark | DeepSeek-V3.1 | GPT-5.3 Codex |
|---|---|---|
| Terminal-Bench | — | 78.4% |
| METR Time Horizons | — | 74.5% |
| Vending-Bench 2 | — | 5,940 |
Reasoning Not comparable
DeepSeek-V3.1: 27.3 (#109), GPT-5.3 Codex: —
| Benchmark | DeepSeek-V3.1 | GPT-5.3 Codex |
|---|---|---|
| Epoch Capabilities Index | 139.92 | 156.84 |
| SimpleBench | 40% | — |
| Kagi LLM Benchmark | 53.2% | — |
| LMArena Hard Prompts | 1417 | — |
| DTBench | 82.7% | — |
| LMCA | 24.3% | — |
| ForecastBench | 58 | — |
Math Not comparable
DeepSeek-V3.1: 36.1 (#125), GPT-5.3 Codex: —
| Benchmark | DeepSeek-V3.1 | GPT-5.3 Codex |
|---|---|---|
| LMArena Math | 1420 | — |
Knowledge Not comparable
DeepSeek-V3.1: 43.0 (#86), GPT-5.3 Codex: —
| Benchmark | DeepSeek-V3.1 | GPT-5.3 Codex |
|---|---|---|
| Vectara Hallucination Rate | 5.5% | — |
| LMArena Expert | 1403 | — |
Multilingual Not comparable
DeepSeek-V3.1: 51.8 (#100), GPT-5.3 Codex: —
| Benchmark | DeepSeek-V3.1 | GPT-5.3 Codex |
|---|---|---|
| LMArena Non-English | 1400 | — |
| LMArena Chinese | 1470 | — |
| LMArena French | 1447 | — |
| LMArena German | 1412 | — |
| LMArena Japanese | 1374 | — |
| LMArena Korean | 1337 | — |
| LMArena Russian | 1405 | — |
| LMArena Spanish | 1429 | — |
Instruction Following Not comparable
DeepSeek-V3.1: 74.1 (#105), GPT-5.3 Codex: —
| Benchmark | DeepSeek-V3.1 | GPT-5.3 Codex |
|---|---|---|
| LMArena Instruction Following | 1400 | — |
Long Context Not comparable
DeepSeek-V3.1: 36.3 (#227), GPT-5.3 Codex: —
| Benchmark | DeepSeek-V3.1 | GPT-5.3 Codex |
|---|---|---|
| Fiction.LiveBench | 52.8% | — |
| LMArena Longer Query | 1422 | — |
Writing & Preference Not comparable
DeepSeek-V3.1: 60.5 (#93), GPT-5.3 Codex: —
| Benchmark | DeepSeek-V3.1 | GPT-5.3 Codex |
|---|---|---|
| LMArena Text | 1420 | — |
| LMArena Creative Writing | 1401 | — |
| EQ-Bench Creative Writing | 1436 | — |
| LMArena Multi-Turn | 1408 | — |
Frequently asked questions
Is DeepSeek-V3.1 better than GPT-5.3 Codex?
GPT-5.3 Codex is the stronger model overall, scoring 45.5 to 42.2 on the Noometry Index. DeepSeek-V3.1 costs 11× less per token, which makes it the better buy when GPT-5.3 Codex's lead doesn't matter for your workload.
Which is cheaper, DeepSeek-V3.1 or GPT-5.3 Codex?
DeepSeek-V3.1 is cheaper. It lists at $0.25 per million input tokens and $0.95 per million output tokens; GPT-5.3 Codex lists at $1.75 and $14.
Is DeepSeek-V3.1 or GPT-5.3 Codex better for coding?
GPT-5.3 Codex scores higher on coding benchmarks: 48.5 versus 39.8 in the Noometry coding category.
Which has the bigger context window?
GPT-5.3 Codex does, with 400K tokens against 164K.
How many benchmarks do DeepSeek-V3.1 and GPT-5.3 Codex share?
2 benchmarks have published results for both models. DeepSeek-V3.1 has 27 scored results on Noometry and GPT-5.3 Codex has 8.