Model comparison
DeepSeek V4 Flash vs GPT-5.3 Codex
DeepSeek V4 Flash is the stronger model overall, scoring 53.6 to 45.8 on the Noometry Index.
Last verified . 4 shared benchmarks.
DeepSeekSummary
- They share 4 benchmarks with published results for both. DeepSeek V4 Flash scores higher in 0 categories and GPT-5.3 Codex in 1 category, but none of those gaps is larger than the uncertainty.
- The biggest single-benchmark swing is WeirdML: 63% for DeepSeek V4 Flash and 79.3% for GPT-5.3 Codex.
- DeepSeek V4 Flash is cheaper at $0.15 / $0.60 per million input/output tokens, against $1.75 / $14 for GPT-5.3 Codex.
- DeepSeek V4 Flash accepts more context: 1M tokens versus 400K.
- DeepSeek V4 Flash has downloadable open weights; the other is API-only.
Side by side
| DeepSeek V4 Flash | GPT-5.3 Codex | |
|---|---|---|
| Provider | DeepSeek | OpenAI |
| Noometry Index | 53.6 | 45.8 |
| Released | 2026-04-24 | 2026-02-05 |
| Weights | Open | Proprietary |
| Context window | 1M | 400K |
| Max output | 393K | 128K |
| Input $ / M tokens | $0.15 | $1.75 |
| Output $ / M tokens | $0.60 | $14 |
| Results tracked | 41 | 8 |
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Category by category
Coding Too close to call
DeepSeek V4 Flash: 47.9 (#59), GPT-5.3 Codex: 48.6 (#56)
| Benchmark | DeepSeek V4 Flash | GPT-5.3 Codex |
|---|---|---|
| LMArena WebDev | 1582 | 1409 |
| WeirdML | 63% | 79.3% |
| ALE-Bench | 1,306 | 1,655 |
| SWE-bench Verified | — | 74.8% |
| FrontierCode | 18.8% | — |
| SciCode | 49.9% | — |
| LMArena Coding | 1457 | — |
Agentic & Tool Use Not comparable
DeepSeek V4 Flash: —, GPT-5.3 Codex: 48.0 (#9)
| Benchmark | DeepSeek V4 Flash | GPT-5.3 Codex |
|---|---|---|
| Terminal-Bench | — | 78.4% |
| METR Time Horizons | — | 74.5% |
| Vending-Bench 2 | — | 5,940 |
Reasoning Not comparable
DeepSeek V4 Flash: 53.7 (#30), GPT-5.3 Codex: —
| Benchmark | DeepSeek V4 Flash | GPT-5.3 Codex |
|---|---|---|
| Epoch Capabilities Index | 154.49 | 156.77 |
| ARC-AGI-2 | 61.4% | — |
| SimpleBench | 61.1% | — |
| Kagi LLM Benchmark | 52.2% | — |
| NYT Connections (extended) | 89.6% | — |
| ARC-AGI-1 | 89% | — |
| CritPt | 16.6% | — |
| Chess Puzzles | 33% | — |
| LMArena Hard Prompts | 1444 | — |
| Mystery Game Puzzles | 34% | — |
| DTBench | 90.9% | — |
| LMCA | 41.7% | — |
Math Not comparable
DeepSeek V4 Flash: 60.3 (#37), GPT-5.3 Codex: —
| Benchmark | DeepSeek V4 Flash | GPT-5.3 Codex |
|---|---|---|
| FrontierMath (Tiers 1-3) | 57.5% | — |
| FrontierMath Tier 4 | 24.4% | — |
| MathArena Final-Answer Competitions | 76.5% | — |
| OTIS Mock AIME 2024-2025 | 94.4% | — |
| ProofBench | 56% | — |
| LMArena Math | 1427 | — |
Knowledge Not comparable
DeepSeek V4 Flash: 55.4 (#48), GPT-5.3 Codex: —
| Benchmark | DeepSeek V4 Flash | GPT-5.3 Codex |
|---|---|---|
| GPQA Diamond | 91% | — |
| SimpleQA Verified | 33.6% | — |
| LMArena Expert | 1441 | — |
Multilingual Not comparable
DeepSeek V4 Flash: 53.0 (#72), GPT-5.3 Codex: —
| Benchmark | DeepSeek V4 Flash | GPT-5.3 Codex |
|---|---|---|
| LMArena Non-English | 1420 | — |
| LMArena Chinese | 1468 | — |
| LMArena French | 1439 | — |
| LMArena German | 1418 | — |
| LMArena Japanese | 1406 | — |
| LMArena Korean | 1384 | — |
| LMArena Russian | 1428 | — |
| LMArena Spanish | 1436 | — |
Instruction Following Not comparable
DeepSeek V4 Flash: 74.9 (#81), GPT-5.3 Codex: —
| Benchmark | DeepSeek V4 Flash | GPT-5.3 Codex |
|---|---|---|
| LMArena Instruction Following | 1421 | — |
Long Context Not comparable
DeepSeek V4 Flash: 43.8 (#85), GPT-5.3 Codex: —
| Benchmark | DeepSeek V4 Flash | GPT-5.3 Codex |
|---|---|---|
| LMArena Longer Query | 1434 | — |
Writing & Preference Not comparable
DeepSeek V4 Flash: 63.8 (#61), GPT-5.3 Codex: —
| Benchmark | DeepSeek V4 Flash | GPT-5.3 Codex |
|---|---|---|
| LMArena Text | 1432 | — |
| LMArena Creative Writing | 1403 | — |
| EQ-Bench Creative Writing | 1559 | — |
| LMArena Multi-Turn | 1449 | — |
Frequently asked questions
Is DeepSeek V4 Flash better than GPT-5.3 Codex?
DeepSeek V4 Flash is the stronger model overall, scoring 53.6 to 45.8 on the Noometry Index.
Which is cheaper, DeepSeek V4 Flash or GPT-5.3 Codex?
DeepSeek V4 Flash is cheaper. It lists at $0.15 per million input tokens and $0.60 per million output tokens; GPT-5.3 Codex lists at $1.75 and $14.
Is DeepSeek V4 Flash or GPT-5.3 Codex better for coding?
They score almost the same on coding (47.9 vs 48.6); test both on your own repository before choosing.
Which has the bigger context window?
DeepSeek V4 Flash does, with 1M tokens against 400K.
How many benchmarks do DeepSeek V4 Flash and GPT-5.3 Codex share?
4 benchmarks have published results for both models. DeepSeek V4 Flash has 41 scored results on Noometry and GPT-5.3 Codex has 8.