Model comparison
DeepSeek V4 Flash vs GPT-5.3 Codex
Head-to-head evidence from 5 shared benchmark results across 3 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: DeepSeek V4 Flash #61 (Estimated); GPT-5.3 Codex #26 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. DeepSeek V4 Flash and GPT-5.3 Codex share 5 comparable benchmark results. 2 of 8 categories are comparable. 17 results are unique to DeepSeek V4 Flash; 16 to GPT-5.3 Codex.
Updated July 23, 2026- Shared results
- 5
- DeepSeek V4 Flash only
- 17
- GPT-5.3 Codex only
- 16
- Comparable categories
- 2 / 8
Pick GPT-5.3 Codex if you want the stronger benchmark profile. DeepSeek V4 Flash only becomes the better choice if you want the cheaper token bill or you need the larger 1M context window.
Confidence note. This is a partial-evidence comparison with 5 shared benchmark results across 3 evidence categories; 2 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
GPT-5.3 Codex is clearly ahead on the BenchAlign aggregate, 66.69 to 58.88. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.3 Codex's sharpest advantage is in agentic, where it averages 71.4 against 49.1. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 49.1% to 77.3%.
GPT-5.3 Codex is also the more expensive model on tokens at $1.75 input / $14.00 output per 1M tokens, versus $0.14 input / $0.28 output per 1M tokens for DeepSeek V4 Flash. That is roughly 50.0x on output cost alone. GPT-5.3 Codex is the reasoning model in the pair, while DeepSeek V4 Flash is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. DeepSeek V4 Flash gives you the larger context window at 1M, compared with 400K for GPT-5.3 Codex.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | DeepSeek V4 Flash | Δ | GPT-5.3 Codex |
|---|---|---|---|
| Agentic | DeepSeek V4 Flash49.1 | Margin→ 22.3 | GPT-5.3 Codex71.4 |
| Coding | DeepSeek V4 Flash64.2 | Margin→ 3.0 | GPT-5.3 Codex67.2 |
| Knowledge | DeepSeek V4 Flash38.8 | MarginNo overlap | GPT-5.3 CodexNot measured |
| Math | DeepSeek V4 Flash40.8 | MarginNo overlap | GPT-5.3 CodexNot measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
Terminal-Bench 2.0
AgenticA 49.1%B 77.3%Winner: GPT-5.3 CodexΔ 28.2Terminal-Bench 2.0: DeepSeek V4 Flash scored 49.1%; GPT-5.3 Codex scored 77.3%. GPT-5.3 Codex wins this benchmark. - Source ↗
SWE-bench Verified
CodingA 73.7%B 85%Winner: GPT-5.3 CodexΔ 11.3SWE-bench Verified: DeepSeek V4 Flash scored 73.7%; GPT-5.3 Codex scored 85%. GPT-5.3 Codex wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 49.1%B 56.8%Winner: GPT-5.3 CodexΔ 7.7SWE-bench Pro: DeepSeek V4 Flash scored 49.1%; GPT-5.3 Codex scored 56.8%. GPT-5.3 Codex wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | DeepSeek V4 Flash | GPT-5.3 Codex | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek V4 Flash$0.14 input / $0.28 output | GPT-5.3 Codex$1.75 input / $14 output | DeepSeek V4 Flash has the lower combined listed price. |
| Generation speedtokens per second | DeepSeek V4 FlashNot available | GPT-5.3 Codex79 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | DeepSeek V4 FlashNot available | GPT-5.3 Codex88.26 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | DeepSeek V4 Flash1M | GPT-5.3 Codex400K | DeepSeek V4 Flash lists the larger context window. |
Benchmark Deep Dive
AgenticGPT-5.3 Codex wins8 benchmarks
| Benchmark | DeepSeek V4 Flash | GPT-5.3 Codex | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 49.1% | 77.3% | GPT-5.3 Codex leads |
| MCP AtlasSource | 64% | — | Not comparable |
| ToolathlonSource | 40.7% | — | Not comparable |
| Claw-EvalSource | 57.8% | — | Not comparable |
| Gert LabsSource | 54.35% | 57.47% | GPT-5.3 Codex leads |
| OSWorld-VerifiedSource | — | 64.7% | Not comparable |
| τ²-bench resultsSource | — | 86% | Not comparable |
| JobBenchSource | — | 33.7% | Not comparable |
CodingGPT-5.3 Codex wins7 benchmarks
| Benchmark | DeepSeek V4 Flash | GPT-5.3 Codex | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 73.7% | 85% | GPT-5.3 Codex leads |
| SWE-bench ProSource | 49.1% | 56.8% | GPT-5.3 Codex leads |
| SWE MultilingualSource | 69.7% | — | Not comparable |
| Terminal-Bench 2.0Source | 49.1% | — | Not comparable |
| SWE-RebenchSource | — | 58.2% | Not comparable |
| Vibe Code BenchSource | — | 61.77% | Not comparable |
| AA-SciCodeSource | — | 53.2% | Not comparable |
Reasoning4 benchmarks
Knowledge12 benchmarks
| Benchmark | DeepSeek V4 Flash | GPT-5.3 Codex | Result |
|---|---|---|---|
| MMLU-ProSource | 83% | — | Not comparable |
| SimpleQASource | 23.1% | — | Not comparable |
| Chinese-SimpleQASource | 71.5% | — | Not comparable |
| GPQASource | 71.2% | — | Not comparable |
| GPQA-DSource | 71.2% | — | Not comparable |
| HLESource | 8.1% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | — | 44.3% | Not comparable |
| AA-GPQA DiamondSource | — | 91.5% | Not comparable |
| AA-HLESource | — | 39.9% | Not comparable |
| AA-Omniscience IndexSource | — | 9.9% | Not comparable |
| AA-Omniscience AccuracySource | — | 51.8% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 86.9% | Not comparable |
Math4 benchmarks
Multimodal2 benchmarks
Inst. Following1 benchmarks
| Benchmark | DeepSeek V4 Flash | GPT-5.3 Codex | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 75.4% | Not comparable |
Frequently Asked Questions (3)
Which is better, DeepSeek V4 Flash or GPT-5.3 Codex?
GPT-5.3 Codex is ahead on BenchLM's BenchAlign leaderboard, 66.69 to 58.88. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 49.1% and 77.3%.
Which is better for coding, DeepSeek V4 Flash or GPT-5.3 Codex?
GPT-5.3 Codex has the edge for coding in this comparison, averaging 67.2 versus 64.2. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, DeepSeek V4 Flash or GPT-5.3 Codex?
GPT-5.3 Codex has the edge for agentic tasks in this comparison, averaging 71.4 versus 49.1. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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