Model comparison
DeepSeek V4 Pro vs GPT-5.4 nano
Head-to-head evidence from 5 shared benchmark results across 2 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: DeepSeek V4 Pro #46 (Supported); GPT-5.4 nano #25 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. DeepSeek V4 Pro and GPT-5.4 nano share 5 comparable benchmark results. 3 of 8 categories are comparable. 18 results are unique to DeepSeek V4 Pro; 24 to GPT-5.4 nano.
Updated July 23, 2026- Shared results
- 5
- DeepSeek V4 Pro only
- 18
- GPT-5.4 nano only
- 24
- Comparable categories
- 3 / 8
Pick GPT-5.4 nano if you want the stronger benchmark profile. DeepSeek V4 Pro only becomes the better choice if agentic is the priority or you want the cheaper token bill.
Confidence note. This is a partial-evidence comparison with 5 shared benchmark results across 2 evidence categories; 3 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
GPT-5.4 nano is clearly ahead on the BenchAlign aggregate, 66.79 to 60.66. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.4 nano's sharpest advantage is in knowledge, where it averages 43.8 against 41.3. The single biggest benchmark swing on the page is HLE, 7.7% to 37.7%. DeepSeek V4 Pro does hit back in agentic, so the answer changes if that is the part of the workload you care about most.
GPT-5.4 nano is also the more expensive model on tokens at $0.20 input / $1.25 output per 1M tokens, versus $0.43 input / $0.87 output per 1M tokens for DeepSeek V4 Pro. GPT-5.4 nano is the reasoning model in the pair, while DeepSeek V4 Pro 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 Pro gives you the larger context window at 1M, compared with 400K for GPT-5.4 nano.
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 Pro | Δ | GPT-5.4 nano |
|---|---|---|---|
| Agentic | DeepSeek V4 Pro59.1 | Margin← 16.2 | GPT-5.4 nano42.9 |
| Math | DeepSeek V4 Pro31.7 | Margin← 10.7 | GPT-5.4 nano21.0 |
| Knowledge | DeepSeek V4 Pro41.3 | Margin→ 2.5 | GPT-5.4 nano43.8 |
| Coding | DeepSeek V4 Pro65.3 | MarginNo overlap | GPT-5.4 nanoNot measured |
| Multimodal | DeepSeek V4 ProNot measured | MarginNo overlap | GPT-5.4 nano66.1 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
HLE
KnowledgeA 7.7%B 37.7%Winner: GPT-5.4 nanoΔ 30HLE: DeepSeek V4 Pro scored 7.7%; GPT-5.4 nano scored 37.7%. GPT-5.4 nano wins this benchmark. - Source ↗
Terminal-Bench 2.0
AgenticA 59.1%B 46.3%Winner: DeepSeek V4 ProΔ 12.8Terminal-Bench 2.0: DeepSeek V4 Pro scored 59.1%; GPT-5.4 nano scored 46.3%. DeepSeek V4 Pro wins this benchmark. - Source ↗
GPQA
KnowledgeA 72.9%B 82.8%Winner: GPT-5.4 nanoΔ 9.9GPQA: DeepSeek V4 Pro scored 72.9%; GPT-5.4 nano scored 82.8%. GPT-5.4 nano wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | DeepSeek V4 Pro | GPT-5.4 nano | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek V4 Pro$0.435 input / $0.87 output | GPT-5.4 nano$0.2 input / $1.25 output | DeepSeek V4 Pro has the lower combined listed price. |
| Generation speedtokens per second | DeepSeek V4 ProNot available | GPT-5.4 nano191 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | DeepSeek V4 ProNot available | GPT-5.4 nano3.64 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | DeepSeek V4 Pro1M | GPT-5.4 nano400K | DeepSeek V4 Pro lists the larger context window. |
Benchmark Deep Dive
AgenticDeepSeek V4 Pro wins12 benchmarks
| Benchmark | DeepSeek V4 Pro | GPT-5.4 nano | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 59.1% | 46.3% | DeepSeek V4 Pro leads |
| MCP AtlasSource | 69.4% | 56.1% | DeepSeek V4 Pro leads |
| ToolathlonSource | 46.3% | 35.5% | DeepSeek V4 Pro leads |
| Claw-EvalSource | 59.8% | — | Not comparable |
| Gert LabsSource | 50.28% | — | Not comparable |
| ResearchClawBenchSource | 17.1% | — | Not comparable |
| OSWorld-VerifiedSource | — | 39% | Not comparable |
| τ²-bench resultsSource | — | 76% | Not comparable |
| AA Agentic IndexSource | — | 27.5% | Not comparable |
| APEX-Agents-AASource | — | 24.9% | Not comparable |
| GDPval-AASource | — | 30.0% | Not comparable |
| GDPval-AASource | — | 1100 | Not comparable |
Coding7 benchmarks
| Benchmark | DeepSeek V4 Pro | GPT-5.4 nano | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 73.6% | — | Not comparable |
| SWE-bench ProSource | 52.1% | — | Not comparable |
| SWE MultilingualSource | 69.8% | — | Not comparable |
| Terminal-Bench 2.0Source | 59.1% | — | Not comparable |
| Vibe Code BenchSource | — | 26.10% | Not comparable |
| AA Coding IndexSource | — | 56.1% | Not comparable |
| AA-SciCodeSource | — | 46.9% | Not comparable |
Reasoning4 benchmarks
KnowledgeGPT-5.4 nano wins13 benchmarks
| Benchmark | DeepSeek V4 Pro | GPT-5.4 nano | Result |
|---|---|---|---|
| MMLU-ProSource | 82.9% | — | Not comparable |
| SimpleQASource | 45% | — | Not comparable |
| Chinese-SimpleQASource | 75.8% | — | Not comparable |
| GPQASource | 72.9% | 82.8% | GPT-5.4 nano leads |
| GPQA-DSource | 72.9% | — | Not comparable |
| HLESource | 7.7% | 37.7% | GPT-5.4 nano leads |
| HLE w/o toolsSource | — | 24.3% | Not comparable |
| Artificial Analysis Intelligence IndexSource | — | 38.2% | Not comparable |
| AA-GPQA DiamondSource | — | 81.7% | Not comparable |
| AA-HLESource | — | 26.5% | Not comparable |
| AA-Omniscience IndexSource | — | -29.5% | Not comparable |
| AA-Omniscience AccuracySource | — | 25.4% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 73.6% | Not comparable |
MathDeepSeek V4 Pro wins6 benchmarks
| Benchmark | DeepSeek V4 Pro | GPT-5.4 nano | Result |
|---|---|---|---|
| HMMT Feb 2026Source | 31.7% | — | Not comparable |
| IMOAnswerBenchSource | 35.3% | — | Not comparable |
| ApexSource | 0.4% | — | Not comparable |
| Apex ShortlistSource | 9.2% | — | Not comparable |
| FrontierMath v2 (Tiers 1-3)Source | — | 25.860% | Not comparable |
| FrontierMath v2 (Tier 4)Source | — | 6.250% | Not comparable |
Multimodal4 benchmarks
Inst. Following1 benchmarks
| Benchmark | DeepSeek V4 Pro | GPT-5.4 nano | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 75.9% | Not comparable |
Frequently Asked Questions (4)
Which is better, DeepSeek V4 Pro or GPT-5.4 nano?
GPT-5.4 nano is ahead on BenchLM's BenchAlign leaderboard, 66.79 to 60.66. The biggest single separator in this matchup is HLE, where the scores are 7.7% and 37.7%.
Which is better for knowledge tasks, DeepSeek V4 Pro or GPT-5.4 nano?
GPT-5.4 nano has the edge for knowledge tasks in this comparison, averaging 43.8 versus 41.3. Inside this category, HLE is the benchmark that creates the most daylight between them.
Which is better for math, DeepSeek V4 Pro or GPT-5.4 nano?
DeepSeek V4 Pro has the edge for math in this comparison, averaging 31.7 versus 21. GPT-5.4 nano stays close enough that the answer can still flip depending on your workload.
Which is better for agentic tasks, DeepSeek V4 Pro or GPT-5.4 nano?
DeepSeek V4 Pro has the edge for agentic tasks in this comparison, averaging 59.1 versus 42.9. Inside this category, MCP Atlas is the benchmark that creates the most daylight between them.
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