Model comparison
DeepSeek V4 Flash (Max) vs GPT-5.5 Pro
Head-to-head evidence from 3 shared benchmark results across 3 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: DeepSeek V4 Flash (Max) unranked (Not scored); GPT-5.5 Pro #38 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. DeepSeek V4 Flash (Max) and GPT-5.5 Pro share 3 comparable benchmark results. 3 of 8 categories are comparable. 42 results are unique to DeepSeek V4 Flash (Max); 4 to GPT-5.5 Pro.
Updated July 23, 2026- Shared results
- 3
- DeepSeek V4 Flash (Max) only
- 42
- GPT-5.5 Pro only
- 4
- Comparable categories
- 3 / 8
Treat this as a split decision. DeepSeek V4 Flash (Max) makes more sense if mathematics is the priority or you want the cheaper token bill; GPT-5.5 Pro is the better fit if agentic is the priority.
Confidence note. This is a partial-evidence comparison with 3 shared benchmark results across 3 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
DeepSeek V4 Flash (Max) and GPT-5.5 Pro finish on the same BenchAlign overall score, so this is less about a single winner and more about where the edge shows up. The BenchAlign headline says tie; the benchmark table is where the real choice happens.
GPT-5.5 Pro is also the more expensive model on tokens at $30.00 input / $180.00 output per 1M tokens, versus $0.14 input / $0.28 output per 1M tokens for DeepSeek V4 Flash (Max). That is roughly 642.9x on output cost alone.
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 (Max) | Δ | GPT-5.5 Pro |
|---|---|---|---|
| Math | DeepSeek V4 Flash (Max)94.8 | Margin← 46.7 | GPT-5.5 Pro48.1 |
| Agentic | DeepSeek V4 Flash (Max)63.8 | Margin→ 26.3 | GPT-5.5 Pro90.1 |
| Knowledge | DeepSeek V4 Flash (Max)55.3 | Margin→ 1.9 | GPT-5.5 Pro57.2 |
| Coding | DeepSeek V4 Flash (Max)68.8 | MarginNo overlap | GPT-5.5 ProNot measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
HLE
KnowledgeA 34.8%B 57.2%Winner: GPT-5.5 ProΔ 22.4HLE: DeepSeek V4 Flash (Max) scored 34.8%; GPT-5.5 Pro scored 57.2%. GPT-5.5 Pro wins this benchmark. - Source ↗
BrowseComp
AgenticA 73.2%B 90.1%Winner: GPT-5.5 ProΔ 16.9BrowseComp: DeepSeek V4 Flash (Max) scored 73.2%; GPT-5.5 Pro scored 90.1%. GPT-5.5 Pro wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | DeepSeek V4 Flash (Max) | GPT-5.5 Pro | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek V4 Flash (Max)$0.14 input / $0.28 output | GPT-5.5 Pro$30 input / $180 output | DeepSeek V4 Flash (Max) has the lower combined listed price. |
| Generation speedtokens per second | DeepSeek V4 Flash (Max)Not available | GPT-5.5 ProNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | DeepSeek V4 Flash (Max)Not available | GPT-5.5 ProNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | DeepSeek V4 Flash (Max)1M | GPT-5.5 Pro1M | Listed context windows are equal. |
Benchmark Deep Dive
AgenticGPT-5.5 Pro wins15 benchmarks
| Benchmark | DeepSeek V4 Flash (Max) | GPT-5.5 Pro | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 56.9% | — | Not comparable |
| BrowseCompSource | 73.2% | 90.1% | GPT-5.5 Pro leads |
| HLE w/ toolsSource | 45.1% | — | Not comparable |
| MCP AtlasSource | 69% | — | Not comparable |
| GDPval-AASource | 1189 | — | Not comparable |
| ToolathlonSource | 47.8% | — | Not comparable |
| AA Agentic IndexSource | 31.1% | — | Not comparable |
| τ²-bench resultsSource | 95% | — | Not comparable |
| GDPval-AASource | 34.4% | — | Not comparable |
| AA BriefcaseSource | 831 | — | Not comparable |
| AA EnterpriseOps-GymSource | 39.6% | — | Not comparable |
| AA Harvey LABSource | 81.3% | — | Not comparable |
| AA ITBenchSource | 31.5% | — | Not comparable |
| AA Tau3 BankingSource | 22.9% | — | Not comparable |
| terminalBenchHardSource | 35.6% | — | Not comparable |
Coding7 benchmarks
| Benchmark | DeepSeek V4 Flash (Max) | GPT-5.5 Pro | Result |
|---|---|---|---|
| CodeforcesSource | 3052.0 | — | Not comparable |
| SWE-bench VerifiedSource | 79% | — | Not comparable |
| SWE-bench ProSource | 52.6% | — | Not comparable |
| SWE MultilingualSource | 73.3% | — | Not comparable |
| Terminal-Bench 2.0Source | 56.9% | — | Not comparable |
| AA Coding IndexSource | 56.2% | — | Not comparable |
| AA-SciCodeSource | 44.9% | — | Not comparable |
Reasoning4 benchmarks
KnowledgeGPT-5.5 Pro wins14 benchmarks
| Benchmark | DeepSeek V4 Flash (Max) | GPT-5.5 Pro | Result |
|---|---|---|---|
| MMLU-ProSource | 86.2% | — | Not comparable |
| SimpleQASource | 34.1% | — | Not comparable |
| Chinese-SimpleQASource | 78.9% | — | Not comparable |
| GPQASource | 88.1% | — | Not comparable |
| GPQA-DSource | 88.1% | — | Not comparable |
| HLESource | 34.8% | 57.2% | GPT-5.5 Pro leads |
| Artificial Analysis Intelligence IndexSource | 40.3% | — | Not comparable |
| AA-GPQA DiamondSource | 89.4% | — | Not comparable |
| AA-HLESource | 32.1% | — | Not comparable |
| AA-Omniscience IndexSource | -22.9% | — | Not comparable |
| AA-Omniscience AccuracySource | 37.2% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 95.8% | — | Not comparable |
| AA Openness IndexSource | 50.0% | — | Not comparable |
| HLE w/o toolsSource | — | 43.1% | Not comparable |
MathDeepSeek V4 Flash (Max) wins7 benchmarks
| Benchmark | DeepSeek V4 Flash (Max) | GPT-5.5 Pro | Result |
|---|---|---|---|
| HMMT Feb 2026Source | 94.8% | — | Not comparable |
| IMOAnswerBenchSource | 88.4% | — | Not comparable |
| ApexSource | 33.0% | — | Not comparable |
| Apex ShortlistSource | 85.7% | — | Not comparable |
| FrontierMath (legacy)Source | — | 52.4% | Not comparable |
| FrontierMath v2 (Tiers 1-3)Source | — | 51.000% | Not comparable |
| FrontierMath v2 (Tier 4)Source | — | 39.600% | Not comparable |
Multimodal1 benchmarks
| Benchmark | DeepSeek V4 Flash (Max) | GPT-5.5 Pro | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 1238 | — | Not comparable |
Inst. Following1 benchmarks
| Benchmark | DeepSeek V4 Flash (Max) | GPT-5.5 Pro | Result |
|---|---|---|---|
| AA-IFBenchSource | 79.2% | — | Not comparable |
Frequently Asked Questions (4)
Which is better, DeepSeek V4 Flash (Max) or GPT-5.5 Pro?
DeepSeek V4 Flash (Max) and GPT-5.5 Pro are tied on the BenchAlign overall score, so the right pick depends on which category matters most for your use case.
Which is better for knowledge tasks, DeepSeek V4 Flash (Max) or GPT-5.5 Pro?
GPT-5.5 Pro has the edge for knowledge tasks in this comparison, averaging 57.2 versus 55.3. Inside this category, HLE is the benchmark that creates the most daylight between them.
Which is better for math, DeepSeek V4 Flash (Max) or GPT-5.5 Pro?
DeepSeek V4 Flash (Max) has the edge for math in this comparison, averaging 94.8 versus 48.1. GPT-5.5 Pro stays close enough that the answer can still flip depending on your workload.
Which is better for agentic tasks, DeepSeek V4 Flash (Max) or GPT-5.5 Pro?
GPT-5.5 Pro has the edge for agentic tasks in this comparison, averaging 90.1 versus 63.8. Inside this category, BrowseComp is the benchmark that creates the most daylight between them.
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