Model comparison
DeepSeek V4 Flash Base vs GPT-5.5
Head-to-head evidence from 0 shared benchmark results across 0 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: DeepSeek V4 Flash Base unranked (Not scored); GPT-5.5 #9 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. DeepSeek V4 Flash Base and GPT-5.5 share 0 comparable benchmark results. 2 of 8 categories are comparable. 24 results are unique to DeepSeek V4 Flash Base; 57 to GPT-5.5.
Updated July 23, 2026- Shared results
- 0
- DeepSeek V4 Flash Base only
- 24
- GPT-5.5 only
- 57
- Comparable categories
- 2 / 8
Treat this as a split decision. DeepSeek V4 Flash Base makes more sense if you would rather avoid the extra latency and token burn of a reasoning model; GPT-5.5 is the better fit if reasoning is the priority or you want the stronger reasoning-first profile.
Confidence note. This is a partial-evidence comparison with 0 shared benchmark results across 0 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
DeepSeek V4 Flash Base and GPT-5.5 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 is the reasoning model in the pair, while DeepSeek V4 Flash Base 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.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | DeepSeek V4 Flash Base | GPT-5.5 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek V4 Flash BaseNot available | GPT-5.5$5 input / $30 output | A complete price comparison is not available. |
| Generation speedtokens per second | DeepSeek V4 Flash BaseNot available | GPT-5.5Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | DeepSeek V4 Flash BaseNot available | GPT-5.5Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | DeepSeek V4 Flash Base1M | GPT-5.51M | Listed context windows are equal. |
Benchmark Deep Dive
Agentic24 benchmarks
| Benchmark | DeepSeek V4 Flash Base | GPT-5.5 | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | — | 82% | Not comparable |
| CyberGymSource | — | 81.8% | Not comparable |
| BrowseCompSource | — | 84.4% | Not comparable |
| OSWorld-VerifiedSource | — | 78.7% | Not comparable |
| MCP AtlasSource | — | 75.3% | Not comparable |
| ToolathlonSource | — | 55.6% | Not comparable |
| τ²-bench resultsSource | — | 93.9% | Not comparable |
| AA Agentic IndexSource | — | 44.9% | Not comparable |
| APEX-Agents-AASource | — | 37.7% | Not comparable |
| GDPval-AASource | — | 49.5% | Not comparable |
| GDPval-AASource | — | 1490 | Not comparable |
| Gert LabsSource | — | 72.93% | Not comparable |
| ResearchClawBenchSource | — | 17.0% | Not comparable |
| OSWorld 2.0Source | — | 13.0% | Not comparable |
| JobBenchSource | — | 42.7% | Not comparable |
| ExploitGymSource | — | 13.4% | Not comparable |
| AA BriefcaseSource | — | 1154 | Not comparable |
| AA AutomationBenchSource | — | 42.1% | Not comparable |
| AA EnterpriseOps-GymSource | — | 46.6% | Not comparable |
| AA Harvey LABSource | — | 86.3% | Not comparable |
| AA ITBenchSource | — | 45.8% | Not comparable |
| AA Tau3 BankingSource | — | 31.3% | Not comparable |
| terminalBenchHardSource | — | 60.6% | Not comparable |
| aaTerminalBench21Source | — | 84.3% | Not comparable |
Coding11 benchmarks
| Benchmark | DeepSeek V4 Flash Base | GPT-5.5 | Result |
|---|---|---|---|
| BigCodeBenchSource | 56.8% | — | Not comparable |
| HumanEvalSource | 69.5% | — | Not comparable |
| SWE-bench ProSource | — | 58.6% | Not comparable |
| Terminal-Bench 2.0Source | — | 82.0% | Not comparable |
| Vibe Code BenchSource | — | 69.85% | Not comparable |
| React Native EvalsSource | — | 84.7% | Not comparable |
| cursorBench31Source | — | 59.2% | Not comparable |
| cursorBench32Source | — | 58.4% | Not comparable |
| AA Coding IndexSource | — | 74.9% | Not comparable |
| AA-SciCodeSource | — | 56.1% | Not comparable |
| FrontierCode 1.1 MainSource | — | 43.0% | Not comparable |
ReasoningGPT-5.5 wins11 benchmarks
| Benchmark | DeepSeek V4 Flash Base | GPT-5.5 | Result |
|---|---|---|---|
| BBHSource | 86.9% | — | Not comparable |
| DROPSource | 88.6% | — | Not comparable |
| HellaSwagSource | 85.7% | — | Not comparable |
| WinoGrandeSource | 79.5% | — | Not comparable |
| CLUEWSCSource | 82.2% | — | Not comparable |
| LongBench v2Source | 44.7% | — | Not comparable |
| MRCR v2 64K-128KSource | — | 83.1% | Not comparable |
| MRCR v2 128K-256KSource | — | 87.5% | Not comparable |
| ARC-AGI-2Source | — | 85% | Not comparable |
| AA-LCRSource | — | 74.3% | Not comparable |
| CritPtSource | — | 27.1% | Not comparable |
KnowledgeGPT-5.5 wins22 benchmarks
| Benchmark | DeepSeek V4 Flash Base | GPT-5.5 | Result |
|---|---|---|---|
| AGIEvalSource | 82.6% | — | Not comparable |
| MMLUSource | 88.7% | — | Not comparable |
| MMLU-ReduxSource | 89.4% | — | Not comparable |
| MMLU-ProSource | 68.3% | — | Not comparable |
| MMMLUSource | 88.8% | — | Not comparable |
| C-EvalSource | 92.1% | — | Not comparable |
| CMMLUSource | 90.4% | — | Not comparable |
| MultiLoKoSource | 42.2% | — | Not comparable |
| SimpleQASource | 30.1% | — | Not comparable |
| SuperGPQASource | 46.5% | — | Not comparable |
| FACTS ParametricSource | 33.9% | — | Not comparable |
| TriviaQASource | 82.8% | — | Not comparable |
| GPQASource | — | 93.6% | Not comparable |
| GPQA-DSource | — | 93.6% | Not comparable |
| HLESource | — | 52.2% | Not comparable |
| HLE w/o toolsSource | — | 41.4% | Not comparable |
| Artificial Analysis Intelligence IndexSource | — | 54.8% | Not comparable |
| AA-GPQA DiamondSource | — | 93.5% | Not comparable |
| AA-HLESource | — | 44.3% | Not comparable |
| AA-Omniscience IndexSource | — | 20.1% | Not comparable |
| AA-Omniscience AccuracySource | — | 56.9% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 85.5% | Not comparable |
Math6 benchmarks
Multilingual1 benchmarks
| Benchmark | DeepSeek V4 Flash Base | GPT-5.5 | Result |
|---|---|---|---|
| MGSMSource | 85.7% | — | Not comparable |
Multimodal5 benchmarks
Inst. Following1 benchmarks
| Benchmark | DeepSeek V4 Flash Base | GPT-5.5 | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 75.9% | Not comparable |
Frequently Asked Questions (3)
Which is better, DeepSeek V4 Flash Base or GPT-5.5?
DeepSeek V4 Flash Base and GPT-5.5 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 Base or GPT-5.5?
GPT-5.5 has the edge for knowledge tasks in this comparison, averaging 57.8 versus 56.4. DeepSeek V4 Flash Base stays close enough that the answer can still flip depending on your workload.
Which is better for reasoning, DeepSeek V4 Flash Base or GPT-5.5?
GPT-5.5 has the edge for reasoning in this comparison, averaging 85 versus 44.7. DeepSeek V4 Flash Base stays close enough that the answer can still flip depending on your workload.
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