Model comparison
DeepSeek V4 Flash (Max) vs GPT-5.2
Head-to-head evidence from 16 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: DeepSeek V4 Flash (Max) unranked (Not scored); GPT-5.2 #64 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. DeepSeek V4 Flash (Max) and GPT-5.2 share 16 comparable benchmark results. 4 of 8 categories are comparable. 29 results are unique to DeepSeek V4 Flash (Max); 12 to GPT-5.2.
Updated July 23, 2026- Shared results
- 16
- DeepSeek V4 Flash (Max) only
- 29
- GPT-5.2 only
- 12
- Comparable categories
- 4 / 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-5.2 is the better fit if knowledge is the priority.
Confidence note. This is a partial-evidence comparison with 16 shared benchmark results across 6 evidence categories; 4 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-5.2 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-5.2 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 (Max). That is roughly 50.0x on output cost alone. DeepSeek V4 Flash (Max) gives you the larger context window at 1M, compared with 400K for GPT-5.2.
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-5.2 |
|---|---|---|---|
| Math | DeepSeek V4 Flash (Max)94.8 | Margin← 59.6 | GPT-5.235.2 |
| Knowledge | DeepSeek V4 Flash (Max)55.3 | Margin→ 37.1 | GPT-5.292.4 |
| Agentic | DeepSeek V4 Flash (Max)63.8 | Margin← 8.1 | GPT-5.255.7 |
| Coding | DeepSeek V4 Flash (Max)68.8 | Margin→ 1.8 | GPT-5.270.6 |
| Reasoning | DeepSeek V4 Flash (Max)Not measured | MarginNo overlap | GPT-5.252.9 |
| Multimodal | DeepSeek V4 Flash (Max)Not measured | MarginNo overlap | GPT-5.280.4 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
BrowseComp
AgenticA 73.2%B 65.8%Winner: DeepSeek V4 Flash (Max)Δ 7.4BrowseComp: DeepSeek V4 Flash (Max) scored 73.2%; GPT-5.2 scored 65.8%. DeepSeek V4 Flash (Max) wins this benchmark. - Source ↗
GPQA
KnowledgeA 88.1%B 92.4%Winner: GPT-5.2Δ 4.3GPQA: DeepSeek V4 Flash (Max) scored 88.1%; GPT-5.2 scored 92.4%. GPT-5.2 wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 52.6%B 55.6%Winner: GPT-5.2Δ 3SWE-bench Pro: DeepSeek V4 Flash (Max) scored 52.6%; GPT-5.2 scored 55.6%. GPT-5.2 wins this benchmark. - Source ↗
SWE-bench Verified
CodingA 79%B 80%Winner: GPT-5.2Δ 1SWE-bench Verified: DeepSeek V4 Flash (Max) scored 79%; GPT-5.2 scored 80%. GPT-5.2 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-5.2 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek V4 Flash (Max)$0.14 input / $0.28 output | GPT-5.2$1.75 input / $14 output | DeepSeek V4 Flash (Max) has the lower combined listed price. |
| Generation speedtokens per second | DeepSeek V4 Flash (Max)Not available | GPT-5.273 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | DeepSeek V4 Flash (Max)Not available | GPT-5.2130.34 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | DeepSeek V4 Flash (Max)1M | GPT-5.2400K | DeepSeek V4 Flash (Max) lists the larger context window. |
Benchmark Deep Dive
AgenticDeepSeek V4 Flash (Max) wins18 benchmarks
| Benchmark | DeepSeek V4 Flash (Max) | GPT-5.2 | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 56.9% | — | Not comparable |
| BrowseCompSource | 73.2% | 65.8% | DeepSeek V4 Flash (Max) 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% | 84.8% | DeepSeek V4 Flash (Max) leads |
| 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 |
| OSWorld-VerifiedSource | — | 47.3% | Not comparable |
| Gert LabsSource | — | 46.54% | Not comparable |
| JobBenchSource | — | 34.3% | Not comparable |
CodingGPT-5.2 wins8 benchmarks
| Benchmark | DeepSeek V4 Flash (Max) | GPT-5.2 | Result |
|---|---|---|---|
| CodeforcesSource | 3052.0 | — | Not comparable |
| SWE-bench VerifiedSource | 79% | 80% | GPT-5.2 leads |
| SWE-bench ProSource | 52.6% | 55.6% | GPT-5.2 leads |
| 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% | 52.1% | GPT-5.2 leads |
| Vibe Code BenchSource | — | 53.50% | Not comparable |
Reasoning5 benchmarks
KnowledgeGPT-5.2 wins13 benchmarks
| Benchmark | DeepSeek V4 Flash (Max) | GPT-5.2 | Result |
|---|---|---|---|
| MMLU-ProSource | 86.2% | — | Not comparable |
| SimpleQASource | 34.1% | — | Not comparable |
| Chinese-SimpleQASource | 78.9% | — | Not comparable |
| GPQASource | 88.1% | 92.4% | GPT-5.2 leads |
| GPQA-DSource | 88.1% | — | Not comparable |
| HLESource | 34.8% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 40.3% | 42.2% | GPT-5.2 leads |
| AA-GPQA DiamondSource | 89.4% | 90.3% | GPT-5.2 leads |
| AA-HLESource | 32.1% | 35.4% | GPT-5.2 leads |
| AA-Omniscience IndexSource | -22.9% | -1.0% | GPT-5.2 leads |
| AA-Omniscience AccuracySource | 37.2% | 43.8% | GPT-5.2 leads |
| AA-Omniscience Hallucination RateSource | 95.8% | 79.7% | GPT-5.2 leads |
| AA Openness IndexSource | 50.0% | — | Not comparable |
MathDeepSeek V4 Flash (Max) wins7 benchmarks
| Benchmark | DeepSeek V4 Flash (Max) | GPT-5.2 | Result |
|---|---|---|---|
| HMMT Feb 2026Source | 94.8% | — | Not comparable |
| IMOAnswerBenchSource | 88.4% | — | Not comparable |
| ApexSource | 33.0% | — | Not comparable |
| Apex ShortlistSource | 85.7% | — | Not comparable |
| AA AIME 2025Source | — | 99.0% | Not comparable |
| FrontierMath v2 (Tiers 1-3)Source | — | 40.700% | Not comparable |
| FrontierMath v2 (Tier 4)Source | — | 18.800% | Not comparable |
Multimodal5 benchmarks
Inst. Following1 benchmarks
| Benchmark | DeepSeek V4 Flash (Max) | GPT-5.2 | Result |
|---|---|---|---|
| AA-IFBenchSource | 79.2% | 75.4% | DeepSeek V4 Flash (Max) leads |
Frequently Asked Questions (5)
Which is better, DeepSeek V4 Flash (Max) or GPT-5.2?
DeepSeek V4 Flash (Max) and GPT-5.2 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-5.2?
GPT-5.2 has the edge for knowledge tasks in this comparison, averaging 92.4 versus 55.3. Inside this category, AA-Omniscience Index is the benchmark that creates the most daylight between them.
Which is better for coding, DeepSeek V4 Flash (Max) or GPT-5.2?
GPT-5.2 has the edge for coding in this comparison, averaging 70.6 versus 68.8. Inside this category, AA-SciCode is the benchmark that creates the most daylight between them.
Which is better for math, DeepSeek V4 Flash (Max) or GPT-5.2?
DeepSeek V4 Flash (Max) has the edge for math in this comparison, averaging 94.8 versus 35.2. GPT-5.2 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-5.2?
DeepSeek V4 Flash (Max) has the edge for agentic tasks in this comparison, averaging 63.8 versus 55.7. Inside this category, τ²-bench results is the benchmark that creates the most daylight between them.
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