Model comparison
DeepSeek V4 Pro (Max) vs Gemini 3.6 Flash
Head-to-head evidence from 16 shared benchmark results across 4 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Evidence parity. DeepSeek V4 Pro (Max) and Gemini 3.6 Flash share 16 comparable benchmark results. 1 of 8 categories are comparable. 32 results are unique to DeepSeek V4 Pro (Max); 3 to Gemini 3.6 Flash.
Updated July 21, 2026- Shared results
- 16
- DeepSeek V4 Pro (Max) only
- 32
- Gemini 3.6 Flash only
- 3
- Comparable categories
- 1 / 8
Treat this as a split decision. DeepSeek V4 Pro (Max) makes more sense if you want the cheaper token bill; Gemini 3.6 Flash is the better fit if agentic is the priority.
Confidence note. This is a partial-evidence comparison with 16 shared benchmark results across 4 evidence categories; 1 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 Pro (Max) and Gemini 3.6 Flash 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.
Gemini 3.6 Flash is also the more expensive model on tokens at $1.50 input / $7.50 output per 1M tokens, versus $0.43 input / $0.87 output per 1M tokens for DeepSeek V4 Pro (Max). That is roughly 8.6x 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 Pro (Max) | Δ | Gemini 3.6 Flash |
|---|---|---|---|
| Agentic | DeepSeek V4 Pro (Max)74.5 | Margin→ 8.5 | Gemini 3.6 Flash83.0 |
| Coding | DeepSeek V4 Pro (Max)70.9 | MarginNo overlap | Gemini 3.6 FlashNot measured |
| Knowledge | DeepSeek V4 Pro (Max)60.1 | MarginNo overlap | Gemini 3.6 FlashNot measured |
| Math | DeepSeek V4 Pro (Max)95.2 | MarginNo overlap | Gemini 3.6 FlashNot measured |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | DeepSeek V4 Pro (Max) | Gemini 3.6 Flash | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek V4 Pro (Max)$0.435 input / $0.87 output | Gemini 3.6 Flash$1.5 input / $7.5 output | DeepSeek V4 Pro (Max) has the lower combined listed price. |
| Generation speedtokens per second | DeepSeek V4 Pro (Max)Not available | Gemini 3.6 FlashNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | DeepSeek V4 Pro (Max)Not available | Gemini 3.6 FlashNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | DeepSeek V4 Pro (Max)1M | Gemini 3.6 Flash1M | Listed context windows are equal. |
Benchmark Deep Dive
AgenticGemini 3.6 Flash wins18 benchmarks
| Benchmark | DeepSeek V4 Pro (Max) | Gemini 3.6 Flash | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 67.9% | — | Not comparable |
| BrowseCompSource | 83.4% | — | Not comparable |
| HLE w/ toolsSource | 48.2% | — | Not comparable |
| MCP AtlasSource | 73.6% | — | Not comparable |
| GDPval-AASource | 1307 | 1421 | Gemini 3.6 Flash leads |
| ToolathlonSource | 51.8% | — | Not comparable |
| AA Agentic IndexSource | 36.4% | 38.7% | Gemini 3.6 Flash leads |
| APEX-Agents-AASource | 24.3% | — | Not comparable |
| τ²-bench resultsSource | 96.2% | — | Not comparable |
| GDPval-AASource | 40.4% | 46.1% | Gemini 3.6 Flash leads |
| AA BriefcaseSource | 932 | 961 | Gemini 3.6 Flash leads |
| AA EnterpriseOps-GymSource | 40.4% | — | Not comparable |
| AA Harvey LABSource | 84.4% | — | Not comparable |
| AA ITBenchSource | 38.3% | — | Not comparable |
| AA Tau3 BankingSource | 25.8% | 24.5% | DeepSeek V4 Pro (Max) leads |
| terminalBenchHardSource | 46.2% | — | Not comparable |
| aaTerminalBench21Source | 64% | 77.5% | Gemini 3.6 Flash leads |
| OSWorld-VerifiedSource | — | 83% | Not comparable |
Coding9 benchmarks
| Benchmark | DeepSeek V4 Pro (Max) | Gemini 3.6 Flash | Result |
|---|---|---|---|
| CodeforcesSource | 3206.0 | — | Not comparable |
| SWE-bench VerifiedSource | 80.6% | — | Not comparable |
| SWE-bench ProSource | 55.4% | — | Not comparable |
| SWE MultilingualSource | 76.2% | — | Not comparable |
| Terminal-Bench 2.0Source | 67.9% | — | Not comparable |
| Vibe Code BenchSource | 49.93% | — | Not comparable |
| AA Coding IndexSource | 59.4% | 69.2% | Gemini 3.6 Flash leads |
| AA-SciCodeSource | 50.0% | 52.7% | Gemini 3.6 Flash leads |
| deepSweSource | — | 49% | Not comparable |
Reasoning4 benchmarks
Knowledge13 benchmarks
| Benchmark | DeepSeek V4 Pro (Max) | Gemini 3.6 Flash | Result |
|---|---|---|---|
| MMLU-ProSource | 87.5% | — | Not comparable |
| SimpleQASource | 57.9% | — | Not comparable |
| Chinese-SimpleQASource | 84.4% | — | Not comparable |
| GPQASource | 90.1% | — | Not comparable |
| GPQA-DSource | 90.1% | — | Not comparable |
| HLESource | 37.7% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 44.3% | 50.1% | Gemini 3.6 Flash leads |
| AA-GPQA DiamondSource | 88.8% | 92.8% | Gemini 3.6 Flash leads |
| AA-HLESource | 35.9% | 38.3% | Gemini 3.6 Flash leads |
| AA-Omniscience IndexSource | -10.0% | 23.5% | Gemini 3.6 Flash leads |
| AA-Omniscience AccuracySource | 43.3% | 50.2% | Gemini 3.6 Flash leads |
| AA-Omniscience Hallucination RateSource | 94.0% | 53.5% | Gemini 3.6 Flash leads |
| AA Openness IndexSource | 50.0% | — | Not comparable |
Math4 benchmarks
Multimodal2 benchmarks
Inst. Following1 benchmarks
| Benchmark | DeepSeek V4 Pro (Max) | Gemini 3.6 Flash | Result |
|---|---|---|---|
| AA-IFBenchSource | 76.5% | — | Not comparable |
Frequently Asked Questions (2)
Which is better, DeepSeek V4 Pro (Max) or Gemini 3.6 Flash?
DeepSeek V4 Pro (Max) and Gemini 3.6 Flash 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 agentic tasks, DeepSeek V4 Pro (Max) or Gemini 3.6 Flash?
Gemini 3.6 Flash has the edge for agentic tasks in this comparison, averaging 83 versus 74.5. Inside this category, GDPval-AA is the benchmark that creates the most daylight between them.
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