Model comparison
DeepSeek V4 Pro vs Gemini 3.6 Flash
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 Pro #46 (Supported); Gemini 3.6 Flash unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. DeepSeek V4 Pro and Gemini 3.6 Flash share 0 comparable benchmark results. 1 of 8 categories are comparable. 23 results are unique to DeepSeek V4 Pro; 19 to Gemini 3.6 Flash.
Updated July 21, 2026- Shared results
- 0
- DeepSeek V4 Pro only
- 23
- Gemini 3.6 Flash only
- 19
- Comparable categories
- 1 / 8
Treat this as a split decision. DeepSeek V4 Pro makes more sense if you want the cheaper token bill or you would rather avoid the extra latency and token burn of a reasoning model; Gemini 3.6 Flash is the better fit if agentic 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; 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 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. That is roughly 8.6x on output cost alone. Gemini 3.6 Flash 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.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | DeepSeek V4 Pro | Gemini 3.6 Flash | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek V4 Pro$0.435 input / $0.87 output | Gemini 3.6 Flash$1.5 input / $7.5 output | DeepSeek V4 Pro has the lower combined listed price. |
| Generation speedtokens per second | DeepSeek V4 ProNot available | Gemini 3.6 FlashNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | DeepSeek V4 ProNot available | Gemini 3.6 FlashNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | DeepSeek V4 Pro1M | Gemini 3.6 Flash1M | Listed context windows are equal. |
Benchmark Deep Dive
AgenticGemini 3.6 Flash wins13 benchmarks
| Benchmark | DeepSeek V4 Pro | Gemini 3.6 Flash | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 59.1% | — | Not comparable |
| MCP AtlasSource | 69.4% | — | Not comparable |
| ToolathlonSource | 46.3% | — | Not comparable |
| Claw-EvalSource | 59.8% | — | Not comparable |
| Gert LabsSource | 50.28% | — | Not comparable |
| ResearchClawBenchSource | 17.1% | — | Not comparable |
| OSWorld-VerifiedSource | — | 83% | Not comparable |
| GDPval-AASource | — | 1421 | Not comparable |
| AA Agentic IndexSource | — | 38.7% | Not comparable |
| GDPval-AASource | — | 46.1% | Not comparable |
| AA BriefcaseSource | — | 961 | Not comparable |
| AA Tau3 BankingSource | — | 24.5% | Not comparable |
| aaTerminalBench21Source | — | 77.5% | Not comparable |
Coding7 benchmarks
| Benchmark | DeepSeek V4 Pro | Gemini 3.6 Flash | 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 |
| deepSweSource | — | 49% | Not comparable |
| AA Coding IndexSource | — | 69.2% | Not comparable |
| AA-SciCodeSource | — | 52.7% | Not comparable |
Reasoning4 benchmarks
Knowledge12 benchmarks
| Benchmark | DeepSeek V4 Pro | Gemini 3.6 Flash | Result |
|---|---|---|---|
| MMLU-ProSource | 82.9% | — | Not comparable |
| SimpleQASource | 45% | — | Not comparable |
| Chinese-SimpleQASource | 75.8% | — | Not comparable |
| GPQASource | 72.9% | — | Not comparable |
| GPQA-DSource | 72.9% | — | Not comparable |
| HLESource | 7.7% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | — | 50.1% | Not comparable |
| AA-GPQA DiamondSource | — | 92.8% | Not comparable |
| AA-HLESource | — | 38.3% | Not comparable |
| AA-Omniscience IndexSource | — | 23.5% | Not comparable |
| AA-Omniscience AccuracySource | — | 50.2% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 53.5% | Not comparable |
Math4 benchmarks
Frequently Asked Questions (2)
Which is better, DeepSeek V4 Pro or Gemini 3.6 Flash?
DeepSeek V4 Pro 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 or Gemini 3.6 Flash?
Gemini 3.6 Flash has the edge for agentic tasks in this comparison, averaging 83 versus 59.1. DeepSeek V4 Pro stays close enough that the answer can still flip depending on your workload.
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