DeepSeek V4 vs Gemini 3.1 Pro: How Do They Compare?
DeepSeek V4-Pro and Google's Gemini-3.1-Pro are two of the most capable AI models available in 2026, each with distinct strengths. Gemini-3.1-Pro is Google's leading closed-source frontier model; DeepSeek V4-Pro is the world's most powerful open-weight model. Here's a comprehensive head-to-head.
At a Glance
| Feature | DeepSeek V4-Pro | Gemini-3.1-Pro |
|---|---|---|
| Developer | DeepSeek | Google DeepMind |
| Total Parameters | 1.6T (MoE) | Undisclosed |
| Context Window | 1M tokens | 1M tokens |
| API Input Price | $1.74 / 1M tokens | Estimated ~$3-7 / 1M tokens |
| Open Weights | ✅ Yes (MIT) | ❌ No |
| Architecture | MoE + Hybrid Attention | Undisclosed (MoE suspected) |
| Multimodal | Text-only at V4 launch | ✅ Text, image, video, audio |
Benchmark Comparison
Knowledge and Reasoning
| Benchmark | DeepSeek V4-Pro Max | Gemini-3.1-Pro High |
|---|---|---|
| MMLU-Pro (EM) | 87.5% | 91.0% |
| GPQA Diamond (Pass@1) | 90.1% | 94.3% |
| HLE (Pass@1) | 37.7% | 44.4% |
| SimpleQA-Verified | 57.9% | 75.6%* |
| Apex Shortlist | 90.2% | 89.1% |
| HMMT 2026 Feb | 95.2% | 94.7% |
| IMOAnswerBench | 89.8% | 81.0% |
*Gemini-3.1-Pro's SimpleQA-Verified score of 75.6% is notably higher, reflecting Google's significant investment in factual world knowledge retrieval.
Analysis: Gemini-3.1-Pro leads on MMLU-Pro, GPQA Diamond, and HLE — the established academic science and reasoning benchmarks. However, DeepSeek V4-Pro leads on Apex Shortlist, HMMT, and IMOAnswerBench, suggesting stronger performance on the harder mathematical reasoning tasks.
Coding
| Benchmark | DeepSeek V4-Pro Max | Gemini-3.1-Pro High |
|---|---|---|
| LiveCodeBench (Pass@1) | 93.5% | 91.7% |
| Codeforces Rating | 3206 | 3052 |
| SWE-bench Pro | 55.4% | 54.2% |
| SWE-bench Verified | 80.6% | 80.6% |
Analysis: DeepSeek V4-Pro leads Gemini on coding tasks — particularly competitive programming (Codeforces 3206 vs 3052) and LiveCodeBench (93.5% vs 91.7%). The SWE-bench Verified tie (both 80.6%) shows these models are essentially equivalent on real-world code patch application.
Long-Context
| Benchmark | DeepSeek V4-Pro Max | Gemini-3.1-Pro High |
|---|---|---|
| MRCR 1M (MMR) | 83.5% | 76.3% |
| CorpusQA 1M (ACC) | 62.0% | 53.8% |
Analysis: Surprisingly, DeepSeek V4-Pro significantly outperforms Gemini-3.1-Pro on both 1M-token long-context benchmarks. This is a major result — it suggests that DeepSeek's Hybrid Attention Architecture (CSA + HCA) is actually superior to Gemini's long-context approach on these specific tasks.
Agentic Tasks
| Benchmark | DeepSeek V4-Pro Max | Gemini-3.1-Pro High |
|---|---|---|
| Terminal Bench 2.0 | 67.9% | 68.5% |
| SWE-bench Pro | 55.4% | 54.2% |
| BrowseComp | 83.4% | 85.9% |
| MCPAtlas Public | 73.6% | 69.2% |
| Toolathlon | 51.8% | 48.8% |
Analysis: These two models are extremely competitive on agentic tasks. Gemini leads on browsing tasks; DeepSeek leads on MCPAtlas and Toolathlon. Terminal Bench 2.0 is essentially tied.
Pricing Comparison
While Gemini-3.1-Pro's exact pricing hasn't been specified, Google Gemini models have historically been priced in the $3–7/M input, $9–21/M output range for their top-tier models.
At DeepSeek V4-Pro's $1.74/$3.48 pricing, it likely represents 2–4× cost savings over Gemini-3.1-Pro's API at equivalent capability levels.
V4-Flash at $0.14/$0.28 is dramatically cheaper still — delivering near-Pro performance at a fraction of the cost of any Gemini offering.
The Open-Weight Advantage
The most fundamental difference between these two models is accessibility:
| Factor | DeepSeek V4-Pro | Gemini-3.1-Pro |
|---|---|---|
| Weight Access | ✅ Public (HuggingFace, MIT) | ❌ API only |
| Self-hosting | ✅ Yes | ❌ No |
| Fine-tuning | ✅ Yes | ❌ No (limited fine-tuning service only) |
| Data privacy | ✅ Full (self-hosted) | Depends on Google Cloud agreements |
| Offline use | ✅ Yes | ❌ No |
For organizations that need complete data sovereignty or want to fine-tune for domain expertise, DeepSeek V4 is the only viable choice.
Multimodal: Gemini's Structural Advantage
One clear area where Gemini-3.1-Pro has a significant advantage is native multimodality. Gemini can natively process:
- Images
- Video
- Audio
- Text
DeepSeek V4 at launch is text-only. For tasks that require understanding images, analyzing videos, or processing audio alongside text, Gemini remains the only frontier-class option that handles all modalities in a single model.
For pure text workflows — which represent the majority of enterprise and developer use cases — this limitation doesn't matter. But for platforms like Framia.pro that handle creative workflows involving images and video, a combination of DeepSeek V4 for text reasoning and specialized image/video models represents the current state of the art.
When to Choose Each Model
Choose DeepSeek V4-Pro when:
- ✅ You need open weights for privacy or fine-tuning
- ✅ Coding is your primary use case
- ✅ Long-context document processing is critical
- ✅ Cost is a significant factor
- ✅ You want self-hosting capability
- ✅ Text-only workflows cover your needs
Choose Gemini-3.1-Pro when:
- ✅ You need native multimodal understanding (image, video, audio)
- ✅ Academic/scientific knowledge depth is paramount
- ✅ Google Cloud ecosystem integration matters
- ✅ You need Google's safety and content policy guarantees
- ✅ Simple QA and world knowledge precision at the absolute frontier
Summary Scorecard
| Category | Winner |
|---|---|
| Coding | DeepSeek V4-Pro |
| Long-context retrieval | DeepSeek V4-Pro |
| Scientific reasoning | Gemini-3.1-Pro |
| World knowledge | Gemini-3.1-Pro |
| Multimodal | Gemini-3.1-Pro (V4 is text-only) |
| Price | DeepSeek V4-Pro |
| Open weights | DeepSeek V4-Pro |
| Agentic tasks | Tie |
Conclusion
DeepSeek V4-Pro and Gemini-3.1-Pro are genuinely competitive at the frontier of AI capabilities. V4-Pro leads on coding, long-context processing, and cost; Gemini-3.1-Pro leads on scientific knowledge, multimodality, and factual accuracy. For developers and enterprises prioritizing text-based workflows at the best value — particularly coding and document processing — DeepSeek V4-Pro is the compelling choice.