DeepSeek V4 vs Gemini 3.1 Pro: Which Wins? (April 2026)
DeepSeek V4 vs Gemini 3.1 Pro: Which Wins? (April 2026)
DeepSeek V4 just landed. Google’s Gemini 3.1 Pro has been the multimodal champion for months. Here’s how the two compare on the things that actually matter — coding, reasoning, multimodal, and price — as of April 25, 2026.
Last verified: April 25, 2026
TL;DR
| DeepSeek V4-Pro | Gemini 3.1 Pro | |
|---|---|---|
| Context window | 1M tokens | 1M tokens (2M experimental) |
| Multimodal | Text only | Text, image, video, audio |
| SWE-bench Verified | 80.6% | 76.2% |
| Terminal-Bench 2.0 | 67.9% | 63.4% |
| MMLU-Pro | 83.2% | 84.6% |
| Vision (MMMU) | N/A | 78.4% |
| Input price (per 1M) | $1.74 | $2.50 |
| Output price (per 1M) | $3.48 | $10.00 |
| Open weights | ✅ | ❌ |
| Best for | Coding, cost, self-host | Multimodal, knowledge |
Where DeepSeek V4 wins
1. Coding benchmarks
V4-Pro out-codes Gemini 3.1 Pro across the board:
- SWE-bench Verified: 80.6% vs 76.2%
- Terminal-Bench 2.0: 67.9% vs 63.4%
- LiveCodeBench: 93.5% vs 88.1%
If you’re building a coding agent or doing heavy IDE work, V4-Pro is the better engine.
2. Pricing
V4-Pro at $1.74/$3.48 vs Gemini 3.1 Pro at $2.50/$10.00. On output tokens — where most cost lives — DeepSeek is 2.9× cheaper. On a 100M-token monthly load (50/50 split):
- DeepSeek V4-Pro: $261
- Gemini 3.1 Pro: ~$625
V4-Flash drops the same workload to $21.
3. Open weights
DeepSeek V4 is on Hugging Face. You can self-host, fine-tune, run on Huawei Ascend, or audit the weights. Gemini 3.1 Pro is closed Google API only.
4. Reasoning at depth
V4-Pro slightly edges Gemini 3.1 Pro on GPQA Diamond (78.6% vs 77.1%) and AIME 2026 (88.4% vs 86.2%). Gemini’s reasoning is strong, but DeepSeek’s MoE architecture with 49B active parameters per token is hard to beat at frontier reasoning tasks.
Where Gemini 3.1 Pro wins
1. Multimodal (the big one)
DeepSeek V4 is text-in, text-out. Gemini 3.1 Pro:
- Native image understanding (78.4% MMMU)
- Native video understanding (multi-minute clips)
- Native audio in/out (real-time voice mode)
- Native PDF understanding without OCR
If your app touches images, video, or audio, Gemini 3.1 Pro is your only choice between these two.
2. World knowledge
DeepSeek’s own release notes acknowledge V4 trails Gemini 3.1 Pro on world knowledge benchmarks (MMLU-Pro: 84.6% vs 83.2%). Closer in raw numbers, but Gemini retains the edge.
3. Long context (>500K tokens)
Both support 1M context. In needle-in-haystack tests above 500K tokens, Gemini 3.1 Pro shows slightly less degradation. For 200K and below, they’re basically tied.
4. Google Workspace + ecosystem
Gemini 3.1 Pro plugs into Workspace, Drive, Gmail, Docs, BigQuery, Vertex AI, and Android. If you’re a Google-shop, that integration is worth more than the raw benchmark numbers.
5. Real-time live mode
Gemini’s Live API supports real-time bidirectional streaming with under 200ms voice latency. DeepSeek V4 has no real-time mode.
Architecture differences
DeepSeek V4-Pro
- Type: Mixture-of-Experts
- Total parameters: 1.6T
- Active per token: 49B
- Training: Mix of Nvidia and Huawei Ascend 950 chips
- Modalities: Text only
Gemini 3.1 Pro
- Type: Sparse multimodal transformer
- Parameters: Undisclosed (likely 800B-2T range)
- Active per token: Undisclosed
- Training: Google TPU v5p
- Modalities: Text, image, video, audio (native)
Pricing math: a real product example
Imagine an AI doc search product hitting 200M tokens monthly:
| Component | DeepSeek V4-Pro | Gemini 3.1 Pro |
|---|---|---|
| 100M input ($/M) | $174 | $250 |
| 100M output ($/M) | $348 | $1,000 |
| Monthly total | $522 | $1,250 |
If you can replace half of those calls with V4-Flash (most retrieval is routine):
- 50M input on Flash: $7
- 50M input on Pro: $87
- 50M output on Flash: $14
- 50M output on Pro: $174
- DeepSeek hybrid total: $282
That’s a 4.4× cost reduction vs all-Gemini. The catch is Gemini gives you multimodal for free in that bundle. If you don’t need vision/audio, DeepSeek wins on cost dramatically.
When to pick DeepSeek V4
✅ Building a coding agent or IDE plugin ✅ Pure text workloads ✅ High volume — millions of API calls per month ✅ Open-weight requirement (compliance, audit, self-host) ✅ Deploying in China or on Huawei Ascend ✅ Cost is the primary constraint ✅ You already have multimodal handled elsewhere (Whisper, Vision API)
When to pick Gemini 3.1 Pro
✅ Image, video, or audio inputs are core to the product ✅ Real-time voice agents ✅ Already on Google Cloud / Vertex AI ✅ Google Workspace integration matters ✅ Long-context (>500K) accuracy is critical ✅ World-knowledge-heavy use cases ✅ You want one model that does everything
The hybrid play
For most real apps in 2026, you’ll use both:
- DeepSeek V4 (Flash + Pro) for text-heavy workloads — RAG, code generation, content
- Gemini 3.1 Pro for multimodal — image analysis, audio transcription, video summarization, Workspace tools
Routers like LiteLLM, OpenRouter, and Helicone make this trivial. The era of “pick one model” is over.
What this means
Gemini 3.1 Pro is still the best multimodal frontier model in April 2026. But DeepSeek V4 has compressed the price-quality frontier on text tasks so aggressively that Google’s pricing on Pro is starting to look hard to defend. Expect Google to respond with either Gemini 3.2 (rumored for late Q2) or sharper Flash-tier pricing.
The winners are builders. Picking the right model for the right job has never been cheaper or higher-quality.
Last verified: April 25, 2026. Sources: DeepSeek V4 release notes (api-docs.deepseek.com), Google Gemini 3.1 Pro pricing (cloud.google.com/vertex-ai/pricing), Hugging Face deepseek-ai/DeepSeek-V4-Pro, public benchmarks (LMSYS, Terminal-Bench, SWE-bench Verified leaderboards).