DeepSeek V4 Pro vs Gemini 3.5 Flash
DeepSeek V4 Pro (2026) and Gemini 3.5 Flash (2026) are frontier-tier reasoning models from DeepSeek and Google DeepMind. DeepSeek V4 Pro ships a 1m-token context window, while Gemini 3.5 Flash ships a 1.05m-token context window. On SWE-bench Verified, DeepSeek V4 Pro leads by 2.6 pts. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
DeepSeek V4 Pro is ~245% cheaper at $0.43/1M; pay for Gemini 3.5 Flash only for coding workflow support.
Decision scorecard
Local evidence first| Signal | DeepSeek V4 Pro | Gemini 3.5 Flash |
|---|---|---|
| Best for | reasoning-heavy apps, tool-calling agents, and long-context analysis | reasoning-heavy apps, multimodal apps, and tool-calling agents |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Agents |
| Context window | 1m | 1.05m |
| Cheapest output | $0.87/1M tokens | $9/1M tokens |
| Provider routes | 5 tracked | 4 tracked |
| Shared benchmarks | SWE-bench Verified leader | 8 shared |
Decision tradeoffs
- DeepSeek V4 Pro holds a shared-benchmark lead on SWE-bench Verified, ahead by 2.6 points.
- DeepSeek V4 Pro has the lower cheapest tracked output price at $0.87/1M tokens.
- DeepSeek V4 Pro has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags DeepSeek V4 Pro for Coding, RAG, and Agents.
- Gemini 3.5 Flash holds a shared-benchmark lead on Google-Proof Q&A, ahead by 2.1 points.
- Gemini 3.5 Flash has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Gemini 3.5 Flash uniquely exposes Vision, Multimodal, and Code execution in local model data.
- Local decision data tags Gemini 3.5 Flash for Coding, RAG, and Agents.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
DeepSeek V4 Pro
$566
Cheapest tracked route/tier: DeepSeek Platform
Gemini 3.5 Flash
$3,450
Cheapest tracked route/tier: Google AI Studio
Estimated monthly gap: $2,885. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on Vercel AI Gateway and OpenRouter; start route-level A/B tests there.
- Gemini 3.5 Flash is $8.13/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Gemini 3.5 Flash adds Vision, Multimodal, and Code execution in local capability data.
- Provider overlap exists on OpenRouter and Vercel AI Gateway; start route-level A/B tests there.
- DeepSeek V4 Pro is $8.13/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Vision, Multimodal, and Code execution before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-04-24 | 2026-05-19 |
| Context window | 1m | 1.05m |
| Parameters | 1.6T | — |
| Architecture | Mixture of Experts | Decoder Only |
| License | MITOSI-approved | Proprietary |
| Openness | Open source | Proprietary |
| Weights | Available | Not released |
| Code | Unknown | Unknown |
| Commercial use | Commercial use: permitted | Commercial use: conditional |
| Knowledge cutoff | - | 2025-01 |
Pricing and availability
| Pricing attribute | DeepSeek V4 Pro | Gemini 3.5 Flash |
|---|---|---|
| Input price | $0.43/1M tokens | $1.50/1M tokens |
| Output price | $0.87/1M tokens | $9/1M tokens |
| Providers |
Capabilities
| Capability | DeepSeek V4 Pro | Gemini 3.5 Flash |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | Yes |
| Reasoning | Yes | Yes |
| Function calling | Yes | Yes |
| Tool use | Yes | Yes |
| Structured outputs | Yes | Yes |
| Code execution | No | Yes |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | DeepSeek V4 Pro | Gemini 3.5 Flash |
|---|---|---|
| SWE-bench Verified | 80.6 | 78.0 |
| SWE-bench Pro | 55.4 | 55.1 |
| Google-Proof Q&A | 90.1 | 92.2 |
| Humanity's Last Exam | 37.7 | 40.2 |
| HumanEval | 76.8 | 92.0 |
| Terminal-Bench 2.0 | 59.1 | 76.2 |
| MCP-Atlas | 69.4 | 83.6 |
| GeneBench-Pro | 2.4 | 8.1 |
Deep dive
On shared benchmark coverage, SWE-bench Verified has DeepSeek V4 Pro at 80.6 and Gemini 3.5 Flash at 78, with DeepSeek V4 Pro ahead by 2.6 points; SWE-bench Pro has DeepSeek V4 Pro at 55.4 and Gemini 3.5 Flash at 55.1, with DeepSeek V4 Pro ahead by 0.3 points; Google-Proof Q&A has DeepSeek V4 Pro at 90.1 and Gemini 3.5 Flash at 92.2, with Gemini 3.5 Flash ahead by 2.1 points. The largest visible gap is 2.6 points on SWE-bench Verified, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.
The capability footprint differs most on vision: Gemini 3.5 Flash, multimodal input: Gemini 3.5 Flash, and code execution: Gemini 3.5 Flash. Both models share reasoning mode, function calling, tool use, and structured outputs, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
For cost, DeepSeek V4 Pro lists $0.43/1M input and $0.87/1M output tokens on the cheapest tracked provider, while Gemini 3.5 Flash lists $1.50/1M input and $9/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts DeepSeek V4 Pro lower by about $3.18 per million blended tokens. Availability is 5 providers versus 4, so concentration risk also matters.
Choose DeepSeek V4 Pro when provider fit, lower input-token cost, and broader provider choice are central to the workload. Choose Gemini 3.5 Flash when coding workflow support and larger context windows are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.
FAQ
Which has a larger context window, DeepSeek V4 Pro or Gemini 3.5 Flash?
Gemini 3.5 Flash supports 1.05m tokens, while DeepSeek V4 Pro supports 1m tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, DeepSeek V4 Pro or Gemini 3.5 Flash?
DeepSeek V4 Pro is cheaper on tracked token pricing. DeepSeek V4 Pro costs $0.43/1M input and $0.87/1M output tokens. Gemini 3.5 Flash costs $1.50/1M input and $9/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is DeepSeek V4 Pro or Gemini 3.5 Flash open source?
DeepSeek V4 Pro is listed under MIT. Gemini 3.5 Flash is listed under Proprietary. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for vision, DeepSeek V4 Pro or Gemini 3.5 Flash?
Gemini 3.5 Flash has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for multimodal input, DeepSeek V4 Pro or Gemini 3.5 Flash?
Gemini 3.5 Flash has the clearer documented multimodal input signal in this comparison. If multimodal input is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run DeepSeek V4 Pro and Gemini 3.5 Flash?
DeepSeek V4 Pro is available on DeepSeek Platform, Fireworks AI, OpenRouter, Vercel AI Gateway, and Novita AI. Gemini 3.5 Flash is available on Google AI Studio, GCP Vertex AI, Vercel AI Gateway, and OpenRouter. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-06-29. Data sourced from public model cards and provider documentation.