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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 1M-token context window. On pricing, DeepSeek V4 Pro costs $0.43/1M input tokens versus $1.5/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.

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
SignalDeepSeek V4 ProGemini 3.5 Flash
Decision fitCoding, RAG, and AgentsCoding, RAG, and Agents
Context window1M1M
Cheapest output$0.87/1M tokens$9/1M tokens
Provider routes3 tracked2 tracked
Shared benchmarks0 rows0 rows

Decision tradeoffs

Choose DeepSeek V4 Pro when...
  • 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.
Choose Gemini 3.5 Flash when...
  • 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 prices on this page.

Lower estimate DeepSeek V4 Pro

DeepSeek V4 Pro

$566

Cheapest tracked route: DeepSeek Platform

Gemini 3.5 Flash

$3,450

Cheapest tracked route: Google AI Studio

Estimated monthly gap: $2,885. Batch, cache, and negotiated pricing are excluded from this local estimate.

Switch friction

DeepSeek V4 Pro -> Gemini 3.5 Flash
  • No overlapping tracked provider route is sourced for DeepSeek V4 Pro and Gemini 3.5 Flash; plan for SDK, billing, or endpoint changes.
  • 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.
Gemini 3.5 Flash -> DeepSeek V4 Pro
  • No overlapping tracked provider route is sourced for Gemini 3.5 Flash and DeepSeek V4 Pro; plan for SDK, billing, or endpoint changes.
  • 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
Released2026-04-242026-05-19
Context window1M1M
Parameters1.6T
Architecturemixture of expertsdecoder only
LicenseMITProprietary
Knowledge cutoff-2025-01

Pricing and availability

Pricing attributeDeepSeek V4 ProGemini 3.5 Flash
Input price$0.43/1M tokens$1.5/1M tokens
Output price$0.87/1M tokens$9/1M tokens
Providers

Capabilities

CapabilityDeepSeek V4 ProGemini 3.5 Flash
VisionNoYes
MultimodalNoYes
ReasoningYesYes
Function callingYesYes
Tool useYesYes
Structured outputsYesYes
Code executionNoYes

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

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, while Gemini 3.5 Flash lists $1.5/1M 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 3 providers versus 2, 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. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions.

FAQ

Which has a larger context window, DeepSeek V4 Pro or Gemini 3.5 Flash?

Gemini 3.5 Flash supports 1M 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 $1.5/1M 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, and OpenRouter. Gemini 3.5 Flash is available on Google AI Studio and GCP Vertex AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

Last reviewed: 2026-05-19. Data sourced from public model cards and provider documentation.