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DeepSeek V3.1 vs o3-pro

DeepSeek V3.1 (2026) and o3-pro (2025) are frontier reasoning models from DeepSeek and OpenAI. DeepSeek V3.1 ships a 64K-token context window, while o3-pro ships a not-yet-sourced context window. On pricing, DeepSeek V3.1 costs $0.56/1M input tokens versus $20/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing.

DeepSeek V3.1 is ~3471% cheaper at $0.56/1M; pay for o3-pro only for coding workflow support.

Specs

Released2026-03-012025-06-10
Context window64K
Parameters
Architecturemixture of expertsdecoder only
LicenseOpen SourceProprietary
Knowledge cutoff-2025-08

Pricing and availability

DeepSeek V3.1o3-pro
Input price$0.56/1M tokens$20/1M tokens
Output price$1.68/1M tokens$80/1M tokens
Providers

Capabilities

DeepSeek V3.1o3-pro
Vision
Multimodal
Reasoning
Function calling
Tool use
Structured outputs
Code execution

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint differs most on reasoning mode: o3-pro, function calling: o3-pro, and tool use: o3-pro. Both models share vision, multimodal input, structured outputs, and code execution, 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 V3.1 lists $0.56/1M input and $1.68/1M output tokens, while o3-pro lists $20/1M input and $80/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts DeepSeek V3.1 lower by about $37.10 per million blended tokens. Availability is 6 providers versus 1, so concentration risk also matters.

Choose DeepSeek V3.1 when coding workflow support, lower input-token cost, and broader provider choice are central to the workload. Choose o3-pro when coding workflow support 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. It also helps separate model capability from provider packaging, which can change cost and latency.

FAQ

Which is cheaper, DeepSeek V3.1 or o3-pro?

DeepSeek V3.1 is cheaper on tracked token pricing. DeepSeek V3.1 costs $0.56/1M input and $1.68/1M output tokens. o3-pro costs $20/1M input and $80/1M output tokens. Provider discounts or batch pricing can still change the final bill.

Is DeepSeek V3.1 or o3-pro open source?

DeepSeek V3.1 is listed under Open Source. o3-pro 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 V3.1 or o3-pro?

Both DeepSeek V3.1 and o3-pro expose vision. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

Which is better for multimodal input, DeepSeek V3.1 or o3-pro?

Both DeepSeek V3.1 and o3-pro expose multimodal input. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

Which is better for reasoning mode, DeepSeek V3.1 or o3-pro?

o3-pro has the clearer documented reasoning mode signal in this comparison. If reasoning mode is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Where can I run DeepSeek V3.1 and o3-pro?

DeepSeek V3.1 is available on Microsoft Foundry, Fireworks AI, NVIDIA NIM, Together AI, and AWS Bedrock. o3-pro is available on OpenRouter. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

Last reviewed: 2026-04-24. Data sourced from public model cards and provider documentation.