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DeepSeek V3.2 vs GPT-5.5

DeepSeek V3.2 (2025) and GPT-5.5 (2026) are frontier reasoning models from DeepSeek and OpenAI. DeepSeek V3.2 ships a 160K-token context window, while GPT-5.5 ships a 1M-token context window. On Google-Proof Q&A, GPT-5.5 leads by 9.6 pts. On pricing, DeepSeek V3.2 costs $0.26/1M input tokens versus $5/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.

DeepSeek V3.2 is ~1831% cheaper at $0.26/1M; pay for GPT-5.5 only for coding workflow support.

Specs

Released2025-01-012026-04-23
Context window160K1M
Parameters671B
Architecturedecoder onlydecoder only
LicenseOpen SourceProprietary
Knowledge cutoff--

Pricing and availability

DeepSeek V3.2GPT-5.5
Input price$0.26/1M tokens$5/1M tokens
Output price$0.42/1M tokens$30/1M tokens
Providers

Capabilities

DeepSeek V3.2GPT-5.5
Vision
Multimodal
Reasoning
Function calling
Tool use
Structured outputs
Code execution

Benchmarks

BenchmarkDeepSeek V3.2GPT-5.5
Google-Proof Q&A84.093.6

Deep dive

On shared benchmark coverage, Google-Proof Q&A has DeepSeek V3.2 at 84 and GPT-5.5 at 93.6, with GPT-5.5 ahead by 9.6 points. The largest visible gap is 9.6 points on Google-Proof Q&A, 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: GPT-5.5, multimodal input: GPT-5.5, reasoning mode: GPT-5.5, function calling: GPT-5.5, and tool use: GPT-5.5. Both models share 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 V3.2 lists $0.26/1M input and $0.42/1M output tokens, while GPT-5.5 lists $5/1M input and $30/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts DeepSeek V3.2 lower by about $12.19 per million blended tokens. Availability is 4 providers versus 1, so concentration risk also matters.

Choose DeepSeek V3.2 when coding workflow support, lower input-token cost, and broader provider choice are central to the workload. Choose GPT-5.5 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 V3.2 or GPT-5.5?

GPT-5.5 supports 1M tokens, while DeepSeek V3.2 supports 160K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

Which is cheaper, DeepSeek V3.2 or GPT-5.5?

DeepSeek V3.2 is cheaper on tracked token pricing. DeepSeek V3.2 costs $0.26/1M input and $0.42/1M output tokens. GPT-5.5 costs $5/1M input and $30/1M output tokens. Provider discounts or batch pricing can still change the final bill.

Is DeepSeek V3.2 or GPT-5.5 open source?

DeepSeek V3.2 is listed under Open Source. GPT-5.5 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 V3.2 or GPT-5.5?

GPT-5.5 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. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

Which is better for multimodal input, DeepSeek V3.2 or GPT-5.5?

GPT-5.5 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 V3.2 and GPT-5.5?

DeepSeek V3.2 is available on Fireworks AI, NVIDIA NIM, AWS Bedrock, and OpenRouter. GPT-5.5 is available on OpenAI API. 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.