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DeepSeek

DeepSeek V3.2

DeepSeek V3.2 is a chat-oriented large language model from DeepSeek, continuing the company's DeepSeek V3 line of general-purpose assistant models.

Input from
$0.250 / 1M tokens
across 7 providers

API Pricing

Cheapest on DigitalOcean 49% below avg
ProviderInput / 1MOutput / 1MCached / 1M
$0.250$0.800$0.075
$0.260$0.380$0.130
$0.269$0.400$0.135
$0.270$0.410-
$0.300$0.450-
$0.620$1.85-
$1.43$2.41$0.715

Prices updated daily. Last check: Sep 1, 2026

DeepSeek V3.2 pricing by provider

Input, output, and batch rates, plus alternatives, for one provider at a time.

Performance & Benchmarks

Source: Artificial Analysis →
Intelligence
25.1 / 100
Math
59.0 / 100

Reasoning & Knowledge

  • MMLU-Pro83.7%
  • GPQA Diamond75.1%
  • Humanity's Last Exam11.2%

Coding

  • LiveCodeBench59.3%
  • SciCode38.7%

Math

  • AIME 202559.0%

Agentic & Tool Use

  • Terminal-Bench Hard32.6%
  • τ²-bench78.9%

Instruction & Long Context

  • IFBench49.0%
  • Long-Context Reasoning42.7%

Benchmarks measured Sep 2026. Scores are independent evaluations, not vendor-reported.

Model Details

General

Creator
DeepSeek
Family
DeepSeek
Modalities
Text

Capabilities

Tool Calling
No
Open Source
No

Strengths & Limitations

Strengths

  • Part of the DeepSeek V3 model line, so prompts and integration patterns generally carry over from earlier DeepSeek V3 releases
  • Typically available from multiple inference providers, allowing side-by-side comparison of latency and cost on the pricing table
  • General-purpose chat and instruction-following design suitable for a broad mix of workloads rather than a single narrow task
  • DeepSeek models are widely used for code assistance and technical Q&A, a common strength of the V3 lineage
  • Multi-provider availability reduces single-vendor dependency for production deployments
  • Standard chat-completions style API surface at most hosts, easing migration from other chat models

Limitations

  • We do not have a confirmed context window length recorded for this release, so effective input limits must be verified with the serving provider
  • No published benchmark scores are tracked in our database for DeepSeek V3.2, making direct quality comparisons harder
  • Reported throughput and time-to-first-token figures are not populated, so latency expectations must be measured per provider
  • Feature support such as tool calling, JSON mode, or vision input is not confirmed in our metadata and may vary by endpoint
  • Performance and quotas can differ substantially between providers serving the same model weights

Key Features

Chat completions interface for multi-turn dialogue
Instruction-following and general text generation
Code generation and code explanation, a common use of the DeepSeek V3 line
Availability across multiple inference providers listed on this page
Part of the DeepSeek family, with sibling models available for capability and cost comparison
Provider-dependent configuration for context length and generation limits

About DeepSeek V3.2

DeepSeek V3.2 is a text chat model developed by DeepSeek, the Chinese AI lab behind the DeepSeek V3 and DeepSeek R1 model lines. It sits in the DeepSeek family as an iteration on the V3 series, positioned as a general-purpose conversational and instruction-following model rather than a specialized reasoning-only or task-specific release. As a chat model, DeepSeek V3.2 is intended for multi-turn dialogue, instruction following, code assistance, and general text generation. Our catalog does not currently track a confirmed context window length, modality list, or published benchmark scores for this specific release, and the throughput and time-to-first-token figures we have from Artificial Analysis are not populated with usable values. Because DeepSeek models are typically served by several independent inference providers in addition to DeepSeek's own API, the practical context limit, token throughput, and feature support (such as tool calling or structured output) can differ from one endpoint to another — check the provider's own documentation before committing to an integration. In practice, DeepSeek models are commonly chosen by teams comparing serving options across multiple hosts, since availability on several inference platforms creates competitive pricing and lets users switch endpoints without changing model families. If you are evaluating DeepSeek V3.2, the most useful comparison points are the other DeepSeek entries in this catalog and any provider-specific serving details, since those — not the model name alone — determine latency, quotas, and per-request limits.

Common Use Cases

DeepSeek V3.2 fits general-purpose assistant workloads: conversational interfaces, drafting and rewriting text, summarization, question answering over supplied context, and code assistance such as generating snippets, explaining unfamiliar code, or writing tests. Because DeepSeek models are commonly served by several independent providers, it is a reasonable candidate for teams that want to benchmark the same model across endpoints and route traffic to whichever offers the best latency or cost for their region. For workloads that depend on very long documents, image input, or strict tool-calling behavior, confirm with the chosen provider that the endpoint supports those requirements, since our metadata does not record them for this release.

Frequently Asked Questions

How much does DeepSeek V3.2 cost to use?

Pricing depends on which provider serves the model and on the pricing type — input tokens, output tokens, cached input, and batch or dedicated capacity are billed differently. Rates also change frequently as providers compete. Use the pricing table on this page to compare current per-provider rates.

What is DeepSeek V3.2 best used for?

It is a general-purpose chat model, so it suits conversational assistants, instruction-following tasks, summarization, question answering, and code assistance. It is a reasonable default for mixed workloads where you want one model to handle both text and light coding tasks.

What context window does DeepSeek V3.2 support?

We do not have a confirmed context window recorded for this release in our database, and the usable limit can also be capped by the individual serving provider. Check the documentation of the provider you plan to use before designing long-context prompts.

How does DeepSeek V3.2 compare to other DeepSeek models?

It continues the DeepSeek V3 line of general-purpose chat models, as distinct from DeepSeek's reasoning-focused R1 releases, which spend additional tokens on explicit chain-of-thought before answering. If your workload is math- or logic-heavy, compare against a reasoning-tier DeepSeek entry; for everyday chat and coding, the V3 line is the more direct fit.

Does DeepSeek V3.2 support tool calling or image input?

Our metadata does not record confirmed support for tool calling, structured output, or vision input for this release. Feature availability often depends on the specific inference provider, so verify against the endpoint's API documentation before building on those capabilities.