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DeepSeek V3.2

DeepSeekfamily · DeepSeek-V3huggingface.co/deepseek-ai/DeepSeek-V3.2

DeepSeek-V3.2 is a large language model designed to harmonize high computational efficiency with strong reasoning and agentic tool-use performance. It introduces DeepSeek Sparse Attention (DSA), a fine-grained sparse attention mechanism...

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data quality68

Updated 7 h ago · first seen 11 Sept 2026

model_01M294WW8H2JQJXMSPY7QTDVWF

Overview

Identity

Identity block not returned by the API for this entity.

Openness

Openness not classified yet — no sourced evidence to place this model in the ontology.

Key facts

Release date

Source:OpenRouter public model & pricing listingT2observed 14 h agomedium

Status

Source:DeepSeek — site & API docsT2observed 14 h agomediumLLM-extracted

Version

Source:DeepSeek — site & API docsT2observed 14 h agomediumLLM-extracted

Paper

Source:DeepSeek — site & API docsT2observed 14 h agomediumLLM-extracted

Repository

Source:DeepSeek — site & API docsT2observed 14 h agomediumLLM-extracted

Openrouter id

Source:OpenRouter public model & pricing listingT2observed 14 h agomedium

Architecture

Architecture

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 14 h agomedium

Model type

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 14 h agomedium

Parameters

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 14 h agomedium

Tokenizer

Source:OpenRouter public model & pricing listingT2observed 14 h agomedium

Weights dtype

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 14 h agomedium

File size

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 14 h agomedium

Library name

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 14 h agomedium

Pipeline tag

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 14 h agomedium

Hugging Face repo

Source:OpenRouter public model & pricing listingT2observed 14 h agomedium

Capabilities

Modalities

Modalities
text
Input
text
Output
text

Capabilities

  • Tool calling

    Yes

    OpenRouter public model & pricing listing · T2

  • Structured output

    Yes

    OpenRouter public model & pricing listing · T2

  • Reasoning

    Yes

    OpenRouter public model & pricing listing · T2

  • Vision

    Unavailable

  • Audio

    Unavailable

  • Fine-tuning available

    Unavailable

Context window

Source:OpenRouter public model & pricing listingT2observed 11 h agomedium

Max output

Source:OpenRouter public model & pricing listingT2observed 14 h agomedium

Tokenizer

Source:OpenRouter public model & pricing listingT2observed 14 h agomedium

Comparable same task and conditions · Partially comparable same task, conditions differ (effort, temperature, judge) · Not comparable different variant or metric

No benchmark results recorded

Results appear when a tier 1–3 source publishes them; we never copy scores without a source.
Current prices per 1M tokens
ProviderInput / 1MOutput / 1MCached inBatch in / outContextObservedSource
DeepSeek APIdeepseek/deepseek-v3.2$0.269$0.40$0.135163.8K6 h agoopenrouter.aiT2

USD per 1M tokens as published by each provider (USD). Rows are append-only: every change is kept in the history below.

Price history

Step lines per provider; amber markers are recorded changes. Click a marker or a row for the evidence behind that price.

Output price · USD / 1M tokens 1 provider

Output price history of DeepSeek V3.2$0$0.10$0.20$0.30$0.40$0.50Sept 26Sept 26Sept 26Sept 26Sept 26Sept 26Sept 26Sept 26DeepSeek API: first observed → $0.40 · 11 Sept 2026
  • DeepSeek API
  • DeepSeek APIfirst observed $0.4011 Sept 2026

Input price · USD / 1M tokens 1 provider

Input price history of DeepSeek V3.2$0$0.10$0.20$0.30$0.40Sept 26Sept 26Sept 26Sept 26Sept 26Sept 26Sept 26Sept 26DeepSeek API: first observed → $0.269 · 11 Sept 2026
  • DeepSeek API
  • DeepSeek APIfirst observed $0.26911 Sept 2026

Hardware fit37

Estimated

3 of 37 device × quantization combinations fit.

Run locally: your machine →
Estimated hardware fit
HardwareQuantizationDevice memoryEst. memoryFits
Apple M3 Ultra4bit394.6 GB est.Yes
Mac Studio (Apple M5 Ultra)4bit394.6 GB est.Yes
NVIDIA DGX B2004bit1,440 GB394.6 GB est.Yes
Apple M2 Ultra4bit394.6 GB est.No
Apple M1 Ultra4bit394.6 GB est.No
Apple M3 Max4bit394.6 GB est.No
Apple M4 Max4bit394.6 GB est.No
Mac Studio (Apple M5 Max)4bit394.6 GB est.No
MacBook Pro (Apple M5 Max)4bit394.6 GB est.No
Apple M2 Max4bit394.6 GB est.No
Apple M1 Max4bit394.6 GB est.No
Apple M4 Pro4bit394.6 GB est.No
Mac mini (Apple M5 Pro)4bit394.6 GB est.No
MacBook Pro (Apple M5 Pro)4bit394.6 GB est.No
Apple M3 Pro4bit394.6 GB est.No
Apple M1 Pro4bit394.6 GB est.No
Apple M2 Pro4bit394.6 GB est.No
Apple M44bit394.6 GB est.No
iMac (Apple M4)4bit394.6 GB est.No
Mac mini (Apple M6)4bit394.6 GB est.No
MacBook Air (Apple M5)4bit394.6 GB est.No
MacBook Pro (Apple M5)4bit394.6 GB est.No
Apple M24bit394.6 GB est.No
Apple M34bit394.6 GB est.No
Apple M14bit394.6 GB est.No
NVIDIA GeForce RTX 30904bit24 GB394.6 GB est.No
NVIDIA GeForce RTX 40904bit24 GB394.6 GB est.No
NVIDIA GeForce RTX 50904bit32 GB394.6 GB est.No
NVIDIA A100 80GB4bit80 GB394.6 GB est.No
NVIDIA H100 SXM4bit80 GB394.6 GB est.No
NVIDIA H100 NVL4bit94 GB394.6 GB est.No
NVIDIA DGX Spark4bit128 GB394.6 GB est.No
NVIDIA H2004bit141 GB394.6 GB est.No
NVIDIA H200 NVL4bit141 GB394.6 GB est.No
NVIDIA B2004bit180 GB394.6 GB est.No
AMD Instinct MI300X4bit192 GB394.6 GB est.No
AMD Instinct MI325X4bit256 GB394.6 GB est.No
Assumptions (6)
  • Estimated, not measured: weights = parameters × bytes/param × 1.15 runtime overhead.
  • bytes/param: 4bit = 0.5, 8bit = 1.0, fp16 = 2.0 (uniform quantization, no per-layer exceptions).
  • KV cache approximated at 0.5 GB per 8 192 tokens of context, independent of architecture (GQA/MLA models need less).
  • A model 'fits' when the estimate is at most the device memory minus 2 GB reserved for the OS and framework.
  • Mixture-of-experts models are estimated on total parameters (all experts must be resident); active parameters are ignored.
  • Device memory uses the largest configuration when several are listed (e.g. Apple silicon tiers).
Explicit derived_from / fine_tuned_from / distilled_from relations stated by sources; artifacts collapsed by kind.
ANCESTORS 1DESCENDANTS 0 · ARTIFACTSDeepSeek-V3.2-Exp-BaseDeepSeekDeepSeek-V3.2-Exp-Base — DeepSeek2 quantizationsartifacts · collapsed2 quantizations — artifacts · collapsedDeepSeek V3.2685.4B params · this modelDeepSeek V3.2 — 685.4B params · this model

Change history34

Temporal, append-only claims: a new observation closes the previous claim instead of overwriting it. Rewind the record with the as-of picker.

Viewing AI Atlas as of 1 Jul 2026 — attributes exactly as the atlas knew them on that day; later corrections are not shown.

Back to today →

DeepSeek V3.2 was not yet in AI Atlas on 1 Jul 2026

First seen 11 Sept 2026. Nothing is inferred backwards: no attribute is shown for dates before the first observation.
34 claims · 34 properties

Release daterelease_date1

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ValueValid from → toStatusSourceConfidenceExtractor
1 Dec 2025currentcurrentOpenRouter public model & pricing listingT2mediumdeterministic

Opennessopenness1

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open-weightscurrentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Licenselicense1

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mitcurrentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Architecturearchitecture1

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ValueValid from → toStatusSourceConfidenceExtractor
DeepseekV32ForCausalLMcurrentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Parametersparameter_count1

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ValueValid from → toStatusSourceConfidenceExtractor
685.4BcurrentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Context windowcontext_length1

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ValueValid from → toStatusSourceConfidenceExtractor
163.8K tokenscurrentcurrentOpenRouter public model & pricing listingT2mediumdeterministic

Max outputmax_output_tokens1

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ValueValid from → toStatusSourceConfidenceExtractor
65.5K tokenscurrentcurrentOpenRouter public model & pricing listingT2mediumdeterministic

Modalitiesmodalities1

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ValueValid from → toStatusSourceConfidenceExtractor
textcurrentcurrentOpenRouter public model & pricing listingT2mediumdeterministic

Input modalitiesmodalities_input1

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ValueValid from → toStatusSourceConfidenceExtractor
textcurrentcurrentOpenRouter public model & pricing listingT2mediumdeterministic

Output modalitiesmodalities_output1

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textcurrentcurrentOpenRouter public model & pricing listingT2mediumdeterministic

Tokenizertokenizer1

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ValueValid from → toStatusSourceConfidenceExtractor
DeepSeekcurrentcurrentOpenRouter public model & pricing listingT2mediumdeterministic

Base modelbase_model1

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ValueValid from → toStatusSourceConfidenceExtractor
deepseek-ai/DeepSeek-V3.2-Exp-BasecurrentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Quantization formatquant_format1

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ValueValid from → toStatusSourceConfidenceExtractor
fp8currentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

File sizefile_size_gb1

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ValueValid from → toStatusSourceConfidenceExtractor
689.5 GBcurrentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Hugging Face repohf_repo1

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deepseek-ai/DeepSeek-V3.2currentcurrentOpenRouter public model & pricing listingT2mediumdeterministic

Pipeline tagpipeline_tag1

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ValueValid from → toStatusSourceConfidenceExtractor
text-generationcurrentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Model cardmodel_card_url1

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https://huggingface.co/deepseek-ai/DeepSeek-V3.2currentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Downloadsmetric.downloads1

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ValueValid from → toStatusSourceConfidenceExtractor
1,732,352currentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Likesmetric.likes1

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1,477currentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Descriptiondescription1

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DeepSeek-V3.2 is a large language model designed to harmonize high computational efficiency with strong reasoning and agentic tool-use performance. It introduces DeepSeek Sparse Attention (DSA), a fine-grained sparse attention mechanism...currentcurrentOpenRouter public model & pricing listingT2mediumdeterministic

Gatedgated1

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ValueValid from → toStatusSourceConfidenceExtractor
NocurrentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Hf inference providershf_inference_providers1

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deepinfra, featherless-ai, novitacurrentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Is quantizedis_quantized1

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YescurrentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Last modifiedlast_modified1

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2025-12-01T11:04:59+00:00currentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Library namelibrary_name1

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transformerscurrentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Downloads all timemetric.downloads_all_time1

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ValueValid from → toStatusSourceConfidenceExtractor
23,362,767currentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Model typemodel_type1

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deepseek_v32currentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Openrouter idopenrouter_id1

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ValueValid from → toStatusSourceConfidenceExtractor
deepseek/deepseek-v3.2currentcurrentOpenRouter public model & pricing listingT2mediumdeterministic

Reasoningreasoning1

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ValueValid from → toStatusSourceConfidenceExtractor
YescurrentcurrentOpenRouter public model & pricing listingT2mediumdeterministic

Structured outputstructured_output1

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YescurrentcurrentOpenRouter public model & pricing listingT2mediumdeterministic

Supported parameterssupported_parameters1

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frequency_penalty, include_reasoning, logit_bias, logprobs, max_tokens, min_p, presence_penalty, reasoning, repetition_penalty, response_format, seed, stop, structured_outputs, temperature, tool_choice, tools, top_k, top_logprobs, top_pcurrentcurrentOpenRouter public model & pricing listingT2mediumdeterministic

Tagstags1

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transformers, safetensors, deepseek_v32, text-generation, fp8currentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Tool callingtool_calling1

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ValueValid from → toStatusSourceConfidenceExtractor
YescurrentcurrentOpenRouter public model & pricing listingT2mediumdeterministic

Weights dtypeweights_dtype1

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ValueValid from → toStatusSourceConfidenceExtractor
BF16, F32, F8_E4M3currentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Claims are temporal and append-only: a new observation closes the previous claim (valid_to) instead of overwriting it. Conflicting claims from different sources are kept side by side and flagged — never averaged. Methodology →

Provenance

Attributed facts

41

Source tiers

T241

Freshest observation

7 h ago

Conflicts

None

Source documents 9

Source documents
SourceDocumentTypeTierLast observedSnapshots
DeepSeek — site & API docsapi-docs.deepseek.com/news/news251201 newsT1· Official14 h ago1
OpenRouter public model & pricing listingopenrouter.ai/api/v1/models catalogueT2· Quality secondary6 h ago6
Hugging Face Hub (public pages, model cards, papers)huggingface.co/deepseek-ai/DeepSeek-V3.2/raw/main/README.md model_cardT2· Quality secondary8 h ago1
Hugging Face Hub (public pages, model cards, papers)huggingface.co/deepseek-ai/DeepSeek-V3.2 model_pageT2· Quality secondary8 h ago4
Hugging Face Hub (public pages, model cards, papers)huggingface.co/cerebras/DeepSeek-V3.2-REAP-345B-A37B model_pageT2· Quality secondary8 h ago5
Hugging Face Hub (public pages, model cards, papers)huggingface.co/cerebras/DeepSeek-V3.2-REAP-508B-A37B model_pageT2· Quality secondary8 h ago5
Hugging Face Hub (public pages, model cards, papers)huggingface.co/models?author=deepseek-ai&p=0&sort=downloads listingT2· Quality secondary8 h ago6
SWE-bench leaderboardsswebench.com/ leaderboardT2· Quality secondary12 h ago1
Artificial Analysisartificialanalysis.ai/leaderboards/models leaderboardT2· Quality secondary12 h ago1

Tier 1 = official/primary, 2 = quality secondary, 3 = community, 4 = unverified. Every snapshot is archived; see all sources and the methodology.

Data quality (68/100) measures how well AI Atlas knows this entity — completeness, primary-source ratio, freshness, conflicts — never how good the model is. Methodology →