DeepSeek V3.2
DeepSeekhuggingface.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...
Updated 13 min ago · first seen 11 Sept 2026
model_01M294WW8H2JQJXMSPY7QTDVWF
- Parameters
- 685.4B
- T2 · 15 min ago
- Context
- 163.8K tokens
- T2 · 16 min ago
- Released
- 1 Dec 2025
- T2 · 16 min ago
Specification
- Release date
- 1 Dec 2025
Source:OpenRouter public model & pricing listingT2observed 16 min agomedium
- Openness
- open-weights
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 15 min agomedium
- Parameters
- 685.4B
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 15 min agomedium
- Context window
- 163.8K tokens
Source:OpenRouter public model & pricing listingT2observed 16 min agomedium
- Max output
- 65.5K tokens
Source:OpenRouter public model & pricing listingT2observed 16 min agomedium
- Modalities
- text
Source:OpenRouter public model & pricing listingT2observed 16 min agomedium
- Input modalities
- text
Source:OpenRouter public model & pricing listingT2observed 16 min agomedium
- Output modalities
- text
Source:OpenRouter public model & pricing listingT2observed 16 min agomedium
- Tokenizer
- DeepSeek
Source:OpenRouter public model & pricing listingT2observed 16 min agomedium
- Hugging Face repo
- deepseek-ai/DeepSeek-V3.2
Source:OpenRouter public model & pricing listingT2observed 16 min agomedium
- Pipeline tag
- text-generation
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 15 min agomedium
- Model card
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 15 min agomedium
- Downloads
- 1,732,352
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 13 min agomedium
- Likes
- 1,477
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 13 min agomedium
- Last modified
- 2025-12-01T11:04:59+00:00
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 15 min agomedium
- Openrouter id
- deepseek/deepseek-v3.2
Source:OpenRouter public model & pricing listingT2observed 16 min agomedium
- Supported parameters
- 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_p
Source:OpenRouter public model & pricing listingT2observed 16 min agomedium
Each value shows its source, tier and observation time. Conflicting claims are kept side by side and flagged — never averaged. How AI Atlas records facts →
Provenance
Attributed facts
21
Source tiers
T221
Freshest observation
13 min ago
Conflicts
None
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
- 163.8K tokens
Source:OpenRouter public model & pricing listingT2observed 16 min agomedium
- Max output
- 65.5K tokens
Source:OpenRouter public model & pricing listingT2observed 16 min agomedium
- Tokenizer
- DeepSeek
Source:OpenRouter public model & pricing listingT2observed 16 min agomedium
No benchmark results recorded
Current prices
| Provider | Input / 1M | Output / 1M | Cached in | Batch in / out | Context | Observed | Source |
|---|---|---|---|---|---|---|---|
| DeepSeek APIdeepseek/deepseek-v3.2 | $0.269 | $0.40 | $0.135 | — | 163.8K | 16 min ago | openrouter.aiT2 |
USD per 1M tokens as published by each provider (USD). Rows are append-only: every change is kept in the history below.
Available through 1
Price history
Input price · USD / 1M tokens
Output price · USD / 1M tokens
- DeepSeek API
Memory need = bytes per parameter (4-bit ≈ 0.5 × 1.15 overhead, 8-bit 1.0, fp16 2.0) + a KV-cache allowance. Not a measurement.
| Hardware | Quantization | Memory | Est. need | Fits |
|---|---|---|---|---|
| Apple M3 Ultra | 4bit | — | 394.6 GB | Yes |
| AMD Instinct MI325X | 4bit | 256 GB | 394.6 GB | No |
| AMD Instinct MI300X | 4bit | 192 GB | 394.6 GB | No |
| Apple M2 Ultra | 4bit | — | 394.6 GB | No |
| NVIDIA B200 | 4bit | 180 GB | 394.6 GB | No |
| NVIDIA H200 | 4bit | 141 GB | 394.6 GB | No |
| Apple M1 Ultra | 4bit | — | 394.6 GB | No |
| Apple M3 Max | 4bit | — | 394.6 GB | No |
| Apple M4 Max | 4bit | — | 394.6 GB | No |
| NVIDIA DGX Spark | 4bit | 128 GB | 394.6 GB | No |
| Apple M2 Max | 4bit | — | 394.6 GB | No |
| NVIDIA A100 80GB | 4bit | 80 GB | 394.6 GB | No |
| NVIDIA H100 SXM | 4bit | 80 GB | 394.6 GB | No |
| Apple M1 Max | 4bit | — | 394.6 GB | No |
| Apple M4 Pro | 4bit | — | 394.6 GB | No |
| Apple M3 Pro | 4bit | — | 394.6 GB | No |
| Apple M1 Pro | 4bit | — | 394.6 GB | No |
| Apple M2 Pro | 4bit | — | 394.6 GB | No |
| Apple M4 | 4bit | — | 394.6 GB | No |
| NVIDIA GeForce RTX 5090 | 4bit | 32 GB | 394.6 GB | No |
| Apple M2 | 4bit | — | 394.6 GB | No |
| Apple M3 | 4bit | — | 394.6 GB | No |
| NVIDIA GeForce RTX 3090 | 4bit | 24 GB | 394.6 GB | No |
| NVIDIA GeForce RTX 4090 | 4bit | 24 GB | 394.6 GB | No |
| Apple M1 | 4bit | — | 394.6 GB | No |
Ancestors 0
None recorded.
This model
DeepSeek V3.2
685.4B params
Quantizations 2
Descendants 0
None recorded.
Papers 0
No papers linked yet.
Repositories 0
No repositories linked yet.
As of
Rewind the record: see this entity's attributes exactly as AI Atlas knew them on a given day.
Claim history
Release daterelease_date1
| Value | Valid from → to | Status | Source | Confidence | Extractor |
|---|---|---|---|---|---|
| 1 Dec 2025 | → current | current | OpenRouter public model & pricing listingT2 | medium | deterministic |
Opennessopenness1
| Value | Valid from → to | Status | Source | Confidence | Extractor |
|---|---|---|---|---|---|
| open-weights | → current | current | Hugging Face Hub (public pages, model cards, papers)T2 | medium | deterministic |
Parametersparameter_count1
| Value | Valid from → to | Status | Source | Confidence | Extractor |
|---|---|---|---|---|---|
| 685.4B | → current | current | Hugging Face Hub (public pages, model cards, papers)T2 | medium | deterministic |
Context windowcontext_length1
| Value | Valid from → to | Status | Source | Confidence | Extractor |
|---|---|---|---|---|---|
| 163.8K tokens | → current | current | OpenRouter public model & pricing listingT2 | medium | deterministic |
Max outputmax_output_tokens1
| Value | Valid from → to | Status | Source | Confidence | Extractor |
|---|---|---|---|---|---|
| 65.5K tokens | → current | current | OpenRouter public model & pricing listingT2 | medium | deterministic |
Modalitiesmodalities1
| Value | Valid from → to | Status | Source | Confidence | Extractor |
|---|---|---|---|---|---|
| text | → current | current | OpenRouter public model & pricing listingT2 | medium | deterministic |
Input modalitiesmodalities_input1
| Value | Valid from → to | Status | Source | Confidence | Extractor |
|---|---|---|---|---|---|
| text | → current | current | OpenRouter public model & pricing listingT2 | medium | deterministic |
Output modalitiesmodalities_output1
| Value | Valid from → to | Status | Source | Confidence | Extractor |
|---|---|---|---|---|---|
| text | → current | current | OpenRouter public model & pricing listingT2 | medium | deterministic |
Tokenizertokenizer1
| Value | Valid from → to | Status | Source | Confidence | Extractor |
|---|---|---|---|---|---|
| DeepSeek | → current | current | OpenRouter public model & pricing listingT2 | medium | deterministic |
Hugging Face repohf_repo1
| Value | Valid from → to | Status | Source | Confidence | Extractor |
|---|---|---|---|---|---|
| deepseek-ai/DeepSeek-V3.2 | → current | current | OpenRouter public model & pricing listingT2 | medium | deterministic |
Pipeline tagpipeline_tag1
| Value | Valid from → to | Status | Source | Confidence | Extractor |
|---|---|---|---|---|---|
| text-generation | → current | current | Hugging Face Hub (public pages, model cards, papers)T2 | medium | deterministic |
Model cardmodel_card_url1
| Value | Valid from → to | Status | Source | Confidence | Extractor |
|---|---|---|---|---|---|
| https://huggingface.co/deepseek-ai/DeepSeek-V3.2 | → current | current | Hugging Face Hub (public pages, model cards, papers)T2 | medium | deterministic |
Downloadsmetric.downloads1
| Value | Valid from → to | Status | Source | Confidence | Extractor |
|---|---|---|---|---|---|
| 1,732,352 | → current | current | Hugging Face Hub (public pages, model cards, papers)T2 | medium | deterministic |
Likesmetric.likes1
| Value | Valid from → to | Status | Source | Confidence | Extractor |
|---|---|---|---|---|---|
| 1,477 | → current | current | Hugging Face Hub (public pages, model cards, papers)T2 | medium | deterministic |
Descriptiondescription1
| Value | Valid from → to | Status | Source | Confidence | Extractor |
|---|---|---|---|---|---|
| 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... | → current | current | OpenRouter public model & pricing listingT2 | medium | deterministic |
Last modifiedlast_modified1
| Value | Valid from → to | Status | Source | Confidence | Extractor |
|---|---|---|---|---|---|
| 2025-12-01T11:04:59+00:00 | → current | current | Hugging Face Hub (public pages, model cards, papers)T2 | medium | deterministic |
Openrouter idopenrouter_id1
| Value | Valid from → to | Status | Source | Confidence | Extractor |
|---|---|---|---|---|---|
| deepseek/deepseek-v3.2 | → current | current | OpenRouter public model & pricing listingT2 | medium | deterministic |
Reasoningreasoning1
| Value | Valid from → to | Status | Source | Confidence | Extractor |
|---|---|---|---|---|---|
| Yes | → current | current | OpenRouter public model & pricing listingT2 | medium | deterministic |
Structured outputstructured_output1
| Value | Valid from → to | Status | Source | Confidence | Extractor |
|---|---|---|---|---|---|
| Yes | → current | current | OpenRouter public model & pricing listingT2 | medium | deterministic |
Supported parameterssupported_parameters1
| Value | Valid from → to | Status | Source | Confidence | Extractor |
|---|---|---|---|---|---|
| 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_p | → current | current | OpenRouter public model & pricing listingT2 | medium | deterministic |
Tool callingtool_calling1
| Value | Valid from → to | Status | Source | Confidence | Extractor |
|---|---|---|---|---|---|
| Yes | → current | current | OpenRouter public model & pricing listingT2 | medium | deterministic |
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 →
DeepSeek API lists DeepSeek V3.2 at $0.269 in / $0.4 out per 1M tokens
openrouter
| Source | Document | Type | Tier | Last observed | Snapshots |
|---|---|---|---|---|---|
| Hugging Face Hub (public pages, model cards, papers) | huggingface.co/cerebras/DeepSeek-V3.2-REAP-345B-A37B | model_page | T2· Quality secondary | just now | 1 |
| Hugging Face Hub (public pages, model cards, papers) | huggingface.co/cerebras/DeepSeek-V3.2-REAP-508B-A37B | model_page | T2· Quality secondary | just now | 1 |
| Hugging Face Hub (public pages, model cards, papers) | huggingface.co/models?author=deepseek-ai&p=0&sort=downloads | listing | T2· Quality secondary | 13 min ago | 2 |
| OpenRouter public model & pricing listing | openrouter.ai/api/v1/models | catalogue | T2· Quality secondary | 16 min ago | 1 |
Tier 1 = official/primary, 2 = quality secondary, 3 = community, 4 = unverified. Every snapshot is archived; see all sources and the methodology.