DeepSeek V3.2 Exp
DeepSeek-V3.2-Exp is an experimental large language model released by DeepSeek as an intermediate step between V3.1 and future architectures. It introduces DeepSeek Sparse Attention (DSA), a fine-grained sparse attention mechanism...
Updated 48 min ago · first seen 11 Sept 2026
model_01M294WWB78928015NA9WBEVMF
- Context
- 163.8K tokens
- T2 · 48 min ago
- Released
- 29 Sept 2025
- T2 · 48 min ago
- Knowledge cutoff
- Jul 2025
- T2 · 48 min ago
Specification
- Release date
- 29 Sept 2025
Source:OpenRouter public model & pricing listingT2observed 48 min agomedium
- Context window
- 163.8K tokens
Source:OpenRouter public model & pricing listingT2observed 48 min agomedium
- Max output
- 65.5K tokens
Source:OpenRouter public model & pricing listingT2observed 48 min agomedium
- Knowledge cutoff
- Jul 2025
Source:OpenRouter public model & pricing listingT2observed 48 min agomedium
- Modalities
- text
Source:OpenRouter public model & pricing listingT2observed 48 min agomedium
- Input modalities
- text
Source:OpenRouter public model & pricing listingT2observed 48 min agomedium
- Output modalities
- text
Source:OpenRouter public model & pricing listingT2observed 48 min agomedium
- Tokenizer
- DeepSeek
Source:OpenRouter public model & pricing listingT2observed 48 min agomedium
- Hugging Face repo
- deepseek-ai/DeepSeek-V3.2-Exp
Source:OpenRouter public model & pricing listingT2observed 48 min agomedium
- Instruct type
- deepseek-v3.1
Source:OpenRouter public model & pricing listingT2observed 48 min agomedium
- Openrouter id
- deepseek/deepseek-v3.2-exp
Source:OpenRouter public model & pricing listingT2observed 48 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 48 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
16
Source tiers
T216
Freshest observation
48 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 48 min agomedium
- Max output
- 65.5K tokens
Source:OpenRouter public model & pricing listingT2observed 48 min agomedium
- Knowledge cutoff
- Jul 2025
Source:OpenRouter public model & pricing listingT2observed 48 min agomedium
- Tokenizer
- DeepSeek
Source:OpenRouter public model & pricing listingT2observed 48 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-exp | $0.27 | $0.41 | — | — | 163.8K | 48 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
No hardware estimate available
No lineage 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 · Input modalities
Input modalitiesmodalities_input1
| Value | Valid from → to | Status | Source | Confidence | Extractor |
|---|---|---|---|---|---|
| text | → 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 Exp at $0.27 in / $0.41 out per 1M tokens
openrouter
| Source | Document | Type | Tier | Last observed | Snapshots |
|---|---|---|---|---|---|
| OpenRouter public model & pricing listing | openrouter.ai/api/v1/models | catalogue | T2· Quality secondary | 48 min ago | 1 |
Tier 1 = official/primary, 2 = quality secondary, 3 = community, 4 = unverified. Every snapshot is archived; see all sources and the methodology.