DeepSeek V3.1
DeepSeekfamily · DeepSeekchat.deepseek.com
DeepSeek-V3.1 is a large hybrid reasoning model (671B parameters, 37B active) that supports both thinking and non-thinking modes via prompt templates. It extends the DeepSeek-V3 base with a two-phase long-context...
Updated 5 h ago · first seen 11 Sept 2026
model_01M294WWCNME74MRVVP3J0Y4C3
Overview
Identity
- Canonical model
- Yesidentity confidence: mediumOne row per real model release. Artifacts (checkpoints, quantisations, conversions) and folded evaluation variants point here.
- Official checkpoints
- official_checkpoints = hf_repo identifiers carried by the model itself; artifacts are separate entities pointing here through canonical_id.
- Artifacts
- None recordedSeparate entities (checkpoint · quantization · conversion · packaging) pointing to this model through canonical_id.
- Provider deployments
- 2
- API aliases
- deepseek-v3-1deepseek-v3-1-reasoningdeepseek/deepseek-chat-v3.1Identifiers under which providers and evaluators refer to this model.
- Folded evaluation variants
- 2Effort / thinking variants (…-high, …-non-reasoning) are result configurations of this model, not separate models. Their old URLs redirect here.
Openness
Open weights— weights downloadable; 7 dimensions unknown.
Weights downloadable under a permissive or Creative Commons licence allowing commercial use; code or data may be missing.
Weights
Yes
Inference code
—
Training code
—
Training data
—
Dataset
—
Commercial use
—
Redistribution
—
Derivatives
—
dimensions marked null are unknown, not false
Key facts
- Release date
Source:DeepSeek — site & API docsT2observed 15 h agomediumLLM-extracted
- Status
Source:DeepSeek — site & API docsT2observed 15 h agomediumLLM-extracted
- Version
Source:DeepSeek — site & API docsT2observed 15 h agomediumLLM-extracted
- Knowledge cutoff
Source:OpenRouter public model & pricing listingT2observed 15 h agomedium
- Official page
Source:DeepSeek — site & API docsT2observed 15 h agomediumLLM-extracted
- Repository
Source:DeepSeek — site & API docsT2observed 15 h agomediumLLM-extracted
- Openrouter id
Source:OpenRouter public model & pricing listingT2observed 15 h agomedium
Architecture
- Architecture
Source:DeepSeek — site & API docsT2observed 15 h agomediumLLM-extracted
- Parameters
Source:DeepSeek — site & API docsT2observed 15 h agomediumLLM-extracted
- Tokenizer
Source:OpenRouter public model & pricing listingT2observed 15 h agomedium
- Hugging Face repo
Source:OpenRouter public model & pricing listingT2observed 15 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 7 h agomedium
- Max output
Source:OpenRouter public model & pricing listingT2observed 15 h agomedium
- Knowledge cutoff
Source:OpenRouter public model & pricing listingT2observed 15 h agomedium
- Tokenizer
Source:OpenRouter public model & pricing listingT2observed 15 h agomedium
Benchmarks24
Compare with another model →Comparable same task and conditions · Partially comparable same task, conditions differ (effort, temperature, judge) · Not comparable different variant or metric
Current rows only, grouped by benchmark → canonical metric → comparability group (task configuration). Effort variants folded into this model appear as rows of the same group. 24 current rows in total. “vs leader” compares with the current leader of the benchmark's primary group only; other groups are not directly comparable. Comparability rules →
Providers & Pricing2
All offers in the price terminal →USD per 1M tokens as published by each provider; native units (per-request fees, flex/priority tiers) are kept verbatim. Rows are append-only — every price change is kept in the history below. Cost of a workload →
Price history
Output price · USD / 1M tokens 2 providers
- DeepSeek API
- OpenRouter
- OpenRouterfirst observed $0.9512 Sept 2026
- DeepSeek APIfirst observed $0.9511 Sept 2026
Input price · USD / 1M tokens 2 providers
- DeepSeek API
- OpenRouter
- OpenRouterfirst observed $0.2512 Sept 2026
- DeepSeek APIfirst observed $0.2511 Sept 2026
Hardware fit37
Assumptions (7)
- Estimated, not measured: weights = parameters × bytes/param × 1.15 runtime overhead (or the observed artifact file size when one is recorded).
- bytes/param: 4bit = 0.5, 8bit = 1.0, fp16 = 2.0 (uniform quantization, no per-layer exceptions).
- KV cache: 2 × layers × kv_heads × head_dim × 2 bytes × context × batch when the architecture is known; otherwise 0.5 GB per 8 192 tokens (× batch), 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).
- Multi-GPU: device memories are summed; interconnect bandwidth, tensor-parallel replication and pipeline bubbles are not modelled.
Versions & Artifacts0
Version history
Context window3 changes
11 Sept 2026→11 Sept 2026→11 Sept 2026→12 Sept 2026
Status1 change
11 Sept 2026→11 Sept 2026
Knowledge cutofffirst observation only
11 Sept 2026current
Max outputfirst observation only
11 Sept 2026current
Opennessfirst observation only
11 Sept 2026current
Parametersfirst observation only
11 Sept 2026current
Each hop is a claim: click a value for its source, tier and observation time. Nothing is overwritten — a new observation closes the previous claim.
Artifacts 0
No artifact (checkpoint, quantisation, conversion or packaging) points to this model yet.
Timeline15
Full timeline →OpenRouter lists DeepSeek V3.1 at $0.25 in / $0.95 out per 1M tokens
openrouterDeepSeek V3.1 scores 25% on Terminal-Bench
artificial_analysisDeepSeek V3.1 scores 37.43% on τ²-bench
artificial_analysisDeepSeek V3.1 scores 14.27% on Humanity's Last Exam
artificial_analysisDeepSeek V3.1 scores 77.88% on GPQA Diamond
artificial_analysisDeepSeek V3.1 scores 13.48 on Artificial Analysis Intelligence Index
artificial_analysisDeepSeek V3.1 scores 24.24% on Terminal-Bench
artificial_analysisDeepSeek V3.1 scores 6.67% on Humanity's Last Exam
artificial_analysisDeepSeek V3.1 scores 73.54% on GPQA Diamond
artificial_analysisDeepSeek V3.1 scores 13.71 on Artificial Analysis Intelligence Index
artificial_analysisDeepSeek V3.1: reasoning changed from false to true
ReasoningNo→YesopenrouterDeepSeek V3.1: context length changed from 128000 to 163840
Context window128K tokens→163.8K tokensopenrouter
Change history
Statusstatus3
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
28
Source tiers
T228
Freshest observation
5 h ago
Conflicts
None
Source documents 3
Tier 1 = official/primary, 2 = quality secondary, 3 = community, 4 = unverified. Every snapshot is archived; see all sources and the methodology.
Data quality (72/100) measures how well AI Atlas knows this entity — completeness, primary-source ratio, freshness, conflicts — never how good the model is. Methodology →