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DeepSeek-V4.1-Flash

DeepSeekfamily · DeepSeekapi-docs.deepseek.com/quick_start/pricing

DeepSeek V4.1 Flash is a sparse mixture-of-experts model from DeepSeek, and the first built on the company's Causal Encoder-Decoder (CED) architecture. It activates 8B parameters on input and 16B on...

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data quality77

Updated 4 h ago · first seen 11 Sept 2026

model_01M293WR6HM862PR1R3X4523QG

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
4
API aliases
deepseek-flashdeepseek-v4-1-flashdeepseek/deepseek-v4.1-flashfireworks/deepseek-v4p1-flashIdentifiers under which providers and evaluators refer to this model.
Folded evaluation variants
0Effort / thinking variants (…-high, …-non-reasoning) are result configurations of this model, not separate models. Their old URLs redirect here.

Openness

Open weights— weights downloadable under MIT; commercial use allowed; redistribution allowed; derivatives allowed; 4 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

    Yes

  • Redistribution

    Yes

  • Derivatives

    Yes

Licence: MIT License (permissive · SPDX MIT)

dimensions marked null are unknown, not false

Key facts

Release date

Source:OpenRouter public model & pricing listingT2observed 5 d agomedium

Official page
api-docs.deepseek.com/quick_start/pricing

Source:DeepSeek — site & API docsT1observed 5 d agohigh

API model id

Source:DeepSeek — site & API docsT1observed 5 d agohigh

Openrouter id

Source:OpenRouter public model & pricing listingT2observed 5 d agomedium

Architecture

Architecture

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 5 h agomedium

Model type

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 5 h agomedium

Parameters

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 5 h agomedium

Tokenizer

Source:OpenRouter public model & pricing listingT2observed 5 d agomedium

Weights dtype

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 5 h agomedium

File size

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 5 h agomedium

Library name

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 5 h agomedium

Pipeline tag

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 5 h agomedium

Hugging Face repo

Source:OpenRouter public model & pricing listingT2observed 5 d agomedium

Capabilities

Modalities

Modalities
imagetext
Input
textimage
Output
text

Capabilities

  • Tool calling

    Yes

    DeepSeek — site & API docs · T1

  • Structured output

    Yes

    DeepSeek — site & API docs · T1

  • Reasoning

    Yes

    DeepSeek — site & API docs · T1

  • Vision

    Yes

    DeepSeek — site & API docs · T1

  • Audio

    Unavailable

  • Fine-tuning available

    Unavailable

Context window

Source:DeepSeek — site & API docsT1observed 5 d agohigh

Max output

Source:DeepSeek — site & API docsT1observed 5 d agohigh

Tokenizer

Source:OpenRouter public model & pricing listingT2observed 5 d agomedium

Benchmarks18

Compare with another model →

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

Benchmark results grouped by comparability group
Benchmark · groupBest scoreTrustConfigurationResultsvs leaderEvaluatedSource
Terminal-Benchagentic · accuracy · variant=v4.0 · evaluator=Artificial AnalysisIndependentevaluatorArtificial Analysisvariantv4.0reasoning_effortmaxconditions differ across rows → partially comparable2non-primary groupobs. 15 Sept 2026artificialanalysis.aiT2
LiveBench Agentic Codingcoding · average score · variant=Agentic CodingOfficial boardvariantAgentic Codingrelease2026-06-251current leader25 Jun 2026livebench.aiT2
LiveBench Codingcoding · average score · variant=CodingOfficial boardvariantCodingrelease2026-06-251−6.34 ptvs Claude Fable 5.125 Jun 2026livebench.aiT2
SciCodecoding · accuracy · evaluator=Artificial AnalysisIndependentevaluatorArtificial Analysisreasoning_effortmaxconditions differ across rows → partially comparable2−11.2 ptvs Claude Fable 5.1obs. 16 Sept 2026artificialanalysis.aiT2
Artificial Analysis Intelligence Indexcomposite · indexIndependentreasoning_effortmaxversion4.3conditions differ across rows → partially comparable2−13.8vs Claude Fable 5.1obs. 16 Sept 2026artificialanalysis.aiT2
LiveBenchgeneral · global_averageOfficial boardrelease2026-06-251−2.30 ptvs Claude Fable 5.125 Jun 2026livebench.aiT2
LiveBench Data Analysisgeneral · average score · variant=Data AnalysisOfficial boardvariantData Analysisrelease2026-06-251−3.72 ptvs gpt-6-astra25 Jun 2026livebench.aiT2
LiveBench Languagegeneral · average score · variant=LanguageOfficial boardvariantLanguagerelease2026-06-251−9.49 ptvs Claude Fable 525 Jun 2026livebench.aiT2
LiveBench Instruction Followinginstruction-following · average score · variant=IFOfficial boardvariantIFrelease2026-06-251−11.4 ptvs Gemini 3.8 Flash25 Jun 2026livebench.aiT2
Humanity's Last Examknowledge · accuracy · evaluator=Artificial AnalysisIndependentevaluatorArtificial Analysisreasoning_effortmaxconditions differ across rows → partially comparable2−19.9 ptvs Claude Fable 5.1obs. 16 Sept 2026artificialanalysis.aiT2
LiveBench Mathematicsmath · average score · variant=MathematicsOfficial boardvariantMathematicsrelease2026-06-251−3.72 ptvs Claude Fable 5.125 Jun 2026livebench.aiT2
MMMU-Promultimodal · accuracy · evaluator=Artificial AnalysisIndependentevaluatorArtificial Analysisreasoning_effortmaxconditions differ across rows → partially comparable2−9.89 ptvs gpt-6-astraobs. 16 Sept 2026artificialanalysis.aiT2
LiveBench Reasoningreasoning · average score · variant=ReasoningOfficial boardvariantReasoningrelease2026-06-251−5.96 ptvs gpt-6-astra25 Jun 2026livebench.aiT2

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. 18 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 & Pricing5

All offers in the price terminal →
Provider deployments, cheapest output first
ProviderContextInput / 1MCached inOutput / 1MBatch in / outNative unitsStatusObservedSource
DeepSeek APIcheapest outputdeepseek/deepseek-v4.1-flash1.05Mout 384K$0.003——active5 d agosince 11 Sept 2026openrouter.aiT2
OpenRouterdeepseek/deepseek-v4.1-flash1.05Mout 384K$0.003——active2 h agosince 16 Sept 2026openrouter.aiT2
Fireworks AIfireworks/deepseek-v4p1-flash—$0.007——active5 d agosince 11 Sept 2026app.fireworks.aiT1
DeepSeek APIdeepseek-flash—$0.006—off_peak_input_per_mtok=0.15off_peak_output_per_mtok=0.6off_peak_cached_input_per_mtok=0.003active5 d agosince 11 Sept 2026api-docs.deepseek.comT1
Together AIdeepseek-v4-1-flash—$0.006$0.30 / $1.2—active7 h agosince 13 Sept 2026together.aiT1

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

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 4 providers

Output price history of DeepSeek-V4.1-Flash$0$0.50$1$1.5Sept 26Sept 26Sept 26Sept 26Sept 26DeepSeek API: first observed → $1.2 · 11 Sept 2026Fireworks AI: first observed → $0.66 · 11 Sept 2026DeepSeek API: $1.2 → $0.60 · 11 Sept 2026OpenRouter: first observed → $0.60 · 12 Sept 2026Together AI: first observed → $1.2 · 13 Sept 2026OpenRouter: $0.60 → $1.2 · 14 Sept 2026OpenRouter: $1.2 → $0.60 · 14 Sept 2026OpenRouter: $0.60 → $1.2 · 14 Sept 2026OpenRouter: $1.2 → $0.60 · 14 Sept 2026OpenRouter: $0.60 → $1.2 · 15 Sept 2026OpenRouter: $1.2 → $0.60 · 15 Sept 2026OpenRouter: $0.60 → $1.2 · 15 Sept 2026OpenRouter: $1.2 → $0.60 · 15 Sept 2026OpenRouter: $0.60 → $1.2 · 16 Sept 2026OpenRouter: $1.2 → $0.60 · 16 Sept 2026
  • DeepSeek API
  • Fireworks AI
  • OpenRouter
  • Together AI
  • OpenRouter$1.2 → $0.6016 Sept 2026
  • OpenRouter$0.60 → $1.216 Sept 2026
  • OpenRouter$1.2 → $0.6015 Sept 2026
  • OpenRouter$0.60 → $1.215 Sept 2026
  • OpenRouter$1.2 → $0.6015 Sept 2026
  • OpenRouter$0.60 → $1.215 Sept 2026
  • OpenRouter$1.2 → $0.6014 Sept 2026
  • OpenRouter$0.60 → $1.214 Sept 2026
  • OpenRouter$1.2 → $0.6014 Sept 2026
  • OpenRouter$0.60 → $1.214 Sept 2026
  • Together AIfirst observed $1.213 Sept 2026
  • OpenRouterfirst observed $0.6012 Sept 2026

Input price · USD / 1M tokens 4 providers

Input price history of DeepSeek-V4.1-Flash$0$0.10$0.20$0.30$0.40Sept 26Sept 26Sept 26Sept 26Sept 26DeepSeek API: first observed → $0.30 · 11 Sept 2026Fireworks AI: first observed → $0.22 · 11 Sept 2026DeepSeek API: $0.30 → $0.15 · 11 Sept 2026OpenRouter: first observed → $0.15 · 12 Sept 2026Together AI: first observed → $0.30 · 13 Sept 2026OpenRouter: $0.15 → $0.30 · 14 Sept 2026OpenRouter: $0.30 → $0.15 · 14 Sept 2026OpenRouter: $0.15 → $0.30 · 14 Sept 2026OpenRouter: $0.30 → $0.15 · 14 Sept 2026OpenRouter: $0.15 → $0.30 · 15 Sept 2026OpenRouter: $0.30 → $0.15 · 15 Sept 2026OpenRouter: $0.15 → $0.30 · 15 Sept 2026OpenRouter: $0.30 → $0.15 · 15 Sept 2026OpenRouter: $0.15 → $0.30 · 16 Sept 2026OpenRouter: $0.30 → $0.15 · 16 Sept 2026
  • DeepSeek API
  • Fireworks AI
  • OpenRouter
  • Together AI
  • OpenRouter$0.30 → $0.1516 Sept 2026
  • OpenRouter$0.15 → $0.3016 Sept 2026
  • OpenRouter$0.30 → $0.1515 Sept 2026
  • OpenRouter$0.15 → $0.3015 Sept 2026
  • OpenRouter$0.30 → $0.1515 Sept 2026
  • OpenRouter$0.15 → $0.3015 Sept 2026
  • OpenRouter$0.30 → $0.1514 Sept 2026
  • OpenRouter$0.15 → $0.3014 Sept 2026
  • OpenRouter$0.30 → $0.1514 Sept 2026
  • OpenRouter$0.15 → $0.3014 Sept 2026
  • Together AIfirst observed $0.3013 Sept 2026
  • OpenRouterfirst observed $0.1512 Sept 2026

Hardware fit37

Estimated

3 of 37 device × quantization combinations fit.

Run locally: your machine →
Estimated hardware fit
HardwareQuantizationDevice memoryEst. memoryFits
Apple M3 Ultra4bit—439.3 GB est.Yes
Mac Studio (Apple M5 Ultra)4bit—439.3 GB est.Yes
NVIDIA DGX B2004bit1,440 GB439.3 GB est.Yes
Apple M2 Ultra4bit—439.3 GB est.No
Apple M1 Ultra4bit—439.3 GB est.No
Apple M3 Max4bit—439.3 GB est.No
Apple M4 Max4bit—439.3 GB est.No
Mac Studio (Apple M5 Max)4bit—439.3 GB est.No
MacBook Pro (Apple M5 Max)4bit—439.3 GB est.No
Apple M2 Max4bit—439.3 GB est.No
Apple M1 Max4bit—439.3 GB est.No
Apple M4 Pro4bit—439.3 GB est.No
Mac mini (Apple M5 Pro)4bit—439.3 GB est.No
MacBook Pro (Apple M5 Pro)4bit—439.3 GB est.No
Apple M3 Pro4bit—439.3 GB est.No
Apple M1 Pro4bit—439.3 GB est.No
Apple M2 Pro4bit—439.3 GB est.No
Apple M44bit—439.3 GB est.No
iMac (Apple M4)4bit—439.3 GB est.No
Mac mini (Apple M6)4bit—439.3 GB est.No
MacBook Air (Apple M5)4bit—439.3 GB est.No
MacBook Pro (Apple M5)4bit—439.3 GB est.No
Apple M24bit—439.3 GB est.No
Apple M34bit—439.3 GB est.No
Apple M14bit—439.3 GB est.No
NVIDIA GeForce RTX 30904bit24 GB439.3 GB est.No
NVIDIA GeForce RTX 40904bit24 GB439.3 GB est.No
NVIDIA GeForce RTX 50904bit32 GB439.3 GB est.No
NVIDIA A100 80GB4bit80 GB439.3 GB est.No
NVIDIA H100 SXM4bit80 GB439.3 GB est.No
NVIDIA H100 NVL4bit94 GB439.3 GB est.No
NVIDIA DGX Spark4bit128 GB439.3 GB est.No
NVIDIA H2004bit141 GB439.3 GB est.No
NVIDIA H200 NVL4bit141 GB439.3 GB est.No
NVIDIA B2004bit180 GB439.3 GB est.No
AMD Instinct MI300X4bit192 GB439.3 GB est.No
AMD Instinct MI325X4bit256 GB439.3 GB est.No
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 windowfirst observation only

11 Sept 2026current

Licensefirst observation only

16 Sept 2026current

Max outputfirst observation only

11 Sept 2026current

Opennessfirst observation only

11 Sept 2026current

Parametersfirst observation only

16 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.

Timeline9

Full timeline →

Change history

Temporal, append-only claims: a new observation closes the previous claim instead of overwriting it. Rewind the record with the as-of picker.
1 claims · 1 propertiesShow all properties

Artifact kindartifact_kind1

Claim history for Artifact kind
ValueValid from → toStatusSourceConfidenceExtractor
quantization → currentcurrentHugging 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

46

Source tiers

T1T210 / 36

Freshest observation

5 h ago

Conflicts

11 flagged

Source documents 9

Source documents
SourceDocumentTypeTierLast observedSnapshots
Fireworks AI — pricingdocs.fireworks.ai/serverless/pricing.md pricingT1· Official4 h ago2
Together AI — pricingtogether.ai/pricing pricingT1· Official7 h ago3
DeepSeek — site & API docsapi-docs.deepseek.com/quick_start/pricing pricingT1· Official36 h ago1
Hugging Face Hub (public pages, model cards, papers)huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash model_pageT2· Quality secondary38 min ago2
Hugging Face Hub (public pages, model cards, papers)huggingface.co/models?author=deepseek-ai&p=0&sort=downloads listingT2· Quality secondary52 min ago32
OpenRouter public model & pricing listingopenrouter.ai/api/v1/models catalogueT2· Quality secondary2 h ago75
Hugging Face Hub (public pages, model cards, papers)huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash/raw/main/README.md model_cardT2· Quality secondary4 h ago1
Artificial Analysisartificialanalysis.ai/leaderboards/models leaderboardT2· Quality secondary6 h ago17
LiveBenchlivebench.ai/table_2026_06_25.csv leaderboardT2· Quality secondary5 d ago1

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

Data quality (77/100) measures how well AI Atlas knows this entity — completeness, primary-source ratio, freshness, conflicts — never how good the model is. Methodology →