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ModelCap

DeepSeek V4.1 Flash

Current board #40Official publisher releaseNewOpen weights

DeepSeek·deepseek/deepseek-v4.1-flash

DeepSeek V4.1 Flash is ModelCap current-board rank #40 with Index 65.2 (Modeled · succession), from the ModelCap Index as of 10 Sept 2026, 11:40 UTC.

DeepSeek V4.1 Flash listed OpenRouter input price is $0.15 per 1M tokens and listed output price is $0.60 per 1M tokens, from OpenRouter listed prices as of 10 Sept 2026, 11:40 UTC.

DeepSeek V4.1 Flash has a published context limit of 1M tokens in the ModelCap catalogue as of 10 Sept 2026, 11:40 UTC.

DeepSeek V4.1 Flash has 3 published OpenRouter serving endpoints, from OpenRouter as of 10 Sept 2026, 11:40 UTC.

DeepSeek V4.1 Flash weight access is open weights, from ModelCap classification of published repository metadata as of 10 Sept 2026, 11:40 UTC.

Snapshot facts · download the public dataset · methodology

ModelCap Index · Current board
65.2#40
Estimated · 11% support · score interval 51.6–78.8
No admitted evaluation publication timestamp yet
Market Gravity
30.9
Secondary market signal
Input
$0.15
per 1M tokens
Output
$0.60
per 1M tokens
Context
1M
tokens
Providers
3
endpoints
Gateway spend
latest · Vercel share

Providers

Uptime measured over the last 30 minutes
ProviderInputOutputContextQuantUptime
DeepSeekCheapest$0.15$0.601M100.0%
Novita$0.30$1.201M100.0%
DeepInfrafp8$0.30$1.201Mfp894.89%

Hugging Face Inference Providers

Exact repository identity

Provider economics and telemetry published by the Hugging Face Router. These are operational signals, not benchmark results.

ProviderInputOutputContextTTFTThroughputFeatures
novita
live
$0.30$1.201M786 ms122.7 tok/stools

Other versions (2)

ModelCap Index · Current board

Methodology
65.2
Modeled · succession · calibrated architecture-and-release-era fallback from static public metadata
Current board
#40
Public rank basis
Modeled · succession (architecture)
Index support
11.1% · weak
Index interval
51.6–78.8
Rank posterior
Not available
Top 5 / Top 10 probability
Not available / Not available
Posterior as of
Snapshot timestamp unavailable
Evidence as of
No admitted evaluation publication timestamp
Identity binding
Exact catalogue product · deepseek/deepseek/deepseek-v4.1-flash/fp8 · aggregates disclosed benchmark configurations · endpoint configuration not claimed · artifact metadata deepseek-ai/DeepSeek-V4.1-Flash@dba1be0a40aa45a94ad051997016db3960a90277 (not the evaluation revision)
Index observations used
0
Qualified Index evidence point
65.2
How this position was produced · fused launch placement

No general-family board lists this model yet. Its point estimate is the precision-weighted mean of every channel that spoke for it; each channel’s share is the weight it carried. Independent measurements replace this placement as boards list the model.

Fused estimate
65.2 ± 10.6
Independent share
0%
Shrink toward corpus
-2.0
Optimism haircut
None applied
Method
precision-weighted-v1
Channels fused into this model’s launch placement
ChannelEstimateShare
Publisher corpus prior · not independent
publisher-corpus-prior over 185 held-out anchors
58.0 ± 22.722%
Family succession · not independent
opens from measured predecessor deepseek/deepseek-v4-flash-0731
67.2 ± 12.078%
Bayesian Evidence Score · measured evidence input only

BES normalizes admitted public benchmark evidence for measured Index rows. Its legacy score and observables prior do not define the public language rank.

Observed capability
Evidence status
No admitted measured evidence
General preference
Coding
Agents & tools
Reasoning
Evidence breadth
0%
Evidence coverage
0%
Market and catalogue signals · secondary, never the language Index rank
Usage (OpenRouter popularity)
20.9
Liquidity (providers × uptime)
56.3
Open reach (HF downloads)
2.0
Surface (context / tools / modalities)
100.0
Freshness
99.9
  • · OpenRouter popularity #94
  • · 3 live providers
  • · HF 30d downloads 6
  • · Catalogue: context 1048576, reasoning, tools, modalities Text/Image
  • · First seen 2026-09-10

These adoption and deployment observations remain context only. They do not change this model's ModelCap Index score or rank.

The bounded 0–100 capability score blends each source’s competitive placement with its published achievement, then combines capability families. Evidence breadth adds a modest uncertainty adjustment; price and popularity are not part of benchmark-led rank.

Experimental capability estimate

Estimate policy
74.7
57.2–92.1 uncertainty interval
Excluded from rank
Confidence
75%
Training support
189 models · 108 lineages
Out-of-domain check
in domain
Feature coverage
100%
Lineage-held-out error
10.3 MAE

Experimental estimate. This layer predicts from admitted evidence and safe metadata only. It never enters ModelCap Score or rank.

Deployment readiness

Metadata index
75.4
strong · 76% metadata coverage
Not capability
Artifact reproducibility
85.0
Access & legal clarity
100.0
Deployability
99.7
Evaluation provenance
0.0

Missing: artifactReproducibility.base-lineage, evaluationProvenance.admitted-evaluation-observations, evaluationProvenance.capability-family-breadth, evaluationProvenance.evaluation-source-diversity, evaluationProvenance.identity-and-source-confidence, evaluationProvenance.evaluation-dataset-revisions.

A metadata completeness and deployability index—not a safety certification, quality grade, or production-readiness claim.

Market activity

Venue coverage
Market Gravity
30.9
OpenRouter weekly popularity
#94 of 313

Market Gravity uses OpenRouter’s full-catalogue popularity order. Sparse Vercel top-ten observations appear only when published and do not affect the score.

Arena preference

No matched Arena rating

This model is visible because it is available in the live catalogue, but it has no trustworthy community result yet. ModelCap does not infer a quality score from price, features, or market activity.

Market Gravity breakdown

Usage55%
20.9

OpenRouter weekly popularity across the full model catalogue.

Liquidity25%
56.3

Independent providers versus the model's open or closed cohort, weighted by uptime.

Open reach15%
2.0

Hugging Face 30-day downloads for open models; neutral for closed models.

Freshness5%
99.9

Time since first public availability, on a six-month half-life.

Specification

Context window
1M tokens
Max output
384K tokens
Inputs
Text, Image
Outputs
Text
Tokenizer
DeepSeek
Cached input tokens
$0.0030 / 1M
First seen on OpenRouter
10 Sept 2026

Capabilities

  • Supported: Reasoning
  • Supported: Tool use
  • Supported: Structured output
  • Supported: Response format
  • Not supported: Moderated

Weights & access

Open weights. Downloadable weights are published under an OSI or free-culture license in the current repository metadata. This describes weight availability, not whether the full training stack qualifies as Open Source AI.

Access
Open weights
Licence
mit
Pinned revision
dba1be0a40aa
Parameters
484.6B
Architecture
DeepseekV41ForCausalLM
Model type
deepseek_v41
Hugging Face downloads (30d)
6
Downloads (all time)
6
Likes
805
Repository updated
10 Sept 2026, 08:18 UTC

Compare DeepSeek V4.1 Flash with

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Alternatives to DeepSeek V4.1 Flash, by the numbers

Ranked neighbours

Models within 3 places of #40 on the ModelCap Index.

Cheaper at a similar or higher Index

Index score within 3 points of, or above, this model's, with a lower listed blended price (3:1 input:output).

Other ranked DeepSeek models

The same publisher's other current models with a public Index position.

DeepSeek V4.1 Flash: common questions

How does DeepSeek V4.1 Flash rank among AI models?

DeepSeek V4.1 Flash holds ModelCap Index position #40 of 172 ranked language models as of 10 September 2026, with an Index score of 65.2 (interval 51.6–78.8); evidence: modeled · succession. The Index combines public benchmark boards with published uncertainty; the methodology page explains the weighting.

How much does DeepSeek V4.1 Flash cost per 1M tokens?

DeepSeek V4.1 Flash is listed at $0.15 per 1M input tokens and $0.60 per 1M output tokens as of 10 September 2026 across 3 providers. Prices come from the OpenRouter catalogue and re-observe on every refresh. For 1,000 requests using 2,000 input and 500 output tokens each, the listed rates imply $0.60 total (2M input + 0.5M output). This excludes caching, batch discounts, prompt-length tiers, tool charges and retries; verify the chosen endpoint's rate and limits before budgeting.

What is the context window of DeepSeek V4.1 Flash?

DeepSeek V4.1 Flash has a published context window of 1M tokens (1,048,576) and a maximum output of 384K tokens. Individual providers can serve less than the published maximum; the providers table lists each endpoint's own limit.

Is DeepSeek V4.1 Flash open-weight?

Open weights (mit). Downloadable weights are published under an OSI or free-culture license in the current repository metadata. This describes weight availability, not whether the full training stack qualifies as Open Source AI. The repository is deepseek-ai/DeepSeek-V4.1-Flash on Hugging Face.

Which API providers serve DeepSeek V4.1 Flash?

3 providers serve DeepSeek V4.1 Flash through OpenRouter as of 10 September 2026: DeepSeek, Novita and DeepInfra. Each provider's price, context limit, quantization and measured uptime are in the providers table above.

Which benchmarks has DeepSeek V4.1 Flash been evaluated on?

DeepSeek V4.1 Flash's Index position rests on the evidence listed on this page; it has no result on the public boards ModelCap tracks as separate leaderboards as of 10 September 2026. The evidence panel names each source and its publication date.

How does DeepSeek V4.1 Flash compare with Gemma 4 26B A4B?

DeepSeek V4.1 Flash ranks #40 (Index 65.2) and Gemma 4 26B A4B ranks #39 (Index 65.2) on the ModelCap Index as of 10 September 2026. The head-to-head page lines up their benchmarks, listed prices, context windows and provider counts side by side.

When was DeepSeek V4.1 Flash released?

DeepSeek V4.1 Flash first appeared in the catalogue on 10 Sept 2026. It is the current version in its family. Rank and price movements since then are recorded on the site's changes feed.