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ModelCap

DeepSeek V3.1

All-versions archive #117Arena #123Official publisher releaseOpen weights

DeepSeek·deepseek/deepseek-chat-v3.1

DeepSeek V3.1 is ModelCap archive rank #117 (Measured), from the ModelCap Index as of 22 Sept 2026, 02:49 UTC.

DeepSeek V3.1 listed OpenRouter input price is $0.25 per 1M tokens and listed output price is $0.95 per 1M tokens, from OpenRouter listed prices as of 22 Sept 2026, 02:49 UTC.

DeepSeek V3.1 has a published context limit of 164K tokens in the ModelCap catalogue as of 22 Sept 2026, 02:49 UTC.

DeepSeek V3.1 has 8 published OpenRouter serving endpoints, from OpenRouter as of 22 Sept 2026, 02:49 UTC.

DeepSeek V3.1 weight access is open weights, from ModelCap classification of published repository metadata as of 22 Sept 2026, 02:49 UTC.

Snapshot facts · download the public dataset · methodology

ModelCap Index · All-versions archive
59.4#117
Measured · 62% support · score interval 54.4–64.4
Evidence as of 13 Sept 2026, 00:00 UTC
Market Gravity
49.5
Secondary market signal

Superseded by DeepSeek V3.2. It no longer holds a current-board position; its all-versions archive rank is #117.

Input
$0.25
per 1M tokens
Output
$0.95
per 1M tokens
Context
164K
tokens
Providers
8
endpoints
Gateway spend
latest · Vercel share

Providers

Uptime measured over the last 30 minutes
ProviderInputOutputContextQuantUptime
DeepInfrafp4Cheapest$0.25$0.95164Kfp499.74%
AtlasCloudfp8$0.30$0.95131Kfp899.41%
SiliconFlowfp8$0.27$1.00164Kfp899.06%
Novitafp8$0.27$1.00131Kfp8100.0%
SambaNovafp8$0.65$1.50131Kfp8100.0%
CoreWeavefp8$0.55$1.65161Kfp8100.0%
Mara$0.60$1.70131K92.15%
Googleus-west2$0.60$1.70164K0.00%

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
deepinfra
live
$0.25$0.95164K626 ms13.9 tok/stools · structured
novita
live
$0.27$1.00131K1409 ms37.1 tok/stools · structured
featherless-ai
live

Reasoning efforts

Best supported result can inform ModelCap

Published Max, X-High, High and other configurations for this model. These are sourced scores, not head-to-head essays.

Related community configurations

Human preference rating
ConfigurationRatingSource rankVotesSource
Thinking
deepseek-v3.1-thinking
1416
CI 1409–1423
#12511KLMArena
Match 100%

Reported evaluation leads (1)

Not independent measurement

Structured rows reported in this exact model repository at the pinned revision below. They are the publisher talking about itself: never measured evidence, never a score input on their own. They remain quarantined until dataset revision, harness, configuration and identity pass ModelCap’s independent admission review.

Dataset / taskMetricValueRevisionProvenance
TIGER-Lab/MMLU-Pro
mmlu_pro
84.8
Unpinned
not published
Reported
Quarantined

Other versions (4)

ModelCap Index · All-versions archive

Methodology
59.4
Measured · 2 public benchmark observations across 2 boards
All-versions archive
#117
Public rank basis
Measured (measured)
Index support
61.9% · strong
Index interval
54.4–64.4
Rank posterior
Not available
Top 5 / Top 10 probability
Not available / Not available
Posterior as of
Snapshot timestamp unavailable
Evidence as of
13 Sept 2026, 00:00 UTC
Identity binding
Exact catalogue product · deepseek/deepseek/deepseek-chat-v3.1/fp8 · aggregates disclosed benchmark configurations · endpoint configuration not claimed · artifact metadata deepseek-ai/DeepSeek-V3.1@c0781d039fb7a1ba2abc4add0bdc293e92d2b8db (not the evaluation revision)
Index observations used
2
Qualified Index evidence point
59.4
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
59.4
Evidence status
confirmed · 77% mass
General preference
60.0
Coding
54.9
Agents & tools
Reasoning
Evidence breadth
92%
Evidence coverage
62%
Market and catalogue signals · secondary, never the language Index rank
Usage (OpenRouter popularity)
20.3
Liquidity (providers × uptime)
94.2
Open reach (HF downloads)
91.7
Surface (context / tools / modalities)
71.8
Freshness
22.1
  • · OpenRouter popularity #100
  • · 8 live providers
  • · HF 30d downloads 284658
  • · Catalogue: context 163840, reasoning, tools
  • · First seen 2025-08-21

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

BES evidence selected · measured input only

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.

Deployment readiness

Metadata index
88.9
strong · 98% metadata coverage
Not capability
Artifact reproducibility
100.0
Access & legal clarity
100.0
Deployability
95.6
Evaluation provenance
51.2

Missing: 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
49.5
OpenRouter weekly popularity
#100 of 322

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

Status
Ranked
Source
LMArena
Official rank
#123 of 402
Rating
1417.3
95% confidence interval
1411–1423
Votes
15K
Source published at
13 Sept 2026, 00:00 UTC
Category
overall
Identity match confidence
100%

Market Gravity breakdown

Usage55%
20.3

OpenRouter weekly popularity across the full model catalogue.

Liquidity25%
94.2

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

Open reach15%
91.7

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

Freshness5%
22.1

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

Specification

Context window
164K tokens
Max output
33K tokens
Inputs
Text
Outputs
Text
Tokenizer
DeepSeek
Cached input tokens
$0.13 / 1M
First seen on OpenRouter
21 Aug 2025
Knowledge cutoff
2025-03-31

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
c0781d039fb7
Parameters
684.5B
Architecture
DeepseekV3ForCausalLM
Model type
deepseek_v3
Hugging Face downloads (30d)
285K
Downloads (all time)
3.0M
Likes
833
Repository updated
5 Sept 2025, 11:30 UTC

Benchmark leaderboards featuring DeepSeek V3.1

All leaderboards
Public benchmark boards on which DeepSeek V3.1 has a published result
LeaderboardScoreSource rankConfigurationPublished
Arena coding leaderboardArena (LMArena)14561442–1469#136 of 397Thinking13 Sept 2026
τ²-Bench Telecom (Artificial Analysis run)Artificial Analysis34.8%#248 of 436tau2:telecom:dual-control:pass-at-1:3-repeats:source-model="DeepSeek V3.1 (Non-reasoning)":reasoning=false5 Sept 2026
Humanity's Last Exam (Artificial Analysis run)Artificial Analysis6.7%#355 of 615hle:may-2025:text-only-2158:no-tools:pass-at-1:source-model="DeepSeek V3.1 (Non-reasoning)":reasoning=false5 Sept 2026

DeepSeek V3.1: common questions

How does DeepSeek V3.1 rank among AI models?

DeepSeek V3.1 is a superseded version and is not on the current board as of 22 September 2026. Its archive position, where one exists, is shown on the page; the newer version carries the current rank.

How much does DeepSeek V3.1 cost per 1M tokens?

DeepSeek V3.1 is listed at $0.25 per 1M input tokens and $0.95 per 1M output tokens as of 22 September 2026 across 8 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 $0.975 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 V3.1?

DeepSeek V3.1 has a published context window of 164K tokens (163,840) and a maximum output of 33K tokens. Individual providers can serve less than the published maximum; the providers table lists each endpoint's own limit.

Is DeepSeek V3.1 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-V3.1 on Hugging Face.

Which API providers serve DeepSeek V3.1?

8 providers serve DeepSeek V3.1 through OpenRouter as of 22 September 2026: DeepInfra, SiliconFlow, Novita, AtlasCloud, CoreWeave and Mara and 2 more. Each provider's price, context limit, quantization and measured uptime are in the providers table above.

Which benchmarks has DeepSeek V3.1 been evaluated on?

DeepSeek V3.1 has published results on 3 public boards tracked by ModelCap as of 22 September 2026: Arena coding 1456 (#136 of 397), AA τ²-Bench Telecom 34.8% (#248 of 436) and AA Humanity's Last Exam 6.7% (#355 of 615). Each board page ranks every tracked model on that benchmark; the ModelCap Index combines them with published uncertainty.

When was DeepSeek V3.1 released?

DeepSeek V3.1 first appeared in the catalogue on 21 Aug 2025, with a published knowledge cutoff of 2025-03-31. It has since been superseded by DeepSeek V3.2. Rank and price movements since then are recorded on the site's changes feed.