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ModelCap

DeepSeek V3.1 Terminus

Arena #143Official publisher releaseOpen weights7d #89 → #91

DeepSeek·#91 of 352 on the current board·cheaper than #90 Qwen3.5-122B-A10B

DeepSeek V3.1 Terminus is a language model from DeepSeek. It ranks #91 of 352 on ModelCap's current board, with an Index score of 57.9, measured on 2 public benchmarks. Its score range of 51.7–64.1 spans positions #65–#122. It is listed at $0.27 per million input tokens and $1.00 per million output tokens from one provider. It reads up to 164K tokens of context, and its weights are openly downloadable.

Figures as of 6 Nov 2026, 13:52 UTC · download the public dataset · methodology

ModelCap Index · Current board
57.9#91
Measured on 2 public benchmarks · range 51.7–64.1
Evidence as of 28 Oct 2026, 00:00 UTC
Market Gravity
15.1Decreased by 0.2
Secondary market signal
Input
$0.27
per 1M tokens
Output
$1.00
per 1M tokens
Context
164K
tokens
Providers
1
endpoint

Providers

Uptime measured over the last 30 minutes
ProviderInputOutputContextQuantUptime
SiliconFlowfp8$0.27$1.00164Kfp8100.0%

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
$0.27$0.95164K423 ms51.9 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-Terminus (Thinking)
1416
CI 1406–1426
#1403KLMArena
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
Idavidrein/gpqa
diamond
—74.2424
Unpinned
not published
Reported
Quarantined

ModelCap Index · Current board

Methodology
57.9
Measured on 2 public benchmarks
Current board
#91 of 352
Score range
51.7–64.1
Rank range
#65–#122
Evidence as of
28 Oct 2026, 00:00 UTC
Benchmarks used
Arena Coding, Arena Overall
Technical details
Public rank basis
Measured (measured)
Evidence label
Measured · 2 public benchmark observations across 2 boards
Index support
47.7% · moderate
Identity binding
Exact catalogue product · deepseek/deepseek/deepseek-v3.1-terminus/fp8 · aggregates disclosed benchmark configurations · endpoint configuration not claimed · artifact metadata deepseek-ai/DeepSeek-V3.1-Terminus@19510d6dc61f79dbd925bd51ee8a9081c509a4b6 (not the evaluation revision)
Index observations used
2
Qualified Index evidence point
57.9
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
57.9
Evidence status
confirmed · 72% mass
General preference
58.2
Coding
55.7
Agents & tools
—
Reasoning
—
Evidence breadth
92%
Evidence coverage
48%
Market and catalogue signals · secondary, never the language Index rank
Usage (OpenRouter popularity)
9.9
Liquidity (providers × uptime)
24.3
Open reach (HF downloads)
16.4
Surface (context / tools / modalities)
71.8
Freshness
21.0
  • · OpenRouter popularity #190
  • · 1 live provider
  • · HF 30d downloads 9757
  • · Catalogue: context 163840, reasoning, tools
  • · First seen 2025-09-22

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
88.1
strong · 98% metadata coverage
Not capability
Artifact reproducibility
100.0
Access & legal clarity
100.0
Deployability
95.0
Evaluation provenance
48.0

Not yet published: pinned evaluation dataset versions.

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

Market activity

Venue coverage
Market Gravity
15.1
OpenRouter weekly popularity
#190 of 339

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
#143 of 419
Rating
1414.7
95% confidence interval
1405–1424
Votes
4K
Source published at
28 Oct 2026, 00:00 UTC
Category
overall
Identity match confidence
100%

Market Gravity breakdown

Usage55%
9.9

OpenRouter weekly popularity across the full model catalogue.

Liquidity25%
24.3

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

Open reach15%
16.4

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

Freshness5%
21.0

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

Specification

Model ID
deepseek/deepseek-v3.1-terminus
Context window
164K tokens
Declared output cap
147K tokens

OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. OpenRouter metadata

Inputs
Text
Outputs
Text
Tokenizer
DeepSeek
Cached input tokens
Not offered
First seen on OpenRouter
22 Sept 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
19510d6dc61f
Parameters
684.5B
Architecture
DeepseekV3ForCausalLM
Model type
deepseek_v3
Hugging Face downloads (30d)
10K
Downloads (all time)
277K
Likes
386
Repository updated
29 Sept 2025, 01:52 UTC

Compare DeepSeek V3.1 Terminus with

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Benchmark leaderboards featuring DeepSeek V3.1 Terminus

All leaderboards
Public benchmark boards on which DeepSeek V3.1 Terminus has a published result
LeaderboardScoreSource rankConfigurationPublished
Arena text leaderboardArena (LMArena)14161406–1426#140 of 419Thinking28 Oct 2026
Arena coding leaderboardArena (LMArena)14601436–1483#143 of 414Thinking28 Oct 2026

Alternatives to DeepSeek V3.1 Terminus, by the numbers

Ranked neighbours

Models within 3 places of #91 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 V3.1 Terminus: common questions

How does DeepSeek V3.1 Terminus rank among AI models?

DeepSeek V3.1 Terminus holds ModelCap Index position #91 of 352 ranked language models as of 6 November 2026, with an Index score of 57.9 (interval 51.7–64.1); evidence: measured. The Index combines public benchmark boards with published uncertainty; the methodology page explains the weighting.

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

DeepSeek V3.1 Terminus is listed at $0.27 per 1M input tokens and $1.00 per 1M output tokens as of 6 November 2026. 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 $1.04 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 Terminus?

DeepSeek V3.1 Terminus has a published context window of 164K tokens (163,840). The snapshot lists a 147,456 token catalogue-declared route output cap. OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. The providers table lists each endpoint's context limit.

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

Which API providers serve DeepSeek V3.1 Terminus?

One provider serves DeepSeek V3.1 Terminus through OpenRouter as of 6 November 2026: SiliconFlow. Each provider's price, context limit, quantization and measured uptime are in the providers table above.

Which benchmarks has DeepSeek V3.1 Terminus been evaluated on?

DeepSeek V3.1 Terminus has published results on 2 public boards tracked by ModelCap as of 6 November 2026: Arena text 1416 (#140 of 419) and Arena coding 1460 (#143 of 414). Each board page ranks every tracked model on that benchmark. The ModelCap Index scores the results its methodology admits, with published uncertainty, and shows reference boards without scoring them.

How does DeepSeek V3.1 Terminus compare with R1 0528?

DeepSeek V3.1 Terminus ranks #91 (Index 57.9) and R1 0528 ranks #86 (Index 59.7) on the ModelCap Index as of 6 November 2026. The head-to-head page lines up their benchmarks, listed prices, context windows and provider counts side by side.

When was DeepSeek V3.1 Terminus released?

DeepSeek V3.1 Terminus first appeared in the catalogue on 22 Sept 2025, with a published knowledge cutoff of 2025-03-31. It is the current version in its family. Rank and price movements since then are recorded on the site's changes feed.