Skip to content
ModelCap

MAI DS R1

Official publisher releaseOpen weights7d #123 → #129

Microsoft·#129 of 352 on the current board

MAI DS R1 is a language model from Microsoft. It ranks #129 of 352 on ModelCap's current board, with an Index score of 50.5, carried over from the model it is built on. Its score range of 33.6–67.4 spans positions #55–#214. Its weights are openly downloadable.

Figures as of 6 Nov 2026, 14:10 UTC · download the public dataset · methodology

ModelCap Index · Current board
50.5#129
Carried over from the model it is built on · range 33.6–67.4
Market Gravity
8.8
Secondary market signal

OpenRouter endpoint status could not be refreshed. This model is not treated as currently served until a successful observation arrives.

Input
Self-hosted
weights only · no listed API price
Output
Self-hosted
weights only · no listed API price
Context
—
tokens
Providers
0
endpoints

Providers

Uptime measured over the last 30 minutes

Current provider status is unavailable.

ModelCap Index · Current board

Methodology
50.5
Carried over from the model it is built on
Current board
#129 of 352
Score range
33.6–67.4
Rank range
#55–#214
Technical details
Public rank basis
Modeled · lineage (lineage)
Evidence label
Modeled · lineage · finetune of deepseek/deepseek-r1 · finetune (100%)
Index support
31.5% · moderate
Identity binding
Exact catalogue product · microsoft/microsoft/MAI-DS-R1 · aggregates disclosed benchmark configurations · endpoint configuration not claimed · artifact metadata microsoft/MAI-DS-R1@a96d011a7111dcde61096468ebeeda8068735809 (not the evaluation revision)
Index observations used
0
Qualified Index evidence point
50.5
Verified lineage
deepseek/deepseek-r1 · minus 1.2 ( finetune)
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
50.5 ± 13.2
Independent share
0%
Shrink toward corpus
0.0
Optimism haircut
None applied
Method
precision-weighted-v1
Channels fused into this model’s launch placement
ChannelEstimateShare
Verified lineage · not independent
finetune of deepseek/deepseek-r1 · finetune
50.5 ± 13.2100%
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)
—
Liquidity (providers × uptime)
—
Open reach (HF downloads)
54.7
Surface (context / tools / modalities)
0.0
Freshness
11.5
  • · HF 30d downloads 1714
  • · Catalogue surface
  • · First seen 2025-04-16

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
39.1
23.0–55.2 uncertainty interval
Excluded from rank
Confidence
71%
Training support
221 models · 129 lineages
Out-of-domain check
in domain
Feature coverage
71%
Lineage-held-out error
8.3 MAE

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

Deployment readiness

Metadata index
52.4
partial · 56% metadata coverage
Not capability
Artifact reproducibility
100.0
Access & legal clarity
100.0
Deployability
8.0
Evaluation provenance
0.0

Not yet published: a current serving provider, measured provider uptime, published provider pricing, declared context and output limits, admitted benchmark results, results across several capability areas, results from more than one source, a confident match to its benchmark entries, 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
8.8
OpenRouter weekly popularity
Not listed

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%
0.0

OpenRouter weekly popularity across the full model catalogue.

Liquidity25%
0.0

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

Open reach15%
54.7

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

Freshness5%
11.5

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

Specification

Model ID
microsoft/MAI-DS-R1
Declared output cap
Unknown

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
Cached input tokens
Not offered
First seen on OpenRouter
16 Apr 2025

Capabilities

  • Not supported: Reasoning
  • Not supported: Tool use
  • Not supported: Structured output
  • Not 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
a96d011a7111
Parameters
671.0B
Architecture
DeepseekV3ForCausalLM
Model type
deepseek_v3
Hugging Face downloads (30d)
2K
Downloads (all time)
22K
Likes
316
Repository updated
15 Dec 2025, 18:31 UTC

Alternatives to MAI DS R1, by the numbers

Ranked neighbours

Models within 3 places of #129 on the ModelCap Index.

Other ranked Microsoft models

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

MAI DS R1: common questions

How does MAI DS R1 rank among AI models?

MAI DS R1 holds ModelCap Index position #129 of 352 ranked language models as of 6 November 2026, with an Index score of 50.5 (interval 33.6–67.4); evidence: modeled · lineage. The Index combines public benchmark boards with published uncertainty; the methodology page explains the weighting.

How much does MAI DS R1 cost per 1M tokens?

No live API price is listed for MAI DS R1 in the current snapshot as of 6 November 2026 because the latest endpoint refresh was unavailable. ModelCap shows a price only when a provider currently lists one.

Is MAI DS R1 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 microsoft/MAI-DS-R1 on Hugging Face.

Which benchmarks has MAI DS R1 been evaluated on?

MAI DS R1'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 6 November 2026. The evidence panel names each source and its publication date.

When was MAI DS R1 released?

MAI DS R1 first appeared in the catalogue on 16 Apr 2025. It is the current version in its family. Rank and price movements since then are recorded on the site's changes feed.