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ModelCap

R1 0528

Arena #133Official publisher releaseOpen weights7d #84 → #86

DeepSeek·#86 of 352 on the current board·cheaper than #81 Mistral Medium 3.5

R1 0528 is a language model from DeepSeek. It ranks #86 of 352 on ModelCap's current board, with an Index score of 59.7, measured on 2 public benchmarks. Its score range of 54.7–64.7 spans positions #64–#100. It is listed at $0.50 per million input tokens and $2.15 per million output tokens across 3 providers. 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
59.7#86
Measured on 2 public benchmarks · range 54.7–64.7
Evidence as of 28 Oct 2026, 00:00 UTC
Market Gravity
31.4Increased by 0.2
Secondary market signal
Input
$0.50
per 1M tokens
Output
$2.15
per 1M tokens
Context
164K
tokens
Providers
3
endpoints

Providers

Uptime measured over the last 30 minutes
ProviderInputOutputContextQuantUptime
DeepInfrafp4Cheapest$0.50$2.15164Kfp4100.0%
SiliconFlowfp8$0.50$2.18164Kfp8100.0%
StreamLake$0.571$2.29128K—100.0%

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
$0.50$2.15164K385 ms29.5 tok/stools · structured
novita
live
$0.70$2.50164K1064 ms18.7 tok/stools · structured
featherless-ai
live
——————

Reported evaluation leads (2)

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
—78.7879
Unpinned
not published
Reported
Quarantined
TIGER-Lab/MMLU-Pro
mmlu_pro
—85
Unpinned
not published
Reported
Quarantined

Other versions (1)

ModelCap Index · Current board

Methodology
59.7
Measured on 2 public benchmarks
Current board
#86 of 352
Score range
54.7–64.7
Rank range
#64–#100
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
61.9% · strong
Identity binding
Exact catalogue product · deepseek/deepseek/deepseek-r1-0528/fp8 · aggregates disclosed benchmark configurations · endpoint configuration not claimed · artifact metadata deepseek-ai/DeepSeek-R1-0528@4236a6af538feda4548eca9ab308586007567f52 (not the evaluation revision)
Index observations used
2
Qualified Index evidence point
59.7
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
59.7
Evidence status
confirmed · 77% mass
General preference
60.1
Coding
57.2
Agents & tools
—
Reasoning
—
Evidence breadth
92%
Evidence coverage
62%
Market and catalogue signals · secondary, never the language Index rank
Usage (OpenRouter popularity)
12.6
Liquidity (providers × uptime)
65.7
Open reach (HF downloads)
49.3
Surface (context / tools / modalities)
71.8
Freshness
13.4
  • · OpenRouter popularity #163
  • · 3 live providers
  • · HF 30d downloads 121043
  • · Catalogue: context 163840, reasoning, tools
  • · First seen 2025-05-28

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
85.0
strong · 94% metadata coverage
Not capability
Artifact reproducibility
85.0
Access & legal clarity
100.0
Deployability
97.0
Evaluation provenance
51.8

Not yet published: the base model it derives from, 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
31.4
OpenRouter weekly popularity
#163 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
#133 of 419
Rating
1421.5
95% confidence interval
1416–1427
Votes
18K
Source published at
28 Oct 2026, 00:00 UTC
Category
overall
Identity match confidence
99%

Market Gravity breakdown

Usage55%
12.6

OpenRouter weekly popularity across the full model catalogue.

Liquidity25%
65.7

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

Open reach15%
49.3

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

Freshness5%
13.4

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

Specification

Model ID
deepseek/deepseek-r1-0528
Context window
164K tokens
Declared output cap
33K 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
$0.35 / 1M
First seen on OpenRouter
28 May 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
4236a6af538f
Parameters
684.5B
Architecture
DeepseekV3ForCausalLM
Model type
deepseek_v3
Hugging Face downloads (30d)
121K
Downloads (all time)
17.1M
Likes
2K
Repository updated
29 May 2025, 11:37 UTC

Compare R1 0528 with

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Benchmark leaderboards featuring R1 0528

All leaderboards
Public benchmark boards on which R1 0528 has a published result
LeaderboardScoreSource rankConfigurationPublished
Arena text leaderboardArena (LMArena)14211416–1427#133 of 419Not reported28 Oct 2026
Arena coding leaderboardArena (LMArena)14641453–1475#136 of 414Default28 Oct 2026

Alternatives to R1 0528, by the numbers

Ranked neighbours

Models within 3 places of #86 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.

R1 0528: common questions

How does R1 0528 rank among AI models?

R1 0528 holds ModelCap Index position #86 of 352 ranked language models as of 6 November 2026, with an Index score of 59.7 (interval 54.7–64.7); evidence: measured. The Index combines public benchmark boards with published uncertainty; the methodology page explains the weighting.

How much does R1 0528 cost per 1M tokens?

R1 0528 is listed at $0.50 per 1M input tokens and $2.15 per 1M output tokens as of 6 November 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 $2.08 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 R1 0528?

R1 0528 has a published context window of 164K tokens (163,840). The snapshot lists a 32,768 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 R1 0528 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-R1-0528 on Hugging Face.

Which API providers serve R1 0528?

3 providers serve R1 0528 through OpenRouter as of 6 November 2026: DeepInfra, SiliconFlow and StreamLake. Each provider's price, context limit, quantization and measured uptime are in the providers table above.

Which benchmarks has R1 0528 been evaluated on?

R1 0528 has published results on 2 public boards tracked by ModelCap as of 6 November 2026: Arena text 1421 (#133 of 419) and Arena coding 1464 (#136 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 R1 0528 compare with DeepSeek V3.2?

R1 0528 ranks #86 (Index 59.7) and DeepSeek V3.2 ranks #82 (Index 60.6) 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 R1 0528 released?

R1 0528 first appeared in the catalogue on 28 May 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.