Long documents
Prompts that approach the documented context limit
DeepSeek V4 Pro 0813
DeepSeek V4 Pro 0813 has the larger documented context window.
Confidence: documented
DeepSeek-R1-0528 vs DeepSeek V4 Pro 0813
Updated October 14, 2026. We do not rank this pair: at least one has no public score. Public scores include evidence status and uncertainty.
Both of these models will change. Get the price, version and retirement notices for the pair, each with its source. Follow model changes
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Decision reading
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner. 5 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
- Shared results
- 5
- DeepSeek-R1-0528 only
- 5
- DeepSeek V4 Pro 0813 only
- 36
- Like-for-like categories
- 0 / 8
Estimated: DeepSeek V4 Pro 0813. Conditional ranges do not establish rank confidence.How the comparison works
Which one for your work
Recommendations appear only when a shared evidence basis or an explicit operating constraint supports the call. Secondary and unsupported use cases stay disclosed below the initial list.
Show secondary and unsupported calls
Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
DeepSeek-R1-0528 is not ranked on the public lane for coding, so no winner is named for coding.
Confidence: limitedAgentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
DeepSeek-R1-0528 is not ranked on the public lane for agentic, so no winner is named for agentic.
Confidence: limitedChat turn cost
1K fresh input + 500 output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-ratesCache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Not enough matched evidence
The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. DeepSeek-R1-0528 does not fit this workload in one request. DeepSeek-R1-0528 has no comparable published API token rate.
Confidence: listed-ratesRepository review cost
50K fresh input + 3K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
Which one for a specific job
Choose a job from the LLM Selector's task catalog to see the category row it rests on, under the same basis rules as the table below. A directional row stays directional; choosing a job never creates a winner.
The same task catalog as the LLM Selector. Each job names the evidence surface it rests on; nothing here adds a new score.
—DeepSeek-R1-052847.6DeepSeek V4 Pro 0813
Not comparable · BenchAlign v5.8
The coding row is not comparable on the public lane: at least one model is not measured or not ranked there.
Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.
Same basis rules as the category table below
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
5 DeepSeek-R1-0528 only
5 Shared
36 DeepSeek V4 Pro 0813 only
Shape of the matched evidence
Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.
Too few matched category axes support a radar. The ruled list below shows only shared benchmark results; positions use each benchmark’s normalized display scale when available.
HLEKnowledge
Normalized gap 25.0DeepSeek-R1-0528:17.7%DeepSeek V4 Pro 0813:42.7%SWE-bench VerifiedCoding
Normalized gap 23.0DeepSeek-R1-0528:57.6%DeepSeek V4 Pro 0813:80.6%GPQAKnowledge
Normalized gap 9.1DeepSeek-R1-0528:81%DeepSeek V4 Pro 0813:90.1%MMLU-ProKnowledge
Normalized gap 2.5DeepSeek-R1-0528:85%DeepSeek V4 Pro 0813:87.5%
Bars run 0–100 on each benchmark’s normalized display scale
Category results, on a stated basis
Each row shows the public-lane category score for both models: the BenchAlign v5.8 lane for agentic, coding, and knowledge, and the weighted public rows elsewhere, with the same rank each model page reports. A row is like-for-like only when both scores rest on Supported evidence or the same weighted set. Directional and not-comparable rows remain visible, but they never receive a winner.
Agentic
Not comparable- DeepSeek-R1-0528
- Not ranked
- DeepSeek V4 Pro 0813
- 53.1
- Supported · #41/124
- Basis
- BenchAlign v5.8 lane · 0 vs 11 public rows
- Reading
- Not comparable
Coding
Not comparable- DeepSeek-R1-0528
- Not ranked
- DeepSeek V4 Pro 0813
- 47.6
- Supported · #47/149
- Basis
- BenchAlign v5.8 lane · 3 vs 15 public rows
- Reading
- Not comparable
Reasoning
Not comparable- DeepSeek-R1-0528
- Not ranked
- DeepSeek V4 Pro 0813
- 60.7
- Unranked · 4 rankable rows
- Basis
- Provisional lane · 0 vs 1 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- DeepSeek-R1-0528
- Not ranked
- DeepSeek V4 Pro 0813
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Knowledge
Not comparable- DeepSeek-R1-0528
- Not ranked
- DeepSeek V4 Pro 0813
- 63.4
- Estimated · #41/181
- Basis
- BenchAlign v5.8 lane · 5 vs 7 public rows
- Reading
- Not comparable
Multilingual
Not comparable- DeepSeek-R1-0528
- Not ranked
- DeepSeek V4 Pro 0813
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- DeepSeek-R1-0528
- Not ranked
- DeepSeek V4 Pro 0813
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- DeepSeek-R1-0528
- Not ranked
- DeepSeek V4 Pro 0813
- 87.4
- Unranked · 4 rankable rows
- Basis
- Provisional lane · 0 vs 1 weighted rows
- Reading
- Not comparable
| Category | DeepSeek-R1-0528 | DeepSeek V4 Pro 0813 | Basis | Reading |
|---|---|---|---|---|
| Agentic | Not ranked | 53.1Supported · #41/124 | Not comparableBenchAlign v5.8 lane · 0 vs 11 public rows | Not comparable |
| Coding | Not ranked | 47.6Supported · #47/149 | Not comparableBenchAlign v5.8 lane · 3 vs 15 public rows | Not comparable |
| Reasoning | Not ranked | 60.7Unranked · 4 rankable rows | Not comparableProvisional lane · 0 vs 1 weighted rows | Not comparable |
| Multimodal | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Knowledge | Not ranked | 63.4Estimated · #41/181 | Not comparableBenchAlign v5.8 lane · 5 vs 7 public rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Instruction following | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Math | Not ranked | 87.4Unranked · 4 rankable rows | Not comparableProvisional lane · 0 vs 1 weighted rows | Not comparable |
Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign v5.8) differ from the provisional-lane categories. Unranked scores sit on the provisional lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.
Supported evidence per lane · bars run 0–100Methodology
What each workload costs
Three fixed token mixes turn per-token rates into comparable decisions. Each scenario states context fit and whether cached input had to fall back to the published list-input rate.
Chat turn
1K fresh input + 500 output tokens
- DeepSeek-R1-0528
- API rate not published
- Fits in one request
- DeepSeek V4 Pro 0813
- $0.0033
- Fits in one request
DeepSeek-R1-0528 has no comparable published API token rate.
Repository review
50K fresh input + 3K output tokens
- DeepSeek-R1-0528
- API rate not published
- Fits in one request
- DeepSeek V4 Pro 0813
- $0.07788
- Fits in one request
DeepSeek-R1-0528 has no comparable published API token rate.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- DeepSeek-R1-0528
- API rate not published
- Does not fit in one request
- Cached-input rate unavailable
- DeepSeek V4 Pro 0813
- $0.0748
- Fits in one request
DeepSeek-R1-0528 does not fit this workload in one request. DeepSeek-R1-0528 has no comparable published API token rate.
Cached input falls back to the list input rate only where a cached rate is unpublished
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationDeepSeek-R1-0528DeepSeek V4 Pro 0813
Context window
Maximum documented context; output-token limits may be lower.
DeepSeek-R1-0528
128K
DeepSeek V4 Pro 0813
API model ID
DeepSeek-R1-0528
Not sourced
DeepSeek V4 Pro 0813
deepseek-v4-pro
DeepSeek models and pricingCached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
DeepSeek-R1-0528
No comparable hosted API rate
DeepSeek V4 Pro 0813
$0.044 per 1M cached input tokens
DeepSeek: Models & PricingDocumented inputs
DeepSeek-R1-0528
Not sourced
DeepSeek V4 Pro 0813
Documented outputs
DeepSeek-R1-0528
Not sourced
DeepSeek V4 Pro 0813
Provider availability
DeepSeek-R1-0528
Not sourced
DeepSeek V4 Pro 0813
Generally Available · DeepSeek API
DeepSeek models and pricing, V4 Pro continuation footnoteReasoning profile
DeepSeek-R1-0528
Reasoning
DeepSeek V4 Pro 0813
Reasoning
Weight access
DeepSeek-R1-0528
Open Weight
DeepSeek V4 Pro 0813
Open Weight
License
DeepSeek-R1-0528
Open Weight
DeepSeek V4 Pro 0813
Open Weight
Release date
DeepSeek-R1-0528
2025-05-28
DeepSeek V4 Pro 0813
2026-08-13
If you already use one of these models
- Deployment change
- Both entries list DeepSeek as the provider. Confirm endpoint, model ID, limits, and feature support before switching.
- Quality signal
- At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.
- Workload cost
- A complete comparable API-rate estimate is not available for both models.
- Context tradeoff
- DeepSeek V4 Pro 0813 has the larger documented window (1M).
Run the same representative tasks against both endpoints before changing production traffic.
Questions
Which is better, DeepSeek-R1-0528 or DeepSeek V4 Pro 0813?
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner. The page therefore keeps the decision tied to the specific documented workload.
Which is better for coding, DeepSeek-R1-0528 or DeepSeek V4 Pro 0813?
DeepSeek-R1-0528 is not ranked on the public lane for coding, so no winner is named for coding.
Which is better for agentic tasks, DeepSeek-R1-0528 or DeepSeek V4 Pro 0813?
DeepSeek-R1-0528 is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.
Which costs less, DeepSeek-R1-0528 or DeepSeek V4 Pro 0813?
Both models do not have comparable published API token rates, so this page does not name a universal price winner.
Which has the larger context window, DeepSeek-R1-0528 or DeepSeek V4 Pro 0813?
DeepSeek V4 Pro 0813 has the larger documented context window: 1M, compared with 128K.
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence46 rows
Agentic
Terminal-Bench 2.0
DeepSeek-R1-0528—DeepSeek V4 Pro 081367.9%SourceNot directly comparable
Terminal-Bench 2.1
DeepSeek-R1-0528—DeepSeek V4 Pro 081387.9%SourceNot directly comparable
BrowseComp
DeepSeek-R1-0528—DeepSeek V4 Pro 081383.4%SourceNot directly comparable
HLE w/ tools
DeepSeek-R1-0528—DeepSeek V4 Pro 081360.0%SourceNot directly comparable
MCP Atlas
DeepSeek-R1-0528—DeepSeek V4 Pro 081373.6%SourceNot directly comparable
Toolathlon
DeepSeek-R1-0528—DeepSeek V4 Pro 081351.8%SourceNot directly comparable
CyberGym
DeepSeek-R1-0528—DeepSeek V4 Pro 081383.3%SourceNot directly comparable
Toolathlon-Verified
DeepSeek-R1-0528—DeepSeek V4 Pro 081374.1%SourceNot directly comparable
Agents' Last Exam
DeepSeek-R1-0528—DeepSeek V4 Pro 081325.7%SourceNot directly comparable
AutomationBench
DeepSeek-R1-0528—DeepSeek V4 Pro 081331.8%SourceNot directly comparable
Terminal-Bench 2.1 (Vals)
DeepSeek-R1-0528—DeepSeek V4 Pro 081354.7%SourceNot directly comparable
Coding
LiveCodeBench
DeepSeek-R1-052873.3%SourceDeepSeek V4 Pro 0813—Not directly comparable
Codeforces
DeepSeek-R1-05281930.0SourceDeepSeek V4 Pro 08133206.0SourceDeepSeek V4 Pro 0813 leads this result
SWE-bench Verified
DeepSeek-R1-052857.6%SourceDeepSeek V4 Pro 081380.6%SourceDeepSeek V4 Pro 0813 leads this result
LiveCodeBench Pass@1-COT
DeepSeek-R1-0528—DeepSeek V4 Pro 081393.5%SourceNot directly comparable
SWE-bench Pro
DeepSeek-R1-0528—DeepSeek V4 Pro 081355.4%SourceNot directly comparable
SWE Multilingual
DeepSeek-R1-0528—DeepSeek V4 Pro 081376.2%SourceNot directly comparable
Terminal-Bench 2.0
DeepSeek-R1-0528—DeepSeek V4 Pro 081367.9%SourceNot directly comparable
Vibe Code Bench
DeepSeek-R1-0528—DeepSeek V4 Pro 081349.93%SourceNot directly comparable
Terminal-Bench 2.1
DeepSeek-R1-0528—DeepSeek V4 Pro 081387.9%SourceNot directly comparable
NL2Repo
DeepSeek-R1-0528—DeepSeek V4 Pro 081361.5%SourceNot directly comparable
DeepSWE
DeepSeek-R1-0528—DeepSeek V4 Pro 081362.7%SourceNot directly comparable
DSBench-FullStack
DeepSeek-R1-0528—DeepSeek V4 Pro 081371.1%SourceNot directly comparable
DSBench-Hard
DeepSeek-R1-0528—DeepSeek V4 Pro 081367.2%SourceNot directly comparable
OpenHarmony Bench
DeepSeek-R1-0528—DeepSeek V4 Pro 081359.0%SourceNot directly comparable
LiveCodeBench (Vals)
DeepSeek-R1-0528—DeepSeek V4 Pro 081387.5%SourceNot directly comparable
SWE-bench (Vals)
DeepSeek-R1-0528—DeepSeek V4 Pro 081396.4%SourceNot directly comparable
Reasoning
MRCR 1M
DeepSeek-R1-0528—DeepSeek V4 Pro 081383.5%SourceNot directly comparable
CorpusQA 1M
DeepSeek-R1-0528—DeepSeek V4 Pro 081362.0%SourceNot directly comparable
ARC-AGI-1
DeepSeek-R1-0528—DeepSeek V4 Pro 081390.00%SourceNot directly comparable
ARC-AGI-2
DeepSeek-R1-0528—DeepSeek V4 Pro 081361.3%SourceNot directly comparable
Knowledge
MMLU-Redux
DeepSeek-R1-052893.4%SourceDeepSeek V4 Pro 0813—Not directly comparable
MMLU-Pro
DeepSeek-R1-052885%SourceDeepSeek V4 Pro 081387.5%SourceDeepSeek V4 Pro 0813 leads this result
GPQA
DeepSeek-R1-052881%SourceDeepSeek V4 Pro 081390.1%SourceDeepSeek V4 Pro 0813 leads this result
SimpleQA
DeepSeek-R1-052827.8%SourceDeepSeek V4 Pro 0813—Not directly comparable
HLE
DeepSeek-R1-052817.7%SourceDeepSeek V4 Pro 081342.7%SourceDeepSeek V4 Pro 0813 leads this result
Chinese-SimpleQA
DeepSeek-R1-0528—DeepSeek V4 Pro 081384.4%SourceNot directly comparable
GPQA-D
DeepSeek-R1-0528—DeepSeek V4 Pro 081390.1%SourceNot directly comparable
GPQA Diamond (Vals)
DeepSeek-R1-0528—DeepSeek V4 Pro 081392.4%SourceNot directly comparable
MMLU-Pro (Vals)
DeepSeek-R1-0528—DeepSeek V4 Pro 081387.0%SourceNot directly comparable
Math
AIME 2024
DeepSeek-R1-052891.4%SourceDeepSeek V4 Pro 0813—Not directly comparable
AIME 2025
DeepSeek-R1-052887.5%SourceDeepSeek V4 Pro 0813—Not directly comparable
HMMT Feb 2026
DeepSeek-R1-0528—DeepSeek V4 Pro 081395.2%SourceNot directly comparable
IMOAnswerBench
DeepSeek-R1-0528—DeepSeek V4 Pro 081389.8%SourceNot directly comparable
Apex
DeepSeek-R1-0528—DeepSeek V4 Pro 081338.3%SourceNot directly comparable
Apex Shortlist
DeepSeek-R1-0528—DeepSeek V4 Pro 081390.2%SourceNot directly comparable
46 public results · 5 shared
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Last updated October 14, 2026