Coding work
Code generation, repair, and software-engineering tasks
Qwen3.8 Max
Qwen3.8 Max leads on the public coding lane, 56 to 50.3, with Supported evidence for both models, although the 90% intervals overlap.
Confidence: limited
DeepSeek V4 Pro 0813 vs Qwen3.8 Max
Updated September 27, 2026. Rank says Qwen3.8 Max is ahead. Price, access, and your workload can each overturn that. 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
Share or export
Decision reading
Qwen3.8 Max has the higher public score estimate, 71.8 versus 63.48, but the 90% score intervals overlap. Treat that as a lead, not a settled winner. 18 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
- Shared results
- 18
- DeepSeek V4 Pro 0813 only
- 24
- Qwen3.8 Max only
- 42
- Like-for-like categories
- 2 / 8
Estimated: DeepSeek V4 Pro 0813 · Supported: Qwen3.8 MaxHow 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.
Agentic work
Tool use, computer use, and multi-step task completion
Qwen3.8 Max
Qwen3.8 Max leads on the public agentic lane, 65.6 to 55, with Supported evidence for both models, although the 90% intervals overlap.
Confidence: limited
Show secondary and unsupported calls
Long documents
Prompts that approach the documented context limit
No clear pick
The documented context windows are equal.
Confidence: documentedChat 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
A complete comparable API-rate estimate is not available for both models.
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.
50.3DeepSeek V4 Pro 081356.0Qwen3.8 Max
Like-for-like · BenchAlign v5.7
Qwen3.8 Max leads the like-for-like coding row, although the 90% intervals overlap.
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.
24 DeepSeek V4 Pro 0813 only
18 Shared
42 Qwen3.8 Max only
1 category rests on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.
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.
SWE-bench ProCoding
Normalized gap 12.3DeepSeek V4 Pro 0813:55.4%Qwen3.8 Max:67.7%AutomationBenchAgentic
Normalized gap 4.5DeepSeek V4 Pro 0813:31.8%Qwen3.8 Max:27.3%GPQAKnowledge
Normalized gap 2.5DeepSeek V4 Pro 0813:90.1%Qwen3.8 Max:92.6%MMLU-Pro (Vals)Knowledge
Normalized gap 1.6DeepSeek V4 Pro 0813:87.0%Qwen3.8 Max:88.6%HLEKnowledge
Normalized gap 0.9DeepSeek V4 Pro 0813:42.7%Qwen3.8 Max:43.6%
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 v5.7 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
Like-for-like- DeepSeek V4 Pro 0813
- 55.0
- Supported · #29/105
- Qwen3.8 Max
- 65.6
- Supported · #10/105
- Basis
- BenchAlign v5.7 lane · 11 vs 15 public rows
- Reading
- Qwen3.8 Max leads · intervals overlap
Coding
Like-for-like- DeepSeek V4 Pro 0813
- 50.3
- Supported · #39/135
- Qwen3.8 Max
- 56.0
- Supported · #24/135
- Basis
- BenchAlign v5.7 lane · 15 vs 12 public rows
- Reading
- Qwen3.8 Max leads · intervals overlap
Knowledge
Directional only- DeepSeek V4 Pro 0813
- 63.4
- Estimated · #29/158
- Qwen3.8 Max
- 66.7
- Supported · #19/158
- Basis
- BenchAlign v5.7 lane · 8 vs 6 public rows
- Reading
- Directional only
Reasoning
Not comparable- DeepSeek V4 Pro 0813
- 56.9
- Unranked · 4 rankable rows
- Qwen3.8 Max
- 87.6
- Unranked · 2 rankable rows
- Basis
- Provisional lane · 1 vs 2 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- DeepSeek V4 Pro 0813
- Not ranked
- Qwen3.8 Max
- 87.4
- #6/50
- Basis
- Provisional lane · 0 vs 2 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- DeepSeek V4 Pro 0813
- Not ranked
- Qwen3.8 Max
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- DeepSeek V4 Pro 0813
- Not ranked
- Qwen3.8 Max
- 90.5
- #16/124
- Basis
- Provisional lane · 0 vs 1 weighted rows
- Reading
- Not comparable
Math
Not comparable- DeepSeek V4 Pro 0813
- 80.2
- Unranked · 4 rankable rows
- Qwen3.8 Max
- Not ranked
- Basis
- Provisional lane · 1 vs 0 weighted rows
- Reading
- Not comparable
| Category | DeepSeek V4 Pro 0813 | Qwen3.8 Max | Basis | Reading |
|---|---|---|---|---|
| Agentic | 55.0Supported · #29/105 | 65.6Supported · #10/105 | Like-for-likeBenchAlign v5.7 lane · 11 vs 15 public rows | Qwen3.8 Max leads · intervals overlap |
| Coding | 50.3Supported · #39/135 | 56.0Supported · #24/135 | Like-for-likeBenchAlign v5.7 lane · 15 vs 12 public rows | Qwen3.8 Max leads · intervals overlap |
| Knowledge | 63.4Estimated · #29/158 | 66.7Supported · #19/158 | Directional onlyBenchAlign v5.7 lane · 8 vs 6 public rows | Directional only |
| Reasoning | 56.9Unranked · 4 rankable rows | 87.6Unranked · 2 rankable rows | Not comparableProvisional lane · 1 vs 2 weighted rows | Not comparable |
| Multimodal | Not ranked | 87.4#6/50 | Not comparableProvisional lane · 0 vs 2 weighted rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Instruction following | Not ranked | 90.5#16/124 | Not comparableProvisional lane · 0 vs 1 weighted rows | Not comparable |
| Math | 80.2Unranked · 4 rankable rows | Not ranked | Not comparableProvisional lane · 1 vs 0 weighted rows | Not comparable |
Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign v5.7) 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 V4 Pro 0813
- $0.0033
- Fits in one request
- Qwen3.8 Max
- API rate not published
- Fits in one request
Qwen3.8 Max has no comparable published API token rate.
Repository review
50K fresh input + 3K output tokens
- DeepSeek V4 Pro 0813
- $0.07788
- Fits in one request
- Qwen3.8 Max
- API rate not published
- Fits in one request
Qwen3.8 Max has no comparable published API token rate.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- DeepSeek V4 Pro 0813
- $0.0748
- Fits in one request
- Qwen3.8 Max
- API rate not published
- Fits in one request
- Cached-input rate unavailable
Qwen3.8 Max 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 V4 Pro 0813Qwen3.8 Max
Context window
Maximum documented context; output-token limits may be lower.
DeepSeek V4 Pro 0813
Qwen3.8 Max
API model ID
DeepSeek V4 Pro 0813
deepseek-v4-pro
DeepSeek models and pricingQwen3.8 Max
qwen3.8-max
Alibaba Cloud Model Studio pricingCached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
DeepSeek V4 Pro 0813
$0.044 per 1M cached input tokens
DeepSeek: Models & PricingQwen3.8 Max
No comparable hosted API rate
Alibaba Cloud Model Studio pricingDocumented inputs
DeepSeek V4 Pro 0813
Qwen3.8 Max
Not sourced
Documented outputs
DeepSeek V4 Pro 0813
Qwen3.8 Max
Not sourced
Provider availability
DeepSeek V4 Pro 0813
Generally Available · DeepSeek API
DeepSeek models and pricing, V4 Pro continuation footnoteQwen3.8 Max
Not sourced
Reasoning profile
DeepSeek V4 Pro 0813
Reasoning
Qwen3.8 Max
Reasoning
Weight access
DeepSeek V4 Pro 0813
Open Weight
Qwen3.8 Max
Open Weight
License
DeepSeek V4 Pro 0813
Open Weight
Qwen3.8 Max
Open Weight
Release date
DeepSeek V4 Pro 0813
2026-08-13
Qwen3.8 Max
2026-08-03
If you already use one of these models
- Deployment change
- The models list different providers, so authentication, endpoint behavior, limits, and feature support may change.
- Quality signal
- Qwen3.8 Max has the higher public score estimate, 71.8 versus 63.48, but the 90% score intervals overlap.
- Workload cost
- A complete comparable API-rate estimate is not available for both models.
- Context tradeoff
- Both models list 1M.
Run the same representative tasks against both endpoints before changing production traffic.
Questions
Which is better, DeepSeek V4 Pro 0813 or Qwen3.8 Max?
Qwen3.8 Max has the higher public score estimate, 71.8 versus 63.48, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.
Which is better for coding, DeepSeek V4 Pro 0813 or Qwen3.8 Max?
Qwen3.8 Max leads the public coding lane, 56 to 50.3, with Supported evidence for both models, although the 90% intervals overlap.
Which is better for agentic tasks, DeepSeek V4 Pro 0813 or Qwen3.8 Max?
Qwen3.8 Max leads the public agentic tasks lane, 65.6 to 55, with Supported evidence for both models, although the 90% intervals overlap.
Which costs less, DeepSeek V4 Pro 0813 or Qwen3.8 Max?
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 V4 Pro 0813 or Qwen3.8 Max?
Both models list the same context window, 1M.
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence84 rows
Agentic
Terminal-Bench 2.0
DeepSeek V4 Pro 081367.9%SourceQwen3.8 Max—Not directly comparable
Terminal-Bench 2.1
DeepSeek V4 Pro 081387.9%SourceQwen3.8 Max86.6%SourceDeepSeek V4 Pro 0813 leads this result
BrowseComp
DeepSeek V4 Pro 081383.4%SourceQwen3.8 Max—Not directly comparable
HLE w/ tools
DeepSeek V4 Pro 081360.0%SourceQwen3.8 Max56.2%SourceDeepSeek V4 Pro 0813 leads this result
MCP Atlas
DeepSeek V4 Pro 081373.6%SourceQwen3.8 Max—Not directly comparable
Toolathlon
DeepSeek V4 Pro 081351.8%SourceQwen3.8 Max—Not directly comparable
CyberGym
DeepSeek V4 Pro 081383.3%SourceQwen3.8 Max—Not directly comparable
Toolathlon-Verified
DeepSeek V4 Pro 081374.1%SourceQwen3.8 Max72.5%SourceDeepSeek V4 Pro 0813 leads this result
Agents' Last Exam
DeepSeek V4 Pro 081325.7%SourceQwen3.8 Max52.4%SourceQwen3.8 Max leads this result
AutomationBench
DeepSeek V4 Pro 081331.8%SourceQwen3.8 Max27.3%SourceDeepSeek V4 Pro 0813 leads this result
Terminal-Bench 2.1 (Vals)
DeepSeek V4 Pro 081354.7%SourceQwen3.8 Max67.4%SourceQwen3.8 Max leads this result
CoWorkBench
DeepSeek V4 Pro 0813—Qwen3.8 Max74.8%SourceNot directly comparable
JobBench
DeepSeek V4 Pro 0813—Qwen3.8 Max53.4%SourceNot directly comparable
skillsBench
DeepSeek V4 Pro 0813—Qwen3.8 Max70.2%SourceNot directly comparable
WideResearch
DeepSeek V4 Pro 0813—Qwen3.8 Max81.9%SourceNot directly comparable
OSWorld-Verified
DeepSeek V4 Pro 0813—Qwen3.8 Max86.1%SourceNot directly comparable
OSWorld 2.0
DeepSeek V4 Pro 0813—Qwen3.8 Max19.4%SourceNot directly comparable
WebArena-Verified
DeepSeek V4 Pro 0813—Qwen3.8 Max66.8%SourceNot directly comparable
AndroidWorld
DeepSeek V4 Pro 0813—Qwen3.8 Max85.3%SourceNot directly comparable
MobileWorld
DeepSeek V4 Pro 0813—Qwen3.8 Max77.8%SourceNot directly comparable
Coding
LiveCodeBench Pass@1-COT
DeepSeek V4 Pro 081393.5%SourceQwen3.8 Max—Not directly comparable
Codeforces
DeepSeek V4 Pro 08133206.0SourceQwen3.8 Max—Not directly comparable
SWE-bench Verified
DeepSeek V4 Pro 081380.6%SourceQwen3.8 Max—Not directly comparable
SWE-bench Pro
DeepSeek V4 Pro 081355.4%SourceQwen3.8 Max67.7%SourceQwen3.8 Max leads this result
SWE Multilingual
DeepSeek V4 Pro 081376.2%SourceQwen3.8 Max—Not directly comparable
Terminal-Bench 2.0
DeepSeek V4 Pro 081367.9%SourceQwen3.8 Max—Not directly comparable
Vibe Code Bench
DeepSeek V4 Pro 081349.93%SourceQwen3.8 Max—Not directly comparable
Terminal-Bench 2.1
DeepSeek V4 Pro 081387.9%SourceQwen3.8 Max86.6%SourceDeepSeek V4 Pro 0813 leads this result
NL2Repo
DeepSeek V4 Pro 081361.5%SourceQwen3.8 Max55.9%SourceDeepSeek V4 Pro 0813 leads this result
DeepSWE
DeepSeek V4 Pro 081362.7%SourceQwen3.8 Max56.6%SourceDeepSeek V4 Pro 0813 leads this result
DSBench-FullStack
DeepSeek V4 Pro 081371.1%SourceQwen3.8 Max—Not directly comparable
DSBench-Hard
DeepSeek V4 Pro 081367.2%SourceQwen3.8 Max—Not directly comparable
OpenHarmony Bench
Shared sourceDeepSeek V4 Pro 081359.0%Qwen3.8 Max60.8%Qwen3.8 Max leads this result
LiveCodeBench (Vals)
DeepSeek V4 Pro 081387.5%SourceQwen3.8 Max87.9%SourceQwen3.8 Max leads this result
SWE-bench (Vals)
DeepSeek V4 Pro 081396.4%SourceQwen3.8 Max85.6%SourceDeepSeek V4 Pro 0813 leads this result
FrontierSWE
DeepSeek V4 Pro 0813—Qwen3.8 Max73.5%SourceNot directly comparable
MLS-Bench Lite
DeepSeek V4 Pro 0813—Qwen3.8 Max41.0%SourceNot directly comparable
PaperBench
DeepSeek V4 Pro 0813—Qwen3.8 Max93.0%SourceNot directly comparable
VulcanBench v3
DeepSeek V4 Pro 0813—Qwen3.8 Max81.2%SourceNot directly comparable
FrontierSWE v2
DeepSeek V4 Pro 0813—Qwen3.8 Max15.8%SourceNot directly comparable
Reasoning
MRCR 1M
DeepSeek V4 Pro 081383.5%SourceQwen3.8 Max—Not directly comparable
CorpusQA 1M
DeepSeek V4 Pro 081362.0%SourceQwen3.8 Max—Not directly comparable
ARC-AGI-1
DeepSeek V4 Pro 081390.00%SourceQwen3.8 Max—Not directly comparable
ARC-AGI-2
DeepSeek V4 Pro 081361.3%SourceQwen3.8 Max—Not directly comparable
MRCRv2
DeepSeek V4 Pro 0813—Qwen3.8 Max92.9%SourceNot directly comparable
LongBench v2
DeepSeek V4 Pro 0813—Qwen3.8 Max66.3%SourceNot directly comparable
Multimodal
MMMU-Pro
DeepSeek V4 Pro 0813—Qwen3.8 Max82.3%SourceNot directly comparable
MathVision
DeepSeek V4 Pro 0813—Qwen3.8 Max95.2%SourceNot directly comparable
MathVision w/ Python
DeepSeek V4 Pro 0813—Qwen3.8 Max97.7%SourceNot directly comparable
BabyVision
DeepSeek V4 Pro 0813—Qwen3.8 Max82.0%SourceNot directly comparable
BabyVision w/ Python
DeepSeek V4 Pro 0813—Qwen3.8 Max91.3%SourceNot directly comparable
ZeroBench
DeepSeek V4 Pro 0813—Qwen3.8 Max24.0%SourceNot directly comparable
ZeroBench w/ Python
DeepSeek V4 Pro 0813—Qwen3.8 Max49.0%SourceNot directly comparable
MedXpertQA (MM)
DeepSeek V4 Pro 0813—Qwen3.8 Max80.4%SourceNot directly comparable
ScreenSpot Pro
DeepSeek V4 Pro 0813—Qwen3.8 Max84.5%SourceNot directly comparable
Vision2Web
DeepSeek V4 Pro 0813—Qwen3.8 Max69.0%SourceNot directly comparable
CharXiv w/o tools
DeepSeek V4 Pro 0813—Qwen3.8 Max88.4%SourceNot directly comparable
CharXiv
DeepSeek V4 Pro 0813—Qwen3.8 Max93.5%SourceNot directly comparable
OmniDocBench 1.5
DeepSeek V4 Pro 0813—Qwen3.8 Max92.1%SourceNot directly comparable
OCRBench V2
DeepSeek V4 Pro 0813—Qwen3.8 Max74.2%SourceNot directly comparable
CC-OCR
DeepSeek V4 Pro 0813—Qwen3.8 Max79.6%SourceNot directly comparable
RealWorldQA
DeepSeek V4 Pro 0813—Qwen3.8 Max88.0%SourceNot directly comparable
ERQA
DeepSeek V4 Pro 0813—Qwen3.8 Max77.8%SourceNot directly comparable
SimpleVQA
DeepSeek V4 Pro 0813—Qwen3.8 Max75.0%SourceNot directly comparable
PerceptionBench
DeepSeek V4 Pro 0813—Qwen3.8 Max63.5%SourceNot directly comparable
Video-MME (with subtitle)
DeepSeek V4 Pro 0813—Qwen3.8 Max90.4%SourceNot directly comparable
VideoMMMU
DeepSeek V4 Pro 0813—Qwen3.8 Max88.7%SourceNot directly comparable
MMVU
DeepSeek V4 Pro 0813—Qwen3.8 Max82.4%SourceNot directly comparable
MLVU (M-Avg)
DeepSeek V4 Pro 0813—Qwen3.8 Max90.8%SourceNot directly comparable
LVBench
DeepSeek V4 Pro 0813—Qwen3.8 Max81.8%SourceNot directly comparable
Knowledge
MMLU-Pro
DeepSeek V4 Pro 081387.5%SourceQwen3.8 Max—Not directly comparable
SimpleQA
DeepSeek V4 Pro 081357.9%SourceQwen3.8 Max—Not directly comparable
Chinese-SimpleQA
DeepSeek V4 Pro 081384.4%SourceQwen3.8 Max—Not directly comparable
GPQA
DeepSeek V4 Pro 081390.1%SourceQwen3.8 Max92.6%SourceQwen3.8 Max leads this result
GPQA-D
DeepSeek V4 Pro 081390.1%SourceQwen3.8 Max92.6%SourceQwen3.8 Max leads this result
HLE
DeepSeek V4 Pro 081342.7%SourceQwen3.8 Max43.6%SourceQwen3.8 Max leads this result
GPQA Diamond (Vals)
DeepSeek V4 Pro 081392.4%SourceQwen3.8 Max93.7%SourceQwen3.8 Max leads this result
MMLU-Pro (Vals)
DeepSeek V4 Pro 081387.0%SourceQwen3.8 Max88.6%SourceQwen3.8 Max leads this result
HLE w/o tools
DeepSeek V4 Pro 0813—Qwen3.8 Max43.6%SourceNot directly comparable
Instruction following
IFBench
DeepSeek V4 Pro 0813—Qwen3.8 Max82.8%SourceNot directly comparable
Math
HMMT Feb 2026
DeepSeek V4 Pro 081395.2%SourceQwen3.8 Max—Not directly comparable
IMOAnswerBench
DeepSeek V4 Pro 081389.8%SourceQwen3.8 Max—Not directly comparable
Apex
DeepSeek V4 Pro 081338.3%SourceQwen3.8 Max—Not directly comparable
Apex Shortlist
DeepSeek V4 Pro 081390.2%SourceQwen3.8 Max—Not directly comparable
84 public results · 18 shared
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Last updated September 27, 2026