Chat turn cost
1K fresh input + 500 output tokens
DeepSeek V4 Pro 0813
DeepSeek V4 Pro 0813 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Claude Mythos 5 vs DeepSeek V4 Pro 0813
Updated November 11, 2026. We do not rank this pair: at least one has no public score. Public scores include evidence status and uncertainty.
Share or export
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. 8 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
- API price per 1M tokens
Claude Mythos 5: $10 input / $50 output
DeepSeek V4 Pro 0813: $1.32 input / $3.96 output
- Context window
Claude Mythos 5: 1M
DeepSeek V4 Pro 0813: 1M
- Released
Claude Mythos 5: June 9, 2026
DeepSeek V4 Pro 0813: August 13, 2026
- Shared results
- 8
- Claude Mythos 5 only
- 7
- DeepSeek V4 Pro 0813 only
- 34
- 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.
Cache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
DeepSeek V4 Pro 0813
DeepSeek V4 Pro 0813 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Show secondary and unsupported calls
Repository review cost
50K fresh input + 3K output tokens
DeepSeek V4 Pro 0813
DeepSeek V4 Pro 0813 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-ratesCoding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
Claude Mythos 5 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
Claude Mythos 5 is not ranked on the public lane for agentic, so no winner is named for agentic.
Confidence: limitedLong documents
Prompts that approach the documented context limit
No clear pick
The documented context windows are equal.
Confidence: documented
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.
—Claude Mythos 547.9DeepSeek 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
Or describe your own job
The LLM Selector reads what you need a model for and returns a shortlist, ranked in the same order the job pages publish.
Describe the task and constraints. This selector recommends models; it cannot carry out the task or access your files and accounts.
We keep what you type here, drafts included, for 180 days, and after that only the job and requirements read from it. Nothing is tied to your IP address or account. Leave out names and other personal details. Privacy
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
7 Claude Mythos 5 only
8 Shared
34 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.
SWE-bench ProCoding
Normalized gap 24.9Claude Mythos 5:80.3%DeepSeek V4 Pro 0813:55.4%HLEKnowledge
Normalized gap 21.8Claude Mythos 5:64.5%DeepSeek V4 Pro 0813:42.7%SWE-bench VerifiedCoding
Normalized gap 14.9Claude Mythos 5:95.5%DeepSeek V4 Pro 0813:80.6%BrowseCompAgentic
Normalized gap 4.6Claude Mythos 5:88%DeepSeek V4 Pro 0813:83.4%GPQAKnowledge
Normalized gap 4.0Claude Mythos 5:94.1%DeepSeek V4 Pro 0813:90.1%
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, reasoning, multimodal, 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- Claude Mythos 5
- Not ranked
- DeepSeek V4 Pro 0813
- 55.0
- Supported · #44/132
- Basis
- BenchAlign v5.8 lane · 4 vs 12 public rows
- Reading
- Not comparable
Coding
Not comparable- Claude Mythos 5
- Not ranked
- DeepSeek V4 Pro 0813
- 47.9
- Supported · #53/158
- Basis
- BenchAlign v5.8 lane · 3 vs 15 public rows
- Reading
- Not comparable
Reasoning
Not comparable- Claude Mythos 5
- Not ranked
- DeepSeek V4 Pro 0813
- 58.1
- Estimated · #39/158
- Basis
- BenchAlign v5.8 lane · 0 vs 4 public rows
- Reading
- Not comparable
Multimodal
Not comparable- Claude Mythos 5
- Not ranked
- DeepSeek V4 Pro 0813
- Not ranked
- Basis
- BenchAlign v5.8 lane · 3 vs 0 public rows
- Reading
- Not comparable
Knowledge
Not comparable- Claude Mythos 5
- Not ranked
- DeepSeek V4 Pro 0813
- 62.5
- Estimated · #41/179
- Basis
- BenchAlign v5.8 lane · 3 vs 7 public rows
- Reading
- Not comparable
Multilingual
Not comparable- Claude Mythos 5
- Not ranked
- DeepSeek V4 Pro 0813
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- Claude Mythos 5
- Not ranked
- DeepSeek V4 Pro 0813
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- Claude Mythos 5
- Not ranked
- DeepSeek V4 Pro 0813
- 84.4
- Unranked · 4 rankable rows
- Basis
- Provisional lane · 1 vs 1 weighted rows
- Reading
- Not comparable
| Category | Claude Mythos 5 | DeepSeek V4 Pro 0813 | Basis | Reading |
|---|---|---|---|---|
| Agentic | Not ranked | 55.0Supported · #44/132 | Not comparableBenchAlign v5.8 lane · 4 vs 12 public rows | Not comparable |
| Coding | Not ranked | 47.9Supported · #53/158 | Not comparableBenchAlign v5.8 lane · 3 vs 15 public rows | Not comparable |
| Reasoning | Not ranked | 58.1Estimated · #39/158 | Not comparableBenchAlign v5.8 lane · 0 vs 4 public rows | Not comparable |
| Multimodal | Not ranked | Not ranked | Not comparableBenchAlign v5.8 lane · 3 vs 0 public rows | Not comparable |
| Knowledge | Not ranked | 62.5Estimated · #41/179 | Not comparableBenchAlign v5.8 lane · 3 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 | 84.4Unranked · 4 rankable rows | Not comparableProvisional lane · 1 vs 1 weighted rows | Not comparable |
Ranks count the models scored in each category’s lane, so the agentic, coding, reasoning, multimodal, 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
- Claude Mythos 5
- $0.035
- Fits in one request
- DeepSeek V4 Pro 0813
- $0.0033
- Fits in one request
DeepSeek V4 Pro 0813 has the lower modeled cost
Costs use the listed standard API rates.
Repository review
50K fresh input + 3K output tokens
- Claude Mythos 5
- $0.65
- Fits in one request
- DeepSeek V4 Pro 0813
- $0.07788
- Fits in one request
DeepSeek V4 Pro 0813 has the lower modeled cost
Costs use the listed standard API rates.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Claude Mythos 5
- $0.9
- Fits in one request
- DeepSeek V4 Pro 0813
- $0.0748
- Fits in one request
DeepSeek V4 Pro 0813 has the lower modeled cost
Costs use the listed standard API rates.
Your workload
Enter a month of tokens to price it at both models’ listed API rates.
- Claude Mythos 5
- $200.00
- per month
- DeepSeek V4 Pro 0813
- $21.12
- per month
Standard listed rates, no batch or volume discounts.
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.
SpecificationClaude Mythos 5DeepSeek V4 Pro 0813
Context window
Maximum documented context; output-token limits may be lower.
Claude Mythos 5
DeepSeek V4 Pro 0813
API model ID
Claude Mythos 5
claude-mythos-5
Anthropic model overviewDeepSeek 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.
Claude Mythos 5
$1 per 1M cached input tokens
Claude API pricingDeepSeek V4 Pro 0813
$0.044 per 1M cached input tokens
DeepSeek: Models & PricingDocumented inputs
Claude Mythos 5
text, image
Anthropic model overviewDeepSeek V4 Pro 0813
Documented outputs
Claude Mythos 5
DeepSeek V4 Pro 0813
Provider availability
Claude Mythos 5
Limited Access · Claude API
Anthropic model overviewDeepSeek V4 Pro 0813
Generally Available · DeepSeek API
DeepSeek models and pricing, V4 Pro continuation footnoteReasoning profile
Claude Mythos 5
Reasoning
DeepSeek V4 Pro 0813
Reasoning
Weight access
Claude Mythos 5
Proprietary
DeepSeek V4 Pro 0813
Open Weight
License
Claude Mythos 5
Proprietary
DeepSeek V4 Pro 0813
Open Weight
Release date
Claude Mythos 5
2026-06-09
DeepSeek V4 Pro 0813
2026-08-13
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
- 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
- Repository review: $0.65 vs $0.07788. Cache-heavy agent loop: $0.9 vs $0.0748.
- Context tradeoff
- Both models list 1M.
Run the same representative tasks against both endpoints before changing production traffic.
Questions
Which is better, Claude Mythos 5 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, Claude Mythos 5 or DeepSeek V4 Pro 0813?
Claude Mythos 5 is not ranked on the public lane for coding, so no winner is named for coding.
Which is better for agentic tasks, Claude Mythos 5 or DeepSeek V4 Pro 0813?
Claude Mythos 5 is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.
Which costs less, Claude Mythos 5 or DeepSeek V4 Pro 0813?
For the stated presets, chat costs $0.035 on Claude Mythos 5 and $0.0033 on DeepSeek V4 Pro 0813; repository review costs $0.65 and $0.07788; the cache-heavy agent loop costs $0.9 and $0.0748. Costs use the listed standard API rates.
Which has the larger context window, Claude Mythos 5 or DeepSeek V4 Pro 0813?
Both models list the same context window, 1M.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
Claude Mythos 5
API / mo$45,000
Self-host / moNot listed
Break-even—
Proprietary model — self-hosting not applicable.
DeepSeek V4 Pro 0813
API / mo$3,960
Self-host / mo$37,843
Break-evenNot reached at 70% load
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence49 rows
Agentic
Terminal-Bench 2.1
Claude Mythos 588.0%SourceDeepSeek V4 Pro 081387.9%SourceClaude Mythos 5 leads this result
OSWorld-Verified
Claude Mythos 585%SourceDeepSeek V4 Pro 0813—Not directly comparable
BrowseComp
Claude Mythos 588%SourceDeepSeek V4 Pro 081383.4%SourceClaude Mythos 5 leads this result
CyberGym
Claude Mythos 583.8%SourceDeepSeek V4 Pro 081383.3%SourceClaude Mythos 5 leads this result
Finch
Claude Mythos 5—DeepSeek V4 Pro 081367.4%SourceNot directly comparable
Terminal-Bench 2.0
Claude Mythos 5—DeepSeek V4 Pro 081367.9%SourceNot directly comparable
HLE w/ tools
Claude Mythos 5—DeepSeek V4 Pro 081360.0%SourceNot directly comparable
MCP Atlas
Claude Mythos 5—DeepSeek V4 Pro 081373.6%SourceNot directly comparable
Toolathlon
Claude Mythos 5—DeepSeek V4 Pro 081351.8%SourceNot directly comparable
Toolathlon-Verified
Claude Mythos 5—DeepSeek V4 Pro 081374.1%SourceNot directly comparable
Agents' Last Exam
Claude Mythos 5—DeepSeek V4 Pro 081325.7%SourceNot directly comparable
AutomationBench
Claude Mythos 5—DeepSeek V4 Pro 081331.8%SourceNot directly comparable
Terminal-Bench 2.1 (Vals)
Claude Mythos 5—DeepSeek V4 Pro 081354.7%SourceNot directly comparable
Coding
SWE-bench Verified
Claude Mythos 595.5%SourceDeepSeek V4 Pro 081380.6%SourceClaude Mythos 5 leads this result
SWE-bench Pro
Claude Mythos 580.3%SourceDeepSeek V4 Pro 081355.4%SourceClaude Mythos 5 leads this result
Terminal-Bench 2.1
Claude Mythos 588.0%SourceDeepSeek V4 Pro 081387.9%SourceClaude Mythos 5 leads this result
LiveCodeBench Pass@1-COT
Claude Mythos 5—DeepSeek V4 Pro 081393.5%SourceNot directly comparable
Codeforces
Claude Mythos 5—DeepSeek V4 Pro 08133206.0SourceNot directly comparable
SWE Multilingual
Claude Mythos 5—DeepSeek V4 Pro 081376.2%SourceNot directly comparable
Terminal-Bench 2.0
Claude Mythos 5—DeepSeek V4 Pro 081367.9%SourceNot directly comparable
Vibe Code Bench
Claude Mythos 5—DeepSeek V4 Pro 081349.93%SourceNot directly comparable
NL2Repo
Claude Mythos 5—DeepSeek V4 Pro 081361.5%SourceNot directly comparable
DeepSWE
Claude Mythos 5—DeepSeek V4 Pro 081362.7%SourceNot directly comparable
DSBench-FullStack
Claude Mythos 5—DeepSeek V4 Pro 081371.1%SourceNot directly comparable
DSBench-Hard
Claude Mythos 5—DeepSeek V4 Pro 081367.2%SourceNot directly comparable
OpenHarmony Bench
Claude Mythos 5—DeepSeek V4 Pro 081359.0%SourceNot directly comparable
LiveCodeBench (Vals)
Claude Mythos 5—DeepSeek V4 Pro 081387.5%SourceNot directly comparable
SWE-bench (Vals)
Claude Mythos 5—DeepSeek V4 Pro 081396.4%SourceNot directly comparable
Reasoning
MRCR 1M
Claude Mythos 5—DeepSeek V4 Pro 081383.5%SourceNot directly comparable
CorpusQA 1M
Claude Mythos 5—DeepSeek V4 Pro 081362.0%SourceNot directly comparable
ARC-AGI-1
Claude Mythos 5—DeepSeek V4 Pro 081390.00%SourceNot directly comparable
ARC-AGI-2
Claude Mythos 5—DeepSeek V4 Pro 081361.3%SourceNot directly comparable
Multimodal
Knowledge
GPQA
Claude Mythos 594.1%SourceDeepSeek V4 Pro 081390.1%SourceClaude Mythos 5 leads this result
HLE
Claude Mythos 564.5%SourceDeepSeek V4 Pro 081342.7%SourceClaude Mythos 5 leads this result
HLE w/o tools
Claude Mythos 559%SourceDeepSeek V4 Pro 0813—Not directly comparable
MMLU-Pro
Claude Mythos 5—DeepSeek V4 Pro 081387.5%SourceNot directly comparable
Chinese-SimpleQA
Claude Mythos 5—DeepSeek V4 Pro 081384.4%SourceNot directly comparable
GPQA-D
Claude Mythos 5—DeepSeek V4 Pro 081390.1%SourceNot directly comparable
GPQA Diamond (Vals)
Claude Mythos 5—DeepSeek V4 Pro 081392.4%SourceNot directly comparable
MMLU-Pro (Vals)
Claude Mythos 5—DeepSeek V4 Pro 081387.0%SourceNot directly comparable
Multilingual
SWE Multilingual
Claude Mythos 592.2%SourceDeepSeek V4 Pro 0813—Not directly comparable
Math
USAMO 2026
Claude Mythos 597.6%SourceDeepSeek V4 Pro 0813—Not directly comparable
HMMT Feb 2026
Claude Mythos 5—DeepSeek V4 Pro 081395.2%SourceNot directly comparable
IMOAnswerBench
Claude Mythos 5—DeepSeek V4 Pro 081389.8%SourceNot directly comparable
Apex
Claude Mythos 5—DeepSeek V4 Pro 081338.3%SourceNot directly comparable
Apex Shortlist
Claude Mythos 5—DeepSeek V4 Pro 081390.2%SourceNot directly comparable
49 public results · 8 shared
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Last updated November 11, 2026