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BenchLM

Claude Opus 5.5 vs DeepSeek V4 Flash 0731

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.

7 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

Anthropic logo
Model A
Claude Opus 5.5

Anthropic

81.03/100

Estimated · Public rank #5

90% interval 56.4–92.5

DeepSeek logo
Model B
DeepSeek V4 Flash 0731

DeepSeek

—

Evidence status unavailable

90% interval unavailable

Updated September 22, 2026. We do not rank this pair: at least one has no public score. Public scores include evidence status and uncertainty.

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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.

  • Chat turn cost

    1K fresh input + 500 output tokens

    DeepSeek V4 Flash 0731

    DeepSeek V4 Flash 0731 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    Confidence: listed-rates

  • Cache-heavy agent loop cost

    200K cached + 20K fresh input + 10K output tokens

    DeepSeek V4 Flash 0731

    DeepSeek V4 Flash 0731 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 Flash 0731

    DeepSeek V4 Flash 0731 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    Confidence: listed-rates

  • Coding work

    Code generation, repair, and software-engineering tasks

    Not enough matched evidence

    DeepSeek V4 Flash 0731 is not ranked on the public lane for coding, so no winner is named for coding.

    Confidence: limited

  • Agentic work

    Tool use, computer use, and multi-step task completion

    Not enough matched evidence

    DeepSeek V4 Flash 0731 is not ranked on the public lane for agentic, so no winner is named for agentic.

    Confidence: limited

  • Long 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.

76.0Claude Opus 5.5—DeepSeek V4 Flash 0731

Not comparable · BenchAlign

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.

Open the coding leaderboardShortlist models for this job

What is actually comparable

Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.

Shared results
7
Claude Opus 5.5 only
41
DeepSeek V4 Flash 0731 only
33
Like-for-like categories
0 / 8

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign 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
Claude Opus 5.5
82.7
Supported · #1/156
DeepSeek V4 Flash 0731
Not ranked
Basis
BenchAlign lane · 11 vs 11 public rows
Reading
Not comparable

Coding

Not comparable
Claude Opus 5.5
76.0
Estimated · #4/159
DeepSeek V4 Flash 0731
Not ranked
Basis
BenchAlign lane · 9 vs 15 public rows
Reading
Not comparable

Reasoning

Not comparable
Claude Opus 5.5
78.5
#4/19
DeepSeek V4 Flash 0731
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multimodal

Not comparable
Claude Opus 5.5
88.8
#3/50
DeepSeek V4 Flash 0731
Not ranked
Basis
Provisional lane · 1 vs 0 weighted rows
Reading
Not comparable

Knowledge

Not comparable
Claude Opus 5.5
81.5
Estimated · #3/187
DeepSeek V4 Flash 0731
Not ranked
Basis
BenchAlign lane · 17 vs 8 public rows
Reading
Not comparable

Multilingual

Not comparable
Claude Opus 5.5
Not ranked
DeepSeek V4 Flash 0731
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Instruction following

Not comparable
Claude Opus 5.5
Not ranked
DeepSeek V4 Flash 0731
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
Claude Opus 5.5
Not ranked
DeepSeek V4 Flash 0731
79.9
Unranked · 4 rankable rows
Basis
Provisional lane · 0 vs 1 weighted rows
Reading
Not comparable

Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign) differ from the provisional-lane categories. Unranked scores sit on the lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.

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.

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 Opus 5.5
$0.014
Fits in one request
DeepSeek V4 Flash 0731
$0.00028
Fits in one request

DeepSeek V4 Flash 0731 has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

Claude Opus 5.5
$0.26
Fits in one request
DeepSeek V4 Flash 0731
$0.00784
Fits in one request

DeepSeek V4 Flash 0731 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 Opus 5.5
$0.32
Fits in one request
DeepSeek V4 Flash 0731
$0.00616
Fits in one request

DeepSeek V4 Flash 0731 has the lower modeled cost

Costs use the listed standard API rates.

Specification differences

Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.

Cached-input rate

A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.

Claude Opus 5.5

$0.2 per 1M cached input tokens

Claude Opus 5.5 model documentation

DeepSeek V4 Flash 0731

$0.0028 per 1M cached input tokens

Reasoning profile

Claude Opus 5.5

Reasoning

DeepSeek V4 Flash 0731

Reasoning

Weight access

Claude Opus 5.5

Proprietary

DeepSeek V4 Flash 0731

Proprietary

License

Claude Opus 5.5

Proprietary

DeepSeek V4 Flash 0731

Proprietary

Release date

Claude Opus 5.5

2026-09-22

DeepSeek V4 Flash 0731

2026-07-31

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: $0.26 vs $0.00784. Cache-heavy agent loop: $0.32 vs $0.00616.
Context tradeoff
Both models list 1M.

Run the same representative tasks against both endpoints before changing production traffic.

Benchmark evidence

The full public result ledger is available for audit without forcing a wide desktop table onto a phone.

Browse raw public benchmark evidence81 rows

Agentic

  • Terminal-Bench 4.0

    Claude Opus 5.566.40%
    Source
    DeepSeek V4 Flash 0731—

    Not directly comparable

  • Terminal-Bench-Science 0.1

    Claude Opus 5.558.7%
    Source
    DeepSeek V4 Flash 0731—

    Not directly comparable

  • AutomationBench

    Claude Opus 5.540.0%
    Source
    DeepSeek V4 Flash 073125.1%
    Source

    Claude Opus 5.5 leads this result

  • HLE w/ tools

    Claude Opus 5.567.7%
    Source
    DeepSeek V4 Flash 073145.1%
    Source

    Claude Opus 5.5 leads this result

  • OSWorld 2.0

    Claude Opus 5.548.7%
    Source
    DeepSeek V4 Flash 0731—

    Not directly comparable

  • LAB all-pass (Harvey held-out)

    Claude Opus 5.58.3%
    Source
    DeepSeek V4 Flash 0731—

    Not directly comparable

  • LAB criterion-pass (Harvey held-out)

    Claude Opus 5.591.2%
    Source
    DeepSeek V4 Flash 0731—

    Not directly comparable

  • Toolathlon-Verified

    Claude Opus 5.577.8%
    Source
    DeepSeek V4 Flash 073170.3%
    Source

    Claude Opus 5.5 leads this result

  • Toolathlon Verified Pass@3

    Claude Opus 5.582.4%
    Source
    DeepSeek V4 Flash 0731—

    Not directly comparable

  • Toolathlon Verified Pass³

    Claude Opus 5.572.2%
    Source
    DeepSeek V4 Flash 0731—

    Not directly comparable

  • Toolathlon Verified avg. turns

    Claude Opus 5.526.9 turns
    Source
    DeepSeek V4 Flash 0731—

    Not directly comparable

  • Terminal-Bench 2.0

    Claude Opus 5.5—
    DeepSeek V4 Flash 073156.9%
    Source

    Not directly comparable

  • BrowseComp

    Claude Opus 5.5—
    DeepSeek V4 Flash 073173.2%
    Source

    Not directly comparable

  • MCP Atlas

    Claude Opus 5.5—
    DeepSeek V4 Flash 073169%
    Source

    Not directly comparable

  • Toolathlon

    Claude Opus 5.5—
    DeepSeek V4 Flash 073147.8%
    Source

    Not directly comparable

  • Terminal-Bench 2.1

    Claude Opus 5.5—
    DeepSeek V4 Flash 073182.7%
    Source

    Not directly comparable

  • CyberGym

    Claude Opus 5.5—
    DeepSeek V4 Flash 073176.7%
    Source

    Not directly comparable

  • Agents' Last Exam

    Claude Opus 5.5—
    DeepSeek V4 Flash 073125.2%
    Source

    Not directly comparable

  • Terminal-Bench 2.1 (Vals)

    Claude Opus 5.5—
    DeepSeek V4 Flash 073167.0%
    Source

    Not directly comparable

Coding

  • FrontierCode 1.1 Main

    Claude Opus 5.554.4%
    Source
    DeepSeek V4 Flash 0731—

    Not directly comparable

  • cursorBench40

    Claude Opus 5.557.8%
    Source
    DeepSeek V4 Flash 0731—

    Not directly comparable

  • SWE-bench Pro

    Claude Opus 5.589.9%
    Source
    DeepSeek V4 Flash 073152.6%
    Source

    Claude Opus 5.5 leads this result

  • SWE Multilingual

    Claude Opus 5.593.9%
    Source
    DeepSeek V4 Flash 073173.3%
    Source

    Claude Opus 5.5 leads this result

  • SWE Multimodal

    Claude Opus 5.561.4%
    Source
    DeepSeek V4 Flash 0731—

    Not directly comparable

  • DeepSWE

    Claude Opus 5.574.2%
    Source
    DeepSeek V4 Flash 073154.4%
    Source

    Claude Opus 5.5 leads this result

  • FrontierCode 1.1 Extended

    Claude Opus 5.563.6%
    Source
    DeepSeek V4 Flash 0731—

    Not directly comparable

  • FrontierSWE v2

    Claude Opus 5.562.3%
    Source
    DeepSeek V4 Flash 0731—

    Not directly comparable

  • ProgramBench

    Claude Opus 5.591.2%
    Source
    DeepSeek V4 Flash 0731—

    Not directly comparable

  • LiveCodeBench Pass@1-COT

    Claude Opus 5.5—
    DeepSeek V4 Flash 073191.6%
    Source

    Not directly comparable

  • Codeforces

    Claude Opus 5.5—
    DeepSeek V4 Flash 07313052.0
    Source

    Not directly comparable

  • SWE-bench Verified

    Claude Opus 5.5—
    DeepSeek V4 Flash 073179%
    Source

    Not directly comparable

  • Terminal-Bench 2.0

    Claude Opus 5.5—
    DeepSeek V4 Flash 073156.9%
    Source

    Not directly comparable

  • Terminal-Bench 2.1

    Claude Opus 5.5—
    DeepSeek V4 Flash 073182.7%
    Source

    Not directly comparable

  • NL2Repo

    Claude Opus 5.5—
    DeepSeek V4 Flash 073154.2%
    Source

    Not directly comparable

  • DSBench-FullStack

    Claude Opus 5.5—
    DeepSeek V4 Flash 073168.7%
    Source

    Not directly comparable

  • DSBench-Hard

    Claude Opus 5.5—
    DeepSeek V4 Flash 073159.6%
    Source

    Not directly comparable

  • VulcanBench v3

    Claude Opus 5.5—
    DeepSeek V4 Flash 073188.4%
    Source

    Not directly comparable

  • OpenHarmony Bench

    Claude Opus 5.5—
    DeepSeek V4 Flash 073153.8%
    Source

    Not directly comparable

  • LiveCodeBench (Vals)

    Claude Opus 5.5—
    DeepSeek V4 Flash 073187.3%
    Source

    Not directly comparable

  • SWE-bench (Vals)

    Claude Opus 5.5—
    DeepSeek V4 Flash 073188.8%
    Source

    Not directly comparable

Reasoning

  • MRCR 1M

    Claude Opus 5.5—
    DeepSeek V4 Flash 073178.7%
    Source

    Not directly comparable

  • CorpusQA 1M

    Claude Opus 5.5—
    DeepSeek V4 Flash 073160.5%
    Source

    Not directly comparable

Multimodal

  • Chartography (tools)

    Claude Opus 5.589.0%
    Source
    DeepSeek V4 Flash 0731—

    Not directly comparable

  • Chartography (no tools)

    Claude Opus 5.564.4%
    Source
    DeepSeek V4 Flash 0731—

    Not directly comparable

  • BenchCAD Vision2Code (no tools)

    Claude Opus 5.50.730
    Source
    DeepSeek V4 Flash 0731—

    Not directly comparable

  • BenchCAD Vision2Code (tools)

    Claude Opus 5.50.962
    Source
    DeepSeek V4 Flash 0731—

    Not directly comparable

  • Biomedical image analysis

    Claude Opus 5.571.4%
    Source
    DeepSeek V4 Flash 0731—

    Not directly comparable

  • OfficeQA

    Claude Opus 5.578.9%
    Source
    DeepSeek V4 Flash 0731—

    Not directly comparable

  • OfficeQA Pro

    Claude Opus 5.567.7%
    Source
    DeepSeek V4 Flash 0731—

    Not directly comparable

Knowledge

  • HLE

    Claude Opus 5.567.7%
    Source
    DeepSeek V4 Flash 073134.8%
    Source

    Claude Opus 5.5 leads this result

  • HLE w/o tools

    Claude Opus 5.564.4%
    Source
    DeepSeek V4 Flash 0731—

    Not directly comparable

  • HealthBench (raw)

    Claude Opus 5.568.1%
    Source
    DeepSeek V4 Flash 0731—

    Not directly comparable

  • HealthBench (length-adjusted)

    Claude Opus 5.560.6%
    Source
    DeepSeek V4 Flash 0731—

    Not directly comparable

  • HealthBench Professional

    Claude Opus 5.565.6%
    Source
    DeepSeek V4 Flash 0731—

    Not directly comparable

  • HealthBench Professional (raw)

    Claude Opus 5.577.1%
    Source
    DeepSeek V4 Flash 0731—

    Not directly comparable

  • BioMysteryBench (human-solvable)

    Claude Opus 5.589.3%
    Source
    DeepSeek V4 Flash 0731—

    Not directly comparable

  • BioMysteryBench (human-difficult)

    Claude Opus 5.550.0%
    Source
    DeepSeek V4 Flash 0731—

    Not directly comparable

  • SpatialBench Verified

    Claude Opus 5.572.0%
    Source
    DeepSeek V4 Flash 0731—

    Not directly comparable

  • SingleCellBench

    Claude Opus 5.561.2%
    Source
    DeepSeek V4 Flash 0731—

    Not directly comparable

  • Morphology-to-molecule matching

    Claude Opus 5.534.0%
    Source
    DeepSeek V4 Flash 0731—

    Not directly comparable

  • Medicinal chemistry

    Claude Opus 5.563.5%
    Source
    DeepSeek V4 Flash 0731—

    Not directly comparable

  • Protein Design

    Claude Opus 5.560.2%
    Source
    DeepSeek V4 Flash 0731—

    Not directly comparable

  • Protein Design library ranking

    Claude Opus 5.556.0%
    Source
    DeepSeek V4 Flash 0731—

    Not directly comparable

  • De novo protein-binder design

    Claude Opus 5.582.6%
    Source
    DeepSeek V4 Flash 0731—

    Not directly comparable

  • Protocols (troubleshooting)

    Claude Opus 5.573.7%
    Source
    DeepSeek V4 Flash 0731—

    Not directly comparable

  • Protocols (understanding)

    Claude Opus 5.569.0%
    Source
    DeepSeek V4 Flash 0731—

    Not directly comparable

  • MMLU-Pro

    Claude Opus 5.5—
    DeepSeek V4 Flash 073186.2%
    Source

    Not directly comparable

  • SimpleQA

    Claude Opus 5.5—
    DeepSeek V4 Flash 073134.1%
    Source

    Not directly comparable

  • Chinese-SimpleQA

    Claude Opus 5.5—
    DeepSeek V4 Flash 073178.9%
    Source

    Not directly comparable

  • GPQA

    Claude Opus 5.5—
    DeepSeek V4 Flash 073188.1%
    Source

    Not directly comparable

  • GPQA-D

    Claude Opus 5.5—
    DeepSeek V4 Flash 073188.1%
    Source

    Not directly comparable

  • GPQA Diamond (Vals)

    Claude Opus 5.5—
    DeepSeek V4 Flash 073189.9%
    Source

    Not directly comparable

  • MMLU-Pro (Vals)

    Claude Opus 5.5—
    DeepSeek V4 Flash 073186.2%
    Source

    Not directly comparable

Multilingual

  • GMMLU

    Claude Opus 5.594.3%
    Source
    DeepSeek V4 Flash 0731—

    Not directly comparable

  • MILU

    Claude Opus 5.593.1%
    Source
    DeepSeek V4 Flash 0731—

    Not directly comparable

Math

  • ArXivMath Aug. 2026 (no tools)

    Claude Opus 5.591.2%
    Source
    DeepSeek V4 Flash 0731—

    Not directly comparable

  • ArXivMath Aug. 2026 (tools)

    Claude Opus 5.596.9%
    Source
    DeepSeek V4 Flash 0731—

    Not directly comparable

  • HMMT Feb 2026

    Claude Opus 5.5—
    DeepSeek V4 Flash 073194.8%
    Source

    Not directly comparable

  • IMOAnswerBench

    Claude Opus 5.5—
    DeepSeek V4 Flash 073188.4%
    Source

    Not directly comparable

  • Apex

    Claude Opus 5.5—
    DeepSeek V4 Flash 073133.0%
    Source

    Not directly comparable

  • Apex Shortlist

    Claude Opus 5.5—
    DeepSeek V4 Flash 073185.7%
    Source

    Not directly comparable

Questions

Which is better, Claude Opus 5.5 or DeepSeek V4 Flash 0731?

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 Opus 5.5 or DeepSeek V4 Flash 0731?

DeepSeek V4 Flash 0731 is not ranked on the public lane for coding, so no winner is named for coding.

Which is better for agentic tasks, Claude Opus 5.5 or DeepSeek V4 Flash 0731?

DeepSeek V4 Flash 0731 is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.

Which costs less, Claude Opus 5.5 or DeepSeek V4 Flash 0731?

For the stated presets, chat costs $0.014 on Claude Opus 5.5 and $0.00028 on DeepSeek V4 Flash 0731; repository review costs $0.26 and $0.00784; the cache-heavy agent loop costs $0.32 and $0.00616. Costs use the listed standard API rates.

Which has the larger context window, Claude Opus 5.5 or DeepSeek V4 Flash 0731?

Both models list the same context window, 1M.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated September 22, 2026

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