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BenchLM
Data

Claude Opus 4.5 vs DeepSeek V3

Updated November 13, 2026. Rank says Claude Opus 4.5 is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.

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Decision reading

Claude Opus 4.5 has the higher public score estimate, 52.96 versus 31.53, but the 90% score intervals overlap. Treat that as a lead, not a settled winner. 5 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

Model A
Anthropic logo
Claude Opus 4.5

Anthropic

52.96/100

Supported · Public rank #77

90% interval 40.0–66.0

Model B
DeepSeek logo
DeepSeek V3

DeepSeek

31.53/100

Supported · Public rank #169

90% interval 15.2–47.9

API price per 1M tokens

Claude Opus 4.5: $5 input / $25 output

DeepSeek V3: $0.27 input / $1.10 output

Context window

Claude Opus 4.5: 200K

DeepSeek V3: 128K

Released

Claude Opus 4.5: November 24, 2025

DeepSeek V3: December 26, 2024

Shared results
5
Claude Opus 4.5 only
60
DeepSeek V3 only
4
Like-for-like categories
2 / 8
Supported: Claude Opus 4.5 and DeepSeek V3How 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.

  • Long documents

    Prompts that approach the documented context limit

    Claude Opus 4.5

    Claude Opus 4.5 has the larger documented context window.

    Confidence: documented

  • Chat turn cost

    1K fresh input + 500 output tokens

    DeepSeek V3

    DeepSeek V3 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 V3

    DeepSeek V3 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 V3 is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like.

    Confidence: limited

  • Agentic work

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

    Not enough matched evidence

    DeepSeek V3 is scored on Estimated evidence for agentic, so the reading is directional rather than like-for-like.

    Confidence: limited

  • Cache-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. Claude Opus 4.5 does not fit this workload in one request. DeepSeek V3 does not fit this workload in one request. Claude Opus 4.5 has no published cached-input rate, so cached tokens use its listed input rate.

    Confidence: rate-fallback

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.

43.6Claude Opus 4.516.7DeepSeek V3

Directional only · BenchAlign v5.8

Claude Opus 4.5 has the higher coding point estimate. Conditional score ranges do not establish rank confidence.

Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.

Open the coding leaderboardShortlist models for this job
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.

3 categories rest 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.

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.

Reasoning

Like-for-like
Claude Opus 4.5
41.2
Supported · #76/160
DeepSeek V3
24.8
Supported · #130/160
Basis
BenchAlign v5.8 lane · 2 vs 1 public rows
Reading
Claude Opus 4.5 leads · intervals overlap

Knowledge

Like-for-like
Claude Opus 4.5
50.1
Supported · #78/180
DeepSeek V3
30.8
Supported · #144/180
Basis
BenchAlign v5.8 lane · 8 vs 3 public rows
Reading
Claude Opus 4.5 leads · intervals overlap

Agentic

Directional only
Claude Opus 4.5
27.3
Supported · #109/135
DeepSeek V3
14.9
Estimated · #128/135
Basis
BenchAlign v5.8 lane · 15 vs 0 public rows
Reading
Directional only

Coding

Directional only
Claude Opus 4.5
43.6
Supported · #64/162
DeepSeek V3
16.7
Estimated · #147/162
Basis
BenchAlign v5.8 lane · 8 vs 2 public rows
Reading
Directional only

Instruction following

Directional only
Claude Opus 4.5
31.9
#139/157
DeepSeek V3
39.6
#124/157
Basis
Provisional lane · 1 vs 0 weighted rows
Reading
Directional only

Multimodal

Not comparable
Claude Opus 4.5
49.5
Estimated · #59/67
DeepSeek V3
Not ranked
Basis
BenchAlign v5.8 lane · 18 vs 0 public rows
Reading
Not comparable

Multilingual

Not comparable
Claude Opus 4.5
96.5
#2/17
DeepSeek V3
Not ranked
Basis
Provisional lane · 1 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
Claude Opus 4.5
52.9
#10/12
DeepSeek V3
Not ranked
Basis
Provisional lane · 4 vs 0 weighted rows
Reading
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 Opus 4.5
$0.0175
Fits in one request
DeepSeek V3
$0.00082
Fits in one request

DeepSeek V3 has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

Claude Opus 4.5
$0.325
Fits in one request
DeepSeek V3
$0.0168
Fits in one request

DeepSeek V3 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 4.5
$1.35
Does not fit in one request
Cached input priced at the published list-input rate
DeepSeek V3
$0.0304
Does not fit in one request

Claude Opus 4.5 does not fit this workload in one request. DeepSeek V3 does not fit this workload in one request. Claude Opus 4.5 has no published cached-input rate, so cached tokens use its listed input rate.

Your workload

Enter a month of tokens to price it at both models’ listed API rates.

Claude Opus 4.5
$100.00
per month
DeepSeek V3
$4.90
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

Price against score, among all priced models

Overall score against output price per 1M tokens, one model per family. Pricing as of November 12, 2026.

Claude Opus 4.5DeepSeek V3

20406080100$0.10$0.50$1$5$10$50$100Output price, $ per 1M tokens (log)Overall score
  • 40 models score at least as high as Claude Opus 4.5 for the same price or less. The nearest is Claude Opus 5 (score 76.1, also $25.00 per 1M output tokens).
  • 16 models score at least as high as DeepSeek V3 for the same price or less. The nearest is GLM-4.5-Air (score 34.7, also $1.10 per 1M output tokens).

Gray dots are the other priced models. The dark step line is the efficiency frontier: for a model under it, another model costs no more and scores at least as high.

See DeepSeek V3 on the full price vs performance chart

Specification differences

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

Context window

Maximum documented context; output-token limits may be lower.

Claude Opus 4.5

200K

DeepSeek V3

128K

API model ID

Claude Opus 4.5

Not sourced

DeepSeek V3

Not sourced

Cached-input rate

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

Claude Opus 4.5

Not published

DeepSeek V3

$0.07 per 1M cached input tokens

Provider availability

Claude Opus 4.5

Not sourced

DeepSeek V3

Not sourced

Reasoning profile

Claude Opus 4.5

Non-Reasoning

DeepSeek V3

Non-Reasoning

Weight access

Claude Opus 4.5

Proprietary

DeepSeek V3

Open Weight

License

Claude Opus 4.5

Proprietary

DeepSeek V3

Open Weight

Release date

Claude Opus 4.5

2025-11-24

DeepSeek V3

2024-12-26

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
Claude Opus 4.5 has the higher public score estimate, 52.96 versus 31.53, but the 90% score intervals overlap.
Workload cost
Repository review: $0.325 vs $0.0168. Cache-heavy agent loop: $1.35 vs $0.0304.
Context tradeoff
Claude Opus 4.5 has the larger documented window (200K).
Run the same representative tasks against both endpoints before changing production traffic.

Questions

Which is better, Claude Opus 4.5 or DeepSeek V3?

Claude Opus 4.5 has the higher public score estimate, 52.96 versus 31.53, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.

Which is better for coding, Claude Opus 4.5 or DeepSeek V3?

Claude Opus 4.5 scores higher for coding on the public lane, 43.6 to 16.7. DeepSeek V3 is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like. BenchLM does not name a winner for coding from a directional reading; read the shared benchmark rows directly and test the models on the same task set.

Which is better for agentic tasks, Claude Opus 4.5 or DeepSeek V3?

Claude Opus 4.5 scores higher for agentic tasks on the public lane, 27.3 to 14.9. DeepSeek V3 is scored on Estimated evidence for agentic tasks, so the reading is directional rather than like-for-like. BenchLM does not name a winner for agentic tasks from a directional reading; read the shared benchmark rows directly and test the models on the same task set.

Which costs less, Claude Opus 4.5 or DeepSeek V3?

For the stated presets, chat costs $0.0175 on Claude Opus 4.5 and $0.00082 on DeepSeek V3; repository review costs $0.325 and $0.0168; the cache-heavy agent loop costs $1.35 and $0.0304. Claude Opus 4.5 does not fit this workload in one request. DeepSeek V3 does not fit this workload in one request. Claude Opus 4.5 has no published cached-input rate, so cached tokens use its listed input rate.

Which has the larger context window, Claude Opus 4.5 or DeepSeek V3?

Claude Opus 4.5 has the larger documented context window: 200K, compared with 128K.

Self-host vs API cost

Estimates at 50,000 req/day · 1000 tokens/req average.

Claude Opus 4.5
API / mo$22,500
Self-host / moNot listed
Break-even—
Proprietary model — self-hosting not applicable.
DeepSeek V3
API / mo$1,028
Self-host / mo$27,962
Break-evenNot reached at 70% load
Model the full break-even

Benchmark evidence

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

Browse raw public benchmark evidence69 rows

Agentic

  • Terminal-Bench 2.0

    Claude Opus 4.559.3%
    Source
    DeepSeek V3—

    Not directly comparable

  • OSWorld-Verified

    Claude Opus 4.566.3%
    Source
    DeepSeek V3—

    Not directly comparable

  • OSWorld

    Claude Opus 4.566.3%
    Source
    DeepSeek V3—

    Not directly comparable

  • Claw-Eval

    Claude Opus 4.559.6%
    Source
    DeepSeek V3—

    Not directly comparable

  • QwenClawBench

    Claude Opus 4.552.3%
    Source
    DeepSeek V3—

    Not directly comparable

  • τ³-bench results

    Claude Opus 4.570.2%
    Source
    DeepSeek V3—

    Not directly comparable

  • VITA-Bench

    Claude Opus 4.523.3%
    Source
    DeepSeek V3—

    Not directly comparable

  • DeepPlanning

    Claude Opus 4.526.4%
    Source
    DeepSeek V3—

    Not directly comparable

  • Toolathlon

    Claude Opus 4.543.5%
    Source
    DeepSeek V3—

    Not directly comparable

  • MCP Atlas

    Claude Opus 4.542.3%
    Source
    DeepSeek V3—

    Not directly comparable

  • MCP-Tasks

    Claude Opus 4.571.8%
    Source
    DeepSeek V3—

    Not directly comparable

  • WideResearch

    Claude Opus 4.576.4%
    Source
    DeepSeek V3—

    Not directly comparable

  • CyberGym

    Claude Opus 4.550.6%
    Source
    DeepSeek V3—

    Not directly comparable

  • Gert Labs

    Claude Opus 4.564.23%
    Source
    DeepSeek V3—

    Not directly comparable

  • JobBench

    Claude Opus 4.532.3%
    Source
    DeepSeek V3—

    Not directly comparable

Coding

  • SWE-bench Verified

    Claude Opus 4.580.9%
    Source
    DeepSeek V342%
    Source

    Claude Opus 4.5 leads this result

  • LiveCodeBench v6

    Claude Opus 4.584.8%
    Source
    DeepSeek V3—

    Not directly comparable

  • SWE-bench Pro

    Claude Opus 4.557.1%
    Source
    DeepSeek V3—

    Not directly comparable

  • SWE Multilingual

    Claude Opus 4.577.5%
    Source
    DeepSeek V3—

    Not directly comparable

  • NL2Repo

    Claude Opus 4.543.2%
    Source
    DeepSeek V3—

    Not directly comparable

  • Terminal-Bench 2.0

    Claude Opus 4.559.3%
    Source
    DeepSeek V3—

    Not directly comparable

  • LiveCodeBench (Vals)

    Claude Opus 4.575.0%
    Source
    DeepSeek V3—

    Not directly comparable

  • PostTrainBench v1

    Claude Opus 4.517.1%
    Source
    DeepSeek V3—

    Not directly comparable

  • LiveCodeBench

    Claude Opus 4.5—
    DeepSeek V337.6%
    Source

    Not directly comparable

Reasoning

  • LongBench v2

    Claude Opus 4.564.4%
    Source
    DeepSeek V348.7%
    Source

    Claude Opus 4.5 leads this result

  • AI-Needle

    Claude Opus 4.574%
    Source
    DeepSeek V3—

    Not directly comparable

Multimodal

  • MMMU

    Claude Opus 4.580.7%
    Source
    DeepSeek V3—

    Not directly comparable

  • MMMU-Pro

    Claude Opus 4.570.6%
    Source
    DeepSeek V3—

    Not directly comparable

  • RealWorldQA

    Claude Opus 4.577.0%
    Source
    DeepSeek V3—

    Not directly comparable

  • OmniDocBench 1.5

    Claude Opus 4.587.7%
    Source
    DeepSeek V3—

    Not directly comparable

  • Video-MME (with subtitle)

    Claude Opus 4.577.6%
    Source
    DeepSeek V3—

    Not directly comparable

  • Video-MME (w/o subtitle)

    Claude Opus 4.581.4%
    Source
    DeepSeek V3—

    Not directly comparable

  • MathVision

    Claude Opus 4.574.3%
    Source
    DeepSeek V3—

    Not directly comparable

  • We-Math

    Claude Opus 4.570.0%
    Source
    DeepSeek V3—

    Not directly comparable

  • DynaMath

    Claude Opus 4.579.7%
    Source
    DeepSeek V3—

    Not directly comparable

  • SimpleVQA

    Claude Opus 4.565.7%
    Source
    DeepSeek V3—

    Not directly comparable

  • CharXiv

    Claude Opus 4.568.5%
    Source
    DeepSeek V3—

    Not directly comparable

  • CountBench

    Claude Opus 4.590.6%
    Source
    DeepSeek V3—

    Not directly comparable

  • AI2D_TEST

    Claude Opus 4.587.7%
    Source
    DeepSeek V3—

    Not directly comparable

  • ERQA

    Claude Opus 4.546.8%
    Source
    DeepSeek V3—

    Not directly comparable

  • VideoMMMU

    Claude Opus 4.584.4%
    Source
    DeepSeek V3—

    Not directly comparable

  • MLVU (M-Avg)

    Claude Opus 4.581.7%
    Source
    DeepSeek V3—

    Not directly comparable

  • ScreenSpot Pro

    Claude Opus 4.545.7%
    Source
    DeepSeek V3—

    Not directly comparable

  • V*

    Claude Opus 4.567.0%
    Source
    DeepSeek V3—

    Not directly comparable

Knowledge

  • GPQA

    Claude Opus 4.587%
    Source
    DeepSeek V359.1%
    Source

    Claude Opus 4.5 leads this result

  • SuperGPQA

    Claude Opus 4.570.6%
    Source
    DeepSeek V3—

    Not directly comparable

  • MMLU-Pro

    Claude Opus 4.589.5%
    Source
    DeepSeek V375.9%
    Source

    Claude Opus 4.5 leads this result

  • MMLU-Redux

    Claude Opus 4.596.6%
    Source
    DeepSeek V3—

    Not directly comparable

  • C-Eval

    Claude Opus 4.592.2%
    Source
    DeepSeek V3—

    Not directly comparable

  • HLE

    Claude Opus 4.530.8%
    Source
    DeepSeek V3—

    Not directly comparable

  • GPQA Diamond (Vals)

    Claude Opus 4.579.5%
    Source
    DeepSeek V3—

    Not directly comparable

  • MMLU-Pro (Vals)

    Claude Opus 4.585.6%
    Source
    DeepSeek V3—

    Not directly comparable

  • SimpleQA

    Claude Opus 4.5—
    DeepSeek V324.9%
    Source

    Not directly comparable

Multilingual

  • MMLU-ProX

    Claude Opus 4.585.7%
    Source
    DeepSeek V3—

    Not directly comparable

  • NOVA-63

    Claude Opus 4.556.7%
    Source
    DeepSeek V3—

    Not directly comparable

  • INCLUDE

    Claude Opus 4.586.2%
    Source
    DeepSeek V3—

    Not directly comparable

  • PolyMath

    Claude Opus 4.579.0%
    Source
    DeepSeek V3—

    Not directly comparable

  • MAXIFE

    Claude Opus 4.579.2%
    Source
    DeepSeek V3—

    Not directly comparable

Instruction following

  • IFEval

    Claude Opus 4.590.9%
    Source
    DeepSeek V386.1%
    Source

    Claude Opus 4.5 leads this result

  • IFBench

    Claude Opus 4.558%
    Source
    DeepSeek V3—

    Not directly comparable

Math

  • AIME26

    Claude Opus 4.595.1%
    Source
    DeepSeek V3—

    Not directly comparable

  • HMMT Feb 2025

    Claude Opus 4.592.9%
    Source
    DeepSeek V3—

    Not directly comparable

  • HMMT Nov 2025

    Claude Opus 4.593.3%
    Source
    DeepSeek V3—

    Not directly comparable

  • HMMT Feb 2026

    Claude Opus 4.585.3%
    Source
    DeepSeek V3—

    Not directly comparable

  • MMAnswerBench

    Claude Opus 4.584.0%
    Source
    DeepSeek V3—

    Not directly comparable

  • FrontierMath v2 (Tiers 1-3)

    Claude Opus 4.534.386%
    Source
    DeepSeek V3—

    Not directly comparable

  • FrontierMath v2 (Tier 4)

    Claude Opus 4.54.878%
    Source
    DeepSeek V3—

    Not directly comparable

  • AIME 2024

    Claude Opus 4.5—
    DeepSeek V339.2%
    Source

    Not directly comparable

  • MATH-500

    Claude Opus 4.5—
    DeepSeek V390.2%
    Source

    Not directly comparable

69 public results · 5 shared

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Last updated November 13, 2026