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Model A
Claude 3 Opus

Anthropic

35.48/100

Supported · Public rank #208

90% interval 19.151.9

Claude 3 Opus vs DeepSeek V4.1 Flash

Updated September 10, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

DeepSeek logo
Model B
DeepSeek V4.1 Flash

DeepSeek

Evidence status unavailable

90% interval unavailable

Decision reading

The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. Use the documented cost, context, and runtime rows instead.

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

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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.

  • Long documents

    Prompts that approach the documented context limit

    DeepSeek V4.1 Flash

    DeepSeek V4.1 Flash has the larger documented context window.

    Confidence: documented

  • Chat turn cost

    1K fresh input + 500 output tokens

    DeepSeek V4.1 Flash

    DeepSeek V4.1 Flash 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 V4.1 Flash

    DeepSeek V4.1 Flash 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 V4.1 Flash 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

    Claude 3 Opus and DeepSeek V4.1 Flash are not ranked on the public lane for agentic, so no winner is named for agentic.

    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 3 Opus does not fit this workload in one request. Claude 3 Opus has no published cached-input rate, so cached tokens use its listed input rate.

    Confidence: rate-fallback

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
0
Claude 3 Opus only
0
DeepSeek V4.1 Flash only
21
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 3 Opus
Not ranked
DeepSeek V4.1 Flash
Not ranked
Basis
BenchAlign lane · 0 vs 8 public rows
Reading
Not comparable

Coding

Not comparable
Claude 3 Opus
34.7
Estimated · #129/151
DeepSeek V4.1 Flash
Not ranked
Basis
BenchAlign lane · 0 vs 6 public rows
Reading
Not comparable

Reasoning

Not comparable
Claude 3 Opus
Not ranked
DeepSeek V4.1 Flash
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Knowledge

Not comparable
Claude 3 Opus
34.2
Estimated · #165/182
DeepSeek V4.1 Flash
Not ranked
Basis
BenchAlign lane · 0 vs 3 public rows
Reading
Not comparable

Math

Not comparable
Claude 3 Opus
Not ranked
DeepSeek V4.1 Flash
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multilingual

Not comparable
Claude 3 Opus
Not ranked
DeepSeek V4.1 Flash
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multimodal

Not comparable
Claude 3 Opus
Not ranked
DeepSeek V4.1 Flash
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Instruction following

Not comparable
Claude 3 Opus
Not ranked
DeepSeek V4.1 Flash
Not ranked
Basis
Provisional lane · 0 vs 0 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.

A shared-evidence shape is not available.

BenchLM does not draw a radar or infer missing axes when the matched evidence is too sparse.

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 3 Opus
$0.0525
Fits in one request
DeepSeek V4.1 Flash
$0.0009
Fits in one request

DeepSeek V4.1 Flash has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

Claude 3 Opus
$0.975
Fits in one request
DeepSeek V4.1 Flash
$0.0186
Fits in one request

DeepSeek V4.1 Flash 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 3 Opus
$4.05
Does not fit in one request
Cached input priced at the published list-input rate
DeepSeek V4.1 Flash
$0.0192
Fits in one request

Claude 3 Opus does not fit this workload in one request. Claude 3 Opus has no published cached-input rate, so cached tokens use its listed input rate.

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 3 Opus

200K

DeepSeek V4.1 Flash

Cached-input rate

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

Claude 3 Opus

Not published

DeepSeek V4.1 Flash

$0.006 per 1M cached input tokens

DeepSeek: Models & Pricing

Provider availability

Claude 3 Opus

Not sourced

DeepSeek V4.1 Flash

Generally Available · DeepSeek API, open weights

DeepSeek-V4.1-Flash release

Reasoning profile

Claude 3 Opus

Non-Reasoning

DeepSeek V4.1 Flash

Reasoning

Weight access

Claude 3 Opus

Proprietary

DeepSeek V4.1 Flash

Open Weight

License

Claude 3 Opus

Proprietary

DeepSeek V4.1 Flash

Open Weight

Release date

Claude 3 Opus

2024-03-01

DeepSeek V4.1 Flash

2026-09-10

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
The public evidence has no benchmark result shared by both models, so it does not support a quality verdict.
Workload cost
Repository review: $0.975 vs $0.0186. Cache-heavy agent loop: $4.05 vs $0.0192.
Context tradeoff
DeepSeek V4.1 Flash has the larger documented window (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 evidence21 rows

Agentic

  • Terminal-Bench 2.1

    Claude 3 Opus
    DeepSeek V4.1 Flash90.6%
    Source

    Not directly comparable

  • terminalBench3

    Claude 3 Opus
    DeepSeek V4.1 Flash30%
    Source

    Not directly comparable

  • Terminal-Bench 4.0

    Claude 3 Opus
    DeepSeek V4.1 Flash31.20%
    Source

    Not directly comparable

  • CyberGym

    Claude 3 Opus
    DeepSeek V4.1 Flash88.1%
    Source

    Not directly comparable

  • ExploitGym

    Claude 3 Opus
    DeepSeek V4.1 Flash15.3%
    Source

    Not directly comparable

  • HLE w/ tools

    Claude 3 Opus
    DeepSeek V4.1 Flash63.9%
    Source

    Not directly comparable

  • AutomationBench

    Claude 3 Opus
    DeepSeek V4.1 Flash54.8%
    Source

    Not directly comparable

  • Agents' Last Exam

    Claude 3 Opus
    DeepSeek V4.1 Flash31.8%
    Source

    Not directly comparable

Coding

  • Codeforces

    Claude 3 Opus
    DeepSeek V4.1 Flash3471.0
    Source

    Not directly comparable

  • Terminal-Bench 2.1

    Claude 3 Opus
    DeepSeek V4.1 Flash90.6%
    Source

    Not directly comparable

  • terminalBench3

    Claude 3 Opus
    DeepSeek V4.1 Flash30%
    Source

    Not directly comparable

  • DeepSWE

    Claude 3 Opus
    DeepSeek V4.1 Flash74.2%
    Source

    Not directly comparable

  • ProgramBench

    Claude 3 Opus
    DeepSeek V4.1 Flash20.3%
    Source

    Not directly comparable

  • NL2Repo

    Claude 3 Opus
    DeepSeek V4.1 Flash65.4%
    Source

    Not directly comparable

Knowledge

  • GPQA

    Claude 3 Opus
    DeepSeek V4.1 Flash90.9%
    Source

    Not directly comparable

  • GPQA-D

    Claude 3 Opus
    DeepSeek V4.1 Flash90.9%
    Source

    Not directly comparable

  • HLE

    Claude 3 Opus
    DeepSeek V4.1 Flash36.8%
    Source

    Not directly comparable

Math

  • Apex

    Claude 3 Opus
    DeepSeek V4.1 Flash65.6%
    Source

    Not directly comparable

Multimodal

  • Chartography (tools)

    Claude 3 Opus
    DeepSeek V4.1 Flash78.9%
    Source

    Not directly comparable

  • BabyVision w/ Python

    Claude 3 Opus
    DeepSeek V4.1 Flash89.6%
    Source

    Not directly comparable

  • ZeroBench w/ Python

    Claude 3 Opus
    DeepSeek V4.1 Flash49.0%
    Source

    Not directly comparable

Frequently asked questions

Which is better, Claude 3 Opus or DeepSeek V4.1 Flash?

The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. The page therefore keeps the decision tied to the specific documented workload.

Which is better for coding, Claude 3 Opus or DeepSeek V4.1 Flash?

DeepSeek V4.1 Flash is not ranked on the public lane for coding, so no winner is named for coding.

Which is better for agentic tasks, Claude 3 Opus or DeepSeek V4.1 Flash?

Claude 3 Opus and DeepSeek V4.1 Flash are not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.

Which costs less, Claude 3 Opus or DeepSeek V4.1 Flash?

For the stated presets, chat costs $0.0525 on Claude 3 Opus and $0.0009 on DeepSeek V4.1 Flash; repository review costs $0.975 and $0.0186; the cache-heavy agent loop costs $4.05 and $0.0192. Claude 3 Opus does not fit this workload in one request. Claude 3 Opus has no published cached-input rate, so cached tokens use its listed input rate.

Which has the larger context window, Claude 3 Opus or DeepSeek V4.1 Flash?

DeepSeek V4.1 Flash has the larger documented context window: 1M, compared with 200K.

Related comparisons

Last updated September 10, 2026

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