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BenchLM
Anthropic logo
Model A
Claude Opus 4.8

Anthropic

76.45/100

Supported · Public rank #8

90% interval 73.8–79.1

Claude Opus 4.8 vs DeepSeek V3.2 (Thinking)

Updated August 26, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

DeepSeek logo
Model B
DeepSeek V3.2 (Thinking)

DeepSeek

58.8/100

Estimated · Public rank #79

90% interval 47.3–70.3

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 based on different benchmark sets are marked directional and do not name a winner.

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 4.8

    Claude Opus 4.8 has the larger documented context window.

    Confidence: documented

  • Chat turn cost

    1K fresh input + 500 output tokens

    DeepSeek V3.2 (Thinking)

    DeepSeek V3.2 (Thinking) 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 V3.2 (Thinking)

    DeepSeek V3.2 (Thinking) 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

    No shared weighted benchmark basis supports a winner.

    Confidence: limited

  • Agentic work

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

    Not enough matched evidence

    No shared weighted benchmark basis supports a winner.

    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. DeepSeek V3.2 (Thinking) does not fit this workload in one request. Claude Opus 4.8 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 Opus 4.8 only
33
DeepSeek V3.2 (Thinking) only
1
Like-for-like categories
0 / 8

Category results, on a stated basis

Each row states whether both averages use the same weighted benchmark set. Directional and not-comparable rows remain visible, but they never receive a winner in this template.

Agentic

Not comparable
Claude Opus 4.8
80.3
DeepSeek V3.2 (Thinking)
Not measured
Weighted basis
3 vs 0 rows
Reading
Not comparable

Coding

Not comparable
Claude Opus 4.8
81.1
DeepSeek V3.2 (Thinking)
Not measured
Weighted basis
2 vs 0 rows
Reading
Not comparable

Reasoning

Not comparable
Claude Opus 4.8
72.1
DeepSeek V3.2 (Thinking)
Not measured
Weighted basis
1 vs 0 rows
Reading
Not comparable

Knowledge

Not comparable
Claude Opus 4.8
62.7
DeepSeek V3.2 (Thinking)
Not measured
Weighted basis
2 vs 0 rows
Reading
Not comparable

Math

Not comparable
Claude Opus 4.8
53.9
DeepSeek V3.2 (Thinking)
Not measured
Weighted basis
3 vs 0 rows
Reading
Not comparable

Multilingual

Not comparable
Claude Opus 4.8
Not measured
DeepSeek V3.2 (Thinking)
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multimodal

Not comparable
Claude Opus 4.8
77.0
DeepSeek V3.2 (Thinking)
Not measured
Weighted basis
2 vs 0 rows
Reading
Not comparable

Instruction following

Not comparable
Claude Opus 4.8
Not measured
DeepSeek V3.2 (Thinking)
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

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 Opus 4.8
$0.0175
Fits in one request
DeepSeek V3.2 (Thinking)
$0.00165
Fits in one request

DeepSeek V3.2 (Thinking) has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

Claude Opus 4.8
$0.325
Fits in one request
DeepSeek V3.2 (Thinking)
$0.03407
Fits in one request

DeepSeek V3.2 (Thinking) 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 4.8
$1.35
Fits in one request
Cached input priced at the published list-input rate
DeepSeek V3.2 (Thinking)
$0.0609
Does not fit in one request

DeepSeek V3.2 (Thinking) does not fit this workload in one request. Claude Opus 4.8 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 Opus 4.8

1M

Anthropic model overview

DeepSeek V3.2 (Thinking)

128K

Cached-input rate

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

Claude Opus 4.8

Not published

DeepSeek V3.2 (Thinking)

$0.14 per 1M cached input tokens

Provider availability

Claude Opus 4.8

Generally Available · Claude API

Anthropic model overview

DeepSeek V3.2 (Thinking)

Not sourced

Reasoning profile

Claude Opus 4.8

Reasoning

DeepSeek V3.2 (Thinking)

Reasoning

Weight access

Claude Opus 4.8

Proprietary

DeepSeek V3.2 (Thinking)

Open Weight

License

Claude Opus 4.8

Proprietary

DeepSeek V3.2 (Thinking)

Open Weight

Release date

Claude Opus 4.8

2026-05-28

DeepSeek V3.2 (Thinking)

2025-12-01

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: $0.325 vs $0.03407. Cache-heavy agent loop: $1.35 vs $0.0609.
Context tradeoff
Claude Opus 4.8 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 evidence34 rows

Agentic

  • Terminal-Bench 3.0

    Claude Opus 4.821.1%
    Source
    DeepSeek V3.2 (Thinking)—

    Not directly comparable

  • Terminal-Bench 2.0

    Claude Opus 4.874.6%
    Source
    DeepSeek V3.2 (Thinking)—

    Not directly comparable

  • BrowseComp

    Claude Opus 4.884.3%
    Source
    DeepSeek V3.2 (Thinking)—

    Not directly comparable

  • DeepSearchQA

    Claude Opus 4.893.1%
    Source
    DeepSeek V3.2 (Thinking)—

    Not directly comparable

  • OSWorld-Verified

    Claude Opus 4.883.4%
    Source
    DeepSeek V3.2 (Thinking)—

    Not directly comparable

  • Finance Agent v2

    Claude Opus 4.853.9%
    Source
    DeepSeek V3.2 (Thinking)—

    Not directly comparable

  • MCP Atlas

    Claude Opus 4.882.2%
    Source
    DeepSeek V3.2 (Thinking)—

    Not directly comparable

  • Toolathlon

    Claude Opus 4.859.9%
    Source
    DeepSeek V3.2 (Thinking)—

    Not directly comparable

  • Gert Labs

    Claude Opus 4.872.97%
    Source
    DeepSeek V3.2 (Thinking)—

    Not directly comparable

  • ResearchClawBench

    Claude Opus 4.821.1%
    Source
    DeepSeek V3.2 (Thinking)—

    Not directly comparable

  • OSWorld 2.0

    Claude Opus 4.820.6%
    Source
    DeepSeek V3.2 (Thinking)—

    Not directly comparable

Coding

  • SWE-bench Verified

    Claude Opus 4.888.6%
    Source
    DeepSeek V3.2 (Thinking)—

    Not directly comparable

  • SWE-bench Pro

    Claude Opus 4.869.2%
    Source
    DeepSeek V3.2 (Thinking)—

    Not directly comparable

  • SWE Multilingual

    Claude Opus 4.884.4%
    Source
    DeepSeek V3.2 (Thinking)—

    Not directly comparable

  • SWE Multimodal

    Claude Opus 4.838.4%
    Source
    DeepSeek V3.2 (Thinking)—

    Not directly comparable

  • Terminal-Bench 2.0

    Claude Opus 4.874.6%
    Source
    DeepSeek V3.2 (Thinking)—

    Not directly comparable

  • cursorBench31

    Claude Opus 4.858.4%
    Source
    DeepSeek V3.2 (Thinking)—

    Not directly comparable

  • cursorBench32

    Claude Opus 4.862.3%
    Source
    DeepSeek V3.2 (Thinking)—

    Not directly comparable

  • FrontierCode 1.1 Main

    Claude Opus 4.846.5%
    Source
    DeepSeek V3.2 (Thinking)—

    Not directly comparable

  • Vibe Code Bench

    Claude Opus 4.8—
    DeepSeek V3.2 (Thinking)5.11%
    Source

    Not directly comparable

Reasoning

  • ARC-AGI-2

    Claude Opus 4.872.1%
    Source
    DeepSeek V3.2 (Thinking)—

    Not directly comparable

  • ARC-AGI-3

    Claude Opus 4.81.5%
    Source
    DeepSeek V3.2 (Thinking)—

    Not directly comparable

Knowledge

  • GPQA

    Claude Opus 4.893.6%
    Source
    DeepSeek V3.2 (Thinking)—

    Not directly comparable

  • GPQA-D

    Claude Opus 4.893.6%
    Source
    DeepSeek V3.2 (Thinking)—

    Not directly comparable

  • HLE

    Claude Opus 4.857.9%
    Source
    DeepSeek V3.2 (Thinking)—

    Not directly comparable

  • HLE w/o tools

    Claude Opus 4.849.8%
    Source
    DeepSeek V3.2 (Thinking)—

    Not directly comparable

Math

  • USAMO 2026

    Claude Opus 4.896.7%
    Source
    DeepSeek V3.2 (Thinking)—

    Not directly comparable

  • FrontierMath v2 (Tiers 1-3)

    Claude Opus 4.847.241%
    Source
    DeepSeek V3.2 (Thinking)—

    Not directly comparable

  • FrontierMath v2 (Tier 4)

    Claude Opus 4.831.250%
    Source
    DeepSeek V3.2 (Thinking)—

    Not directly comparable

Multilingual

  • INCLUDE

    Claude Opus 4.887.6%
    Source
    DeepSeek V3.2 (Thinking)—

    Not directly comparable

Multimodal

  • OfficeQA Pro

    Claude Opus 4.866.2%
    Source
    DeepSeek V3.2 (Thinking)—

    Not directly comparable

  • ScreenSpot Pro

    Claude Opus 4.887.9%
    Source
    DeepSeek V3.2 (Thinking)—

    Not directly comparable

  • CharXiv

    Claude Opus 4.889.9%
    Source
    DeepSeek V3.2 (Thinking)—

    Not directly comparable

  • CharXiv w/o tools

    Claude Opus 4.880.5%
    Source
    DeepSeek V3.2 (Thinking)—

    Not directly comparable

Frequently asked questions

Which is better, Claude Opus 4.8 or DeepSeek V3.2 (Thinking)?

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 Opus 4.8 or DeepSeek V3.2 (Thinking)?

The published evidence does not provide a shared weighted coding basis for both models, so BenchLM does not name a coding winner.

Which is better for agentic tasks, Claude Opus 4.8 or DeepSeek V3.2 (Thinking)?

The published evidence does not provide a shared weighted agentic tasks basis for both models, so BenchLM does not name a agentic tasks winner.

Which costs less, Claude Opus 4.8 or DeepSeek V3.2 (Thinking)?

For the stated presets, chat costs $0.0175 on Claude Opus 4.8 and $0.00164 on DeepSeek V3.2 (Thinking); repository review costs $0.325 and $0.03407; the cache-heavy agent loop costs $1.35 and $0.0609. DeepSeek V3.2 (Thinking) does not fit this workload in one request. Claude Opus 4.8 has no published cached-input rate, so cached tokens use its listed input rate.

Which has the larger context window, Claude Opus 4.8 or DeepSeek V3.2 (Thinking)?

Claude Opus 4.8 has the larger documented context window: 1M, compared with 128K.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated August 26, 2026

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