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Model comparison

Claude 3.5 Sonnet vs DeepSeek V3

Updated July 30, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Claude 3.5 Sonnet

Anthropic

46.9/100

Estimated · Public rank #139

90% interval 35.4–58.4

DeepSeek V3

DeepSeek

44.1/100

Supported · Public rank #154

90% interval 25.5–62.8

Claude 3.5 Sonnet has the higher public score estimate, 46.9 versus 44.15, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.

3 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 3.5 Sonnet

    Claude 3.5 Sonnet 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

    The category averages use different weighted benchmark sets, so they are directional rather than like-for-like.

    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. Claude 3.5 Sonnet does not fit this workload in one request. DeepSeek V3 does not fit this workload in one request. Claude 3.5 Sonnet 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
3
Claude 3.5 Sonnet only
1
DeepSeek V3 only
3
Like-for-like categories
0 / 8

3 categories use different evidence sets. Those rows remain visible for coverage context but do not name a winner.

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.

Coding

Directional only
Claude 3.5 Sonnet
49.0
DeepSeek V3
38.9
Weighted basis
1 vs 2 rows
Reading
Directional only

Knowledge

Directional only
Claude 3.5 Sonnet
59.4
DeepSeek V3
72.7
Weighted basis
1 vs 2 rows
Reading
Directional only

Math

Directional only
Claude 3.5 Sonnet
1.6
DeepSeek V3
1.7
Weighted basis
2 vs 1 rows
Reading
Directional only

Agentic

Not comparable
Claude 3.5 Sonnet
Not measured
DeepSeek V3
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Reasoning

Not comparable
Claude 3.5 Sonnet
Not measured
DeepSeek V3
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multilingual

Not comparable
Claude 3.5 Sonnet
Not measured
DeepSeek V3
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multimodal

Not comparable
Claude 3.5 Sonnet
Not measured
DeepSeek V3
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Instruction following

Not comparable
Claude 3.5 Sonnet
Not measured
DeepSeek V3
86.1
Weighted basis
0 vs 1 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.

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 3.5 Sonnet
$0.0105
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 3.5 Sonnet
$0.195
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 3.5 Sonnet
$0.81
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 3.5 Sonnet does not fit this workload in one request. DeepSeek V3 does not fit this workload in one request. Claude 3.5 Sonnet 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 3.5 Sonnet

200K

DeepSeek V3

128K

API model ID

Claude 3.5 Sonnet

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 3.5 Sonnet

Not published

DeepSeek V3

$0.07 per 1M cached input tokens

Documented inputs

Claude 3.5 Sonnet

Not sourced

DeepSeek V3

Not sourced

Documented outputs

Claude 3.5 Sonnet

Not sourced

DeepSeek V3

Not sourced

Provider availability

Claude 3.5 Sonnet

Not sourced

DeepSeek V3

Not sourced

Reasoning profile

Claude 3.5 Sonnet

Non-Reasoning

DeepSeek V3

Non-Reasoning

Weight access

Claude 3.5 Sonnet

Proprietary

DeepSeek V3

Open Weight

License

Claude 3.5 Sonnet

Proprietary

DeepSeek V3

Open Weight

Release date

Claude 3.5 Sonnet

2024-06-01

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 3.5 Sonnet has the higher public score estimate, 46.9 versus 44.15, but the 90% score intervals overlap.
Workload cost
Repository review: $0.195 vs $0.0168. Cache-heavy agent loop: $0.81 vs $0.0304.
Context tradeoff
Claude 3.5 Sonnet has the larger documented window (200K).

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

Self-host vs API cost

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

Claude 3.5 Sonnet
API / mo$13,500
Self-host / moNot listed
Break-even
Proprietary model — self-hosting not applicable.
DeepSeek V3
API / mo$1,028
Self-host / mo$18,221
Break-even1.2B/day
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 evidence7 rows

Coding

  • SWE-bench Verified

    Claude 3.5 Sonnet49%
    Source
    DeepSeek V342%
    Source

    Claude 3.5 Sonnet leads this result

  • LiveCodeBench

    Claude 3.5 Sonnet
    DeepSeek V337.6%
    Source

    Not directly comparable

Knowledge

  • GPQA

    Claude 3.5 Sonnet59.4%
    Source
    DeepSeek V359.1%
    Source

    Claude 3.5 Sonnet leads this result

  • MMLU-Pro

    Claude 3.5 Sonnet
    DeepSeek V375.9%
    Source

    Not directly comparable

Math

  • FrontierMath v2 (Tiers 1-3)

    Shared source
    Claude 3.5 Sonnet2.069%
    DeepSeek V31.724%

    Claude 3.5 Sonnet leads this result

  • FrontierMath v2 (Tier 4)

    Claude 3.5 Sonnet0.000%
    Source
    DeepSeek V3

    Not directly comparable

Instruction following

  • IFEval

    Claude 3.5 Sonnet
    DeepSeek V386.1%
    Source

    Not directly comparable

Frequently asked questions

Which is better, Claude 3.5 Sonnet or DeepSeek V3?

Claude 3.5 Sonnet has the higher public score estimate, 46.9 versus 44.15, 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 3.5 Sonnet or DeepSeek V3?

The current coding averages use different weighted benchmark sets, so BenchLM does not name a winner from them. Read the shared benchmark rows directly and test the models on the same task set.

Which is better for agentic tasks, Claude 3.5 Sonnet or DeepSeek V3?

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 3.5 Sonnet or DeepSeek V3?

For the stated presets, chat costs $0.0105 on Claude 3.5 Sonnet and $0.00082 on DeepSeek V3; repository review costs $0.195 and $0.0168; the cache-heavy agent loop costs $0.81 and $0.0304. Claude 3.5 Sonnet does not fit this workload in one request. DeepSeek V3 does not fit this workload in one request. Claude 3.5 Sonnet has no published cached-input rate, so cached tokens use its listed input rate.

Which has the larger context window, Claude 3.5 Sonnet or DeepSeek V3?

Claude 3.5 Sonnet has the larger documented context window: 200K, compared with 128K.

Related comparisons

Last updated July 30, 2026

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