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Model A
Claude 3.5 Sonnet

Anthropic

48.68/100

Estimated · Public rank #151

90% interval 37.260.2

Claude 3.5 Sonnet vs o3

Updated September 3, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

OpenAI logo
Model B
o3

OpenAI

46.83/100

Supported · Public rank #165

90% interval 43.949.7

Decision reading

Claude 3.5 Sonnet has the higher public score estimate, 48.68 versus 46.83, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.

2 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.

  • Chat turn cost

    1K fresh input + 500 output tokens

    o3

    o3 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

    o3

    o3 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

  • Long documents

    Prompts that approach the documented context limit

    No clear pick

    The documented context windows are equal.

    Confidence: documented

  • 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. o3 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. o3 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
2
Claude 3.5 Sonnet only
2
o3 only
0
Like-for-like categories
1 / 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.

Math

Like-for-like
Claude 3.5 Sonnet
1.6
o3
14.5
Weighted basis
2 vs 2 rows
Reading
o3 leads

Agentic

Not comparable
Claude 3.5 Sonnet
Not measured
o3
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Coding

Not comparable
Claude 3.5 Sonnet
49.0
o3
Not measured
Weighted basis
1 vs 0 rows
Reading
Not comparable

Reasoning

Not comparable
Claude 3.5 Sonnet
Not measured
o3
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Knowledge

Not comparable
Claude 3.5 Sonnet
59.4
o3
Not measured
Weighted basis
1 vs 0 rows
Reading
Not comparable

Multilingual

Not comparable
Claude 3.5 Sonnet
Not measured
o3
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multimodal

Not comparable
Claude 3.5 Sonnet
Not measured
o3
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Instruction following

Not comparable
Claude 3.5 Sonnet
Not measured
o3
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.

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.

  • FrontierMath v2 (Tiers 1-3)

    Math

    Claude 3.5 Sonnet: 2.069%o3: 18.685%Normalized gap 16.6Shared source
  • FrontierMath v2 (Tier 4)

    Math

    Claude 3.5 Sonnet: 0.000%o3: 2.083%Normalized gap 2.1Shared source

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
o3
$0.006
Fits in one request

o3 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
o3
$0.124
Fits in one request

o3 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
o3
$0.52
Does not fit in one request
Cached input priced at the published list-input rate

Claude 3.5 Sonnet does not fit this workload in one request. o3 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. o3 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

o3

200K

API model ID

Claude 3.5 Sonnet

Not sourced

o3

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

o3

Not published

Documented inputs

Claude 3.5 Sonnet

Not sourced

o3

Not sourced

Documented outputs

Claude 3.5 Sonnet

Not sourced

o3

Not sourced

Provider availability

Claude 3.5 Sonnet

Not sourced

o3

Not sourced

Reasoning profile

Claude 3.5 Sonnet

Non-Reasoning

o3

Reasoning

Weight access

Claude 3.5 Sonnet

Proprietary

o3

Proprietary

License

Claude 3.5 Sonnet

Proprietary

o3

Proprietary

Release date

Claude 3.5 Sonnet

2024-06-01

o3

2025-04-16

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, 48.68 versus 46.83, but the 90% score intervals overlap.
Workload cost
Repository review: $0.195 vs $0.124. Cache-heavy agent loop: $0.81 vs $0.52.
Context tradeoff
Both models list 200K.

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 evidence4 rows

Coding

  • SWE-bench Verified

    Claude 3.5 Sonnet49%
    Source
    o3

    Not directly comparable

Knowledge

  • GPQA

    Claude 3.5 Sonnet59.4%
    Source
    o3

    Not directly comparable

Math

  • FrontierMath v2 (Tiers 1-3)

    Shared source
    Claude 3.5 Sonnet2.069%
    o318.685%

    o3 leads this result

  • FrontierMath v2 (Tier 4)

    Shared source
    Claude 3.5 Sonnet0.000%
    o32.083%

    o3 leads this result

Frequently asked questions

Which is better, Claude 3.5 Sonnet or o3?

Claude 3.5 Sonnet has the higher public score estimate, 48.68 versus 46.83, 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 o3?

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 3.5 Sonnet or o3?

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 o3?

For the stated presets, chat costs $0.0105 on Claude 3.5 Sonnet and $0.006 on o3; repository review costs $0.195 and $0.124; the cache-heavy agent loop costs $0.81 and $0.52. Claude 3.5 Sonnet does not fit this workload in one request. o3 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. o3 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 o3?

Both models list the same context window, 200K.

Related comparisons

Last updated September 3, 2026

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