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BenchLM
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Model A
Claude Sonnet 4.5

Anthropic

53.74/100

Supported · Public rank #115

90% interval 49.9–57.6

Claude Sonnet 4.5 vs Claude Sonnet 5

Updated September 4, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Anthropic logo
Model B
Claude Sonnet 5

Anthropic

70.76/100

Supported · Public rank #17

90% interval 67.8–73.7

Decision reading

Claude Sonnet 5 has the higher public score, 70.76 versus 53.74, and the 90% score intervals do not overlap.

3 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

    Claude Sonnet 5

    Claude Sonnet 5 has the larger documented context window.

    Confidence: documented

  • Chat turn cost

    1K fresh input + 500 output tokens

    Claude Sonnet 5

    Claude Sonnet 5 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

    Claude Sonnet 5

    Claude Sonnet 5 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

    Claude Sonnet 4.5 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

    Claude Sonnet 4.5 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 Sonnet 4.5 does not fit this workload in one request. Claude Sonnet 4.5 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 Sonnet 4.5 only
8
Claude Sonnet 5 only
20
Like-for-like categories
0 / 8

3 categories rest on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.

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

Directional only
Claude Sonnet 4.5
44.6
Estimated · #100/151
Claude Sonnet 5
66.0
Supported · #12/151
Basis
BenchAlign lane · 5 vs 6 public rows
Reading
Directional only

Coding

Directional only
Claude Sonnet 4.5
51.0
Estimated · #67/183
Claude Sonnet 5
64.2
Supported · #13/183
Basis
BenchAlign lane · 1 vs 9 public rows
Reading
Directional only

Knowledge

Directional only
Claude Sonnet 4.5
51.5
Estimated · #81/181
Claude Sonnet 5
67.1
Supported · #20/181
Basis
BenchAlign lane · 1 vs 6 public rows
Reading
Directional only

Reasoning

Not comparable
Claude Sonnet 4.5
19.1
Unranked · 1 rankable row
Claude Sonnet 5
76.4
Unranked · 2 rankable rows
Basis
Provisional lane · 1 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
Claude Sonnet 4.5
34.8
Unranked · 2 rankable rows
Claude Sonnet 5
Not ranked
Basis
Provisional lane · 2 vs 0 weighted rows
Reading
Not comparable

Multilingual

Not comparable
Claude Sonnet 4.5
Not ranked
Claude Sonnet 5
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multimodal

Not comparable
Claude Sonnet 4.5
Not ranked
Claude Sonnet 5
77.5
#13/48
Basis
Provisional lane · 0 vs 1 weighted rows
Reading
Not comparable

Instruction following

Not comparable
Claude Sonnet 4.5
Not ranked
Claude Sonnet 5
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.

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 Sonnet 4.5
$0.0105
Fits in one request
Claude Sonnet 5
$0.007
Fits in one request

Claude Sonnet 5 has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

Claude Sonnet 4.5
$0.195
Fits in one request
Claude Sonnet 5
$0.13
Fits in one request

Claude Sonnet 5 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 Sonnet 4.5
$0.81
Does not fit in one request
Cached input priced at the published list-input rate
Claude Sonnet 5
$0.18
Fits in one request

Claude Sonnet 4.5 does not fit this workload in one request. Claude Sonnet 4.5 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 Sonnet 4.5

200K

Claude Sonnet 5

1M

Anthropic model overview

Cached-input rate

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

Claude Sonnet 4.5

Not published

Claude Sonnet 5

$0.2 per 1M cached input tokens

Claude API pricing

Provider availability

Claude Sonnet 4.5

Not sourced

Claude Sonnet 5

Generally Available · Claude API

Anthropic model overview

Reasoning profile

Claude Sonnet 4.5

Non-Reasoning

Claude Sonnet 5

Reasoning

Weight access

Claude Sonnet 4.5

Proprietary

Claude Sonnet 5

Proprietary

License

Claude Sonnet 4.5

Proprietary

Claude Sonnet 5

Proprietary

Release date

Claude Sonnet 4.5

2025-09-01

Claude Sonnet 5

2026-06-30

If you already use one of these models
Deployment change
Both entries list Anthropic as the provider. Confirm endpoint, model ID, limits, and feature support before switching.
Quality signal
Claude Sonnet 5 has the higher public score, 70.76 versus 53.74, and the 90% score intervals do not overlap.
Workload cost
Repository review: $0.195 vs $0.13. Cache-heavy agent loop: $0.81 vs $0.18.
Context tradeoff
Claude Sonnet 5 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 evidence31 rows

Agentic

  • Terminal-Bench 2.0

    Claude Sonnet 4.550%
    Source
    Claude Sonnet 580.4%
    Source

    Claude Sonnet 5 leads this result

  • OSWorld-Verified

    Claude Sonnet 4.561.4%
    Source
    Claude Sonnet 581.2%
    Source

    Claude Sonnet 5 leads this result

  • VITA-Bench

    Claude Sonnet 4.517.0%
    Source
    Claude Sonnet 5—

    Not directly comparable

  • Gert Labs

    Claude Sonnet 4.548.51%
    Source
    Claude Sonnet 5—

    Not directly comparable

  • JobBench

    Claude Sonnet 4.527.7%
    Source
    Claude Sonnet 5—

    Not directly comparable

  • Terminal-Bench 3.0

    Claude Sonnet 4.5—
    Claude Sonnet 514.6%
    Source

    Not directly comparable

  • BrowseComp

    Claude Sonnet 4.5—
    Claude Sonnet 584.7%
    Source

    Not directly comparable

  • HLE w/ tools

    Claude Sonnet 4.5—
    Claude Sonnet 557.4%
    Source

    Not directly comparable

  • Terminal-Bench 2.1 (Vals)

    Claude Sonnet 4.5—
    Claude Sonnet 574.5%
    Source

    Not directly comparable

Coding

  • SWE-bench Verified

    Claude Sonnet 4.577.2%
    Source
    Claude Sonnet 585.2%
    Source

    Claude Sonnet 5 leads this result

  • SWE-bench Pro

    Claude Sonnet 4.5—
    Claude Sonnet 563.2%
    Source

    Not directly comparable

  • SWE Multilingual

    Claude Sonnet 4.5—
    Claude Sonnet 578.3%
    Source

    Not directly comparable

  • SWE Multimodal

    Claude Sonnet 4.5—
    Claude Sonnet 528.1%
    Source

    Not directly comparable

  • Terminal-Bench 2.0

    Claude Sonnet 4.5—
    Claude Sonnet 580.4%
    Source

    Not directly comparable

  • FrontierCode 1.1 Main

    Claude Sonnet 4.5—
    Claude Sonnet 542.7%
    Source

    Not directly comparable

  • cursorBench32

    Claude Sonnet 4.5—
    Claude Sonnet 561.5%
    Source

    Not directly comparable

  • LiveCodeBench (Vals)

    Claude Sonnet 4.5—
    Claude Sonnet 582.4%
    Source

    Not directly comparable

  • SWE-bench (Vals)

    Claude Sonnet 4.5—
    Claude Sonnet 579.6%
    Source

    Not directly comparable

Reasoning

  • ARC-AGI-2

    Claude Sonnet 4.513.6%
    Source
    Claude Sonnet 5—

    Not directly comparable

Knowledge

  • GPQA

    Claude Sonnet 4.583.4%
    Source
    Claude Sonnet 5—

    Not directly comparable

  • HLE

    Claude Sonnet 4.5—
    Claude Sonnet 557.4%
    Source

    Not directly comparable

  • HLE w/o tools

    Claude Sonnet 4.5—
    Claude Sonnet 543.2%
    Source

    Not directly comparable

  • HLE-Verified

    Claude Sonnet 4.5—
    Claude Sonnet 531.0%
    Source

    Not directly comparable

  • LABBench2

    Claude Sonnet 4.5—
    Claude Sonnet 580.1%
    Source

    Not directly comparable

  • GPQA Diamond (Vals)

    Claude Sonnet 4.5—
    Claude Sonnet 588.9%
    Source

    Not directly comparable

  • MMLU-Pro (Vals)

    Claude Sonnet 4.5—
    Claude Sonnet 587.5%
    Source

    Not directly comparable

Math

  • AIME 2025

    Claude Sonnet 4.587%
    Source
    Claude Sonnet 5—

    Not directly comparable

  • FrontierMath v2 (Tiers 1-3)

    Claude Sonnet 4.513.495%
    Source
    Claude Sonnet 5—

    Not directly comparable

  • FrontierMath v2 (Tier 4)

    Claude Sonnet 4.54.167%
    Source
    Claude Sonnet 5—

    Not directly comparable

Multimodal

  • CharXiv

    Claude Sonnet 4.5—
    Claude Sonnet 588.3%
    Source

    Not directly comparable

  • CharXiv w/o tools

    Claude Sonnet 4.5—
    Claude Sonnet 577%
    Source

    Not directly comparable

Frequently asked questions

Which is better, Claude Sonnet 4.5 or Claude Sonnet 5?

Claude Sonnet 5 has the higher public score, 70.76 versus 53.74, and the 90% score intervals do not overlap. That is the clearest overall quality signal in the current public data.

Which is better for coding, Claude Sonnet 4.5 or Claude Sonnet 5?

Claude Sonnet 5 scores higher for coding on the public lane, 64.2 to 51. Claude Sonnet 4.5 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 Sonnet 4.5 or Claude Sonnet 5?

Claude Sonnet 5 scores higher for agentic tasks on the public lane, 66 to 44.6. Claude Sonnet 4.5 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 Sonnet 4.5 or Claude Sonnet 5?

For the stated presets, chat costs $0.0105 on Claude Sonnet 4.5 and $0.007 on Claude Sonnet 5; repository review costs $0.195 and $0.13; the cache-heavy agent loop costs $0.81 and $0.18. Claude Sonnet 4.5 does not fit this workload in one request. Claude Sonnet 4.5 has no published cached-input rate, so cached tokens use its listed input rate.

Which has the larger context window, Claude Sonnet 4.5 or Claude Sonnet 5?

Claude Sonnet 5 has the larger documented context window: 1M, compared with 200K.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated September 4, 2026

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