Long documents
Prompts that approach the documented context limit
Claude Sonnet 5
Claude Sonnet 5 has the larger documented context window.
Confidence: documented
Claude 3.5 Sonnet vs Claude Sonnet 5
Updated November 13, 2026. Rank says Claude Sonnet 5 is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.
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Decision reading
Claude Sonnet 5 has the higher public point estimate, 63.83 versus 25.33. Their conditional score ranges do not overlap. These ranges do not establish rank confidence. 4 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
- API price per 1M tokens
Claude 3.5 Sonnet: $3 input / $15 output
Claude Sonnet 5: $2 input / $10 output
- Context window
Claude 3.5 Sonnet: 200K
Claude Sonnet 5: 1M
- Released
Claude 3.5 Sonnet: June 1, 2024
Claude Sonnet 5: June 30, 2026
- Shared results
- 4
- Claude 3.5 Sonnet only
- 1
- Claude Sonnet 5 only
- 28
- Like-for-like categories
- 0 / 8
Estimated: Claude 3.5 Sonnet · Supported: Claude Sonnet 5. Conditional ranges do not establish rank confidence.How the comparison works
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
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-ratesCoding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
Claude 3.5 Sonnet is not ranked on the public lane for coding, so no winner is named for coding.
Confidence: limitedAgentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Claude 3.5 Sonnet is not ranked on the public lane for agentic, so no winner is named for agentic.
Confidence: limitedCache-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. Claude 3.5 Sonnet has no published cached-input rate, so cached tokens use its listed input rate.
Confidence: rate-fallback
Which one for a specific job
Choose a job from the LLM Selector's task catalog to see the category row it rests on, under the same basis rules as the table below. A directional row stays directional; choosing a job never creates a winner.
The same task catalog as the LLM Selector. Each job names the evidence surface it rests on; nothing here adds a new score.
—Claude 3.5 Sonnet51.7Claude Sonnet 5
Not comparable · BenchAlign v5.8
The coding row is not comparable on the public lane: at least one model is not measured or not ranked there.
Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.
Same basis rules as the category table below
Or describe your own job
The LLM Selector reads what you need a model for and returns a shortlist, ranked in the same order the job pages publish.
Describe the task and constraints. This selector recommends models; it cannot carry out the task or access your files and accounts.
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What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
1 Claude 3.5 Sonnet only
4 Shared
28 Claude Sonnet 5 only
1 category rests on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.
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.
SWE-bench VerifiedCoding
Normalized gap 36.2Claude 3.5 Sonnet:49%Claude Sonnet 5:85.2%LiveCodeBench (Vals)Coding
Normalized gap 32.8Claude 3.5 Sonnet:49.6%Claude Sonnet 5:82.4%MMLU-Pro (Vals)Knowledge
Normalized gap 9.1Claude 3.5 Sonnet:78.4%Claude Sonnet 5:87.5%
Bars run 0–100 on each benchmark’s normalized display scale
Category results, on a stated basis
Each row shows the public-lane category score for both models: the BenchAlign v5.8 lane for agentic, coding, reasoning, multimodal, 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.
Knowledge
Directional only- Claude 3.5 Sonnet
- 26.6
- Estimated · #165/180
- Claude Sonnet 5
- 61.8
- Supported · #43/180
- Basis
- BenchAlign v5.8 lane · 3 vs 6 public rows
- Reading
- Directional only
Agentic
Not comparable- Claude 3.5 Sonnet
- Not ranked
- Claude Sonnet 5
- 62.5
- Supported · #22/135
- Basis
- BenchAlign v5.8 lane · 0 vs 10 public rows
- Reading
- Not comparable
Coding
Not comparable- Claude 3.5 Sonnet
- Not ranked
- Claude Sonnet 5
- 51.7
- Supported · #40/162
- Basis
- BenchAlign v5.8 lane · 2 vs 11 public rows
- Reading
- Not comparable
Reasoning
Not comparable- Claude 3.5 Sonnet
- Not ranked
- Claude Sonnet 5
- 59.8
- Estimated · #32/160
- Basis
- BenchAlign v5.8 lane · 0 vs 0 public rows
- Reading
- Not comparable
Multimodal
Not comparable- Claude 3.5 Sonnet
- Not ranked
- Claude Sonnet 5
- 60.4
- Supported · #34/67
- Basis
- BenchAlign v5.8 lane · 0 vs 3 public rows
- Reading
- Not comparable
Multilingual
Not comparable- Claude 3.5 Sonnet
- Not ranked
- Claude Sonnet 5
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- Claude 3.5 Sonnet
- Not ranked
- Claude Sonnet 5
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- Claude 3.5 Sonnet
- Not ranked
- Claude Sonnet 5
- 64.9
- Unranked · 2 rankable rows
- Basis
- Provisional lane · 0 vs 2 weighted rows
- Reading
- Not comparable
| Category | Claude 3.5 Sonnet | Claude Sonnet 5 | Basis | Reading |
|---|---|---|---|---|
| Knowledge | 26.6Estimated · #165/180 | 61.8Supported · #43/180 | Directional onlyBenchAlign v5.8 lane · 3 vs 6 public rows | Directional only |
| Agentic | Not ranked | 62.5Supported · #22/135 | Not comparableBenchAlign v5.8 lane · 0 vs 10 public rows | Not comparable |
| Coding | Not ranked | 51.7Supported · #40/162 | Not comparableBenchAlign v5.8 lane · 2 vs 11 public rows | Not comparable |
| Reasoning | Not ranked | 59.8Estimated · #32/160 | Not comparableBenchAlign v5.8 lane · 0 vs 0 public rows | Not comparable |
| Multimodal | Not ranked | 60.4Supported · #34/67 | Not comparableBenchAlign v5.8 lane · 0 vs 3 public rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Instruction following | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Math | Not ranked | 64.9Unranked · 2 rankable rows | Not comparableProvisional lane · 0 vs 2 weighted rows | Not comparable |
Ranks count the models scored in each category’s lane, so the agentic, coding, reasoning, multimodal, and knowledge denominators (BenchAlign v5.8) differ from the provisional-lane categories. Unranked scores sit on the provisional lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.
Supported evidence per lane · bars run 0–100Methodology
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
- 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 3.5 Sonnet
- $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 3.5 Sonnet
- $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 3.5 Sonnet 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.
Your workload
Enter a month of tokens to price it at both models’ listed API rates.
- Claude 3.5 Sonnet
- $60.00
- per month
- Claude Sonnet 5
- $40.00
- per month
Standard listed rates, no batch or volume discounts.
Cached input falls back to the list input rate only where a cached rate is unpublished
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationClaude 3.5 SonnetClaude Sonnet 5
Context window
Maximum documented context; output-token limits may be lower.
Claude 3.5 Sonnet
200K
Claude Sonnet 5
API model ID
Claude 3.5 Sonnet
Not sourced
Claude Sonnet 5
claude-sonnet-5
Anthropic model overviewCached-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
Claude Sonnet 5
$0.2 per 1M cached input tokens
Claude API pricingDocumented inputs
Claude 3.5 Sonnet
text, image
Anthropic Claude 3.5 Sonnet launch postClaude Sonnet 5
text, image
Anthropic model overviewDocumented outputs
Claude 3.5 Sonnet
Claude Sonnet 5
Provider availability
Claude 3.5 Sonnet
Not sourced
Claude Sonnet 5
Generally Available · Claude API
Anthropic model overviewReasoning profile
Claude 3.5 Sonnet
Non-Reasoning
Claude Sonnet 5
Reasoning
Weight access
Claude 3.5 Sonnet
Proprietary
Claude Sonnet 5
Proprietary
License
Claude 3.5 Sonnet
Proprietary
Claude Sonnet 5
Proprietary
Release date
Claude 3.5 Sonnet
2024-06-01
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 point estimate, 63.83 versus 25.33. Their conditional score ranges do not overlap. These ranges do not establish rank confidence.
- 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.
Questions
Which is better, Claude 3.5 Sonnet or Claude Sonnet 5?
Claude Sonnet 5 has the higher public point estimate, 63.83 versus 25.33. Their conditional score ranges do not overlap. These ranges do not establish rank confidence. The page therefore keeps the decision tied to the specific documented workload.
Which is better for coding, Claude 3.5 Sonnet or Claude Sonnet 5?
Claude 3.5 Sonnet is not ranked on the public lane for coding, so no winner is named for coding.
Which is better for agentic tasks, Claude 3.5 Sonnet or Claude Sonnet 5?
Claude 3.5 Sonnet is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.
Which costs less, Claude 3.5 Sonnet or Claude Sonnet 5?
For the stated presets, chat costs $0.0105 on Claude 3.5 Sonnet 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 3.5 Sonnet 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 Claude Sonnet 5?
Claude Sonnet 5 has the larger documented context window: 1M, compared with 200K.
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence33 rows
Agentic
Terminal-Bench 4.1
Claude 3.5 Sonnet—Claude Sonnet 512.10%SourceNot directly comparable
Terminal-Bench 3.0
Claude 3.5 Sonnet—Claude Sonnet 514.6%SourceNot directly comparable
Terminal-Bench 2.1
Claude 3.5 Sonnet—Claude Sonnet 580.4%SourceNot directly comparable
BrowseComp
Claude 3.5 Sonnet—Claude Sonnet 584.7%SourceNot directly comparable
HLE w/ tools
Claude 3.5 Sonnet—Claude Sonnet 557.4%SourceNot directly comparable
OSWorld-Verified
Claude 3.5 Sonnet—Claude Sonnet 581.2%SourceNot directly comparable
Terminal-Bench 2.1 (Vals)
Claude 3.5 Sonnet—Claude Sonnet 574.5%SourceNot directly comparable
ApprenticeBench
Claude 3.5 Sonnet—Claude Sonnet 516%SourceNot directly comparable
MazeBench
Claude 3.5 Sonnet—Claude Sonnet 50%SourceNot directly comparable
OSWorld 2.1
Claude 3.5 Sonnet—Claude Sonnet 557.0%SourceNot directly comparable
Coding
SWE-bench Verified
Claude 3.5 Sonnet49%SourceClaude Sonnet 585.2%SourceClaude Sonnet 5 leads this result
LiveCodeBench (Vals)
Claude 3.5 Sonnet49.6%SourceClaude Sonnet 582.4%SourceClaude Sonnet 5 leads this result
SWE-bench Pro
Claude 3.5 Sonnet—Claude Sonnet 563.2%SourceNot directly comparable
SWE Multilingual
Claude 3.5 Sonnet—Claude Sonnet 578.3%SourceNot directly comparable
SWE Multimodal
Claude 3.5 Sonnet—Claude Sonnet 528.1%SourceNot directly comparable
Terminal-Bench 2.1
Claude 3.5 Sonnet—Claude Sonnet 580.4%SourceNot directly comparable
FrontierCode 1.1 Main
Claude 3.5 Sonnet—Claude Sonnet 542.7%SourceNot directly comparable
CursorBench 3.2
Claude 3.5 Sonnet—Claude Sonnet 561.5%SourceNot directly comparable
VulcanBench CII v1
Claude 3.5 Sonnet—Claude Sonnet 589.2%SourceNot directly comparable
SWE-bench (Vals)
Claude 3.5 Sonnet—Claude Sonnet 579.6%SourceNot directly comparable
CursorBench 4.0
Claude 3.5 Sonnet—Claude Sonnet 534.1%SourceNot directly comparable
Multimodal
Knowledge
GPQA
Claude 3.5 Sonnet59.4%SourceClaude Sonnet 5—Not directly comparable
GPQA Diamond (Vals)
Claude 3.5 Sonnet59.3%SourceClaude Sonnet 588.9%SourceClaude Sonnet 5 leads this result
MMLU-Pro (Vals)
Claude 3.5 Sonnet78.4%SourceClaude Sonnet 587.5%SourceClaude Sonnet 5 leads this result
HLE
Claude 3.5 Sonnet—Claude Sonnet 557.4%SourceNot directly comparable
HLE w/o tools
Claude 3.5 Sonnet—Claude Sonnet 543.2%SourceNot directly comparable
HLE-Verified
Claude 3.5 Sonnet—Claude Sonnet 531.0%SourceNot directly comparable
LABBench2
Claude 3.5 Sonnet—Claude Sonnet 580.1%SourceNot directly comparable
Math
33 public results · 4 shared
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Last updated November 13, 2026